Environment Variables: Recent Episodes

View Details

In this episode of Environment Variables, host Chris Adams dives into the evolving landscape of sustainable web development with Alexander Dawson and Tzviya Siegman from the World Wide Web Consortium (W3C). Dawson and Siegman discuss the W3C’s efforts to develop Web Sustainability Guidelines (WSG), a comprehensive set of evidence-based practices aimed at reducing the environmental impact of web technologies. They explore the creation and potential impact of these guidelines, especially as global interest grows in embedding sustainable practices within web standards. The episode also covers the challenges of driving adoption across public and private sectors, the role of testability in sustainability guidelines, and future directions for standards that minimize digital carbon footprints. This engaging conversation provides listeners with insights into how W3C’s sustainability initiatives could shape the future of the web.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Tzviya Siegman: LinkedIn | Website * Alexander Dawson: Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

Resources:* The Week in Green Software: Greening Web Standards at the W3C w/ Alex Dawson and Anne Faubry [04:20] * Web Sustainability Guidelines (WSG) 1.0 [04:56] * GRI [16:36] * RDF-star Working Group [19:26] * General policy framework for the ecodesign of digital services version 2024 [21:34] * Sustainable Web Design Community Group [31:04] * Sustainable Web | Interest Groups | Discover W3C groups | W3C [31:06] * The 2024 Web Almanac [33:40]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

**TRANSCRIPT BELOW:

Alexander Dawson:** We have tried to, even at the point of being a community group,

treated this as seriously as possible and made sure what we've created to be as evidence led as possible.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host, Chris Adams. Hello, and welcome to Environment Variables, where we bring you the latest news and insights from the world of sustainable software development. I'm your host, Chris Adams. Green software covers a lot of different kinds of software. And today, we're checking in on the work of a group of fellow travelers in the world of web development, and more specifically, the World Wide Web Consortium. If you're not familiar with the World Wide Web Consortium, the W3C, it's effectively the place where people who build the web define how the web works. And where standards like HTML works, how CSS works, and how they're made accessible, and so on. And long before the Green Software Foundation existed, there was the W3C Sustainable Web Design Community Group, chaired by Tim Frick at the agency Mighty Bytes, who was also the author of the O'Reilly book, Designing for Web Sustainability. And in the last few years, there's been a real uptick in activity in this group, with the creation of the W3C Web Sustainability Guidelines and regular monthly community calls to coordinate the work on developing more sustainable web development practices. So what exactly are the Web Sustainability Guidelines and who are they for? If you cared about sustainability in the digital realm, why would you try getting involved in a group like the W3C in the first place? How does this even change the way people build the web and consume web services? And how do we make them more sustainable? Joining us today are two key figures from the W3C to help us explore these themes. Alex Dawson, one of the editors of the Web Sustainability Guidelines at the W3C, and Tzviya Siegman, at the W3C's new sustainability lead. So in alphabetical order, Alex, you win here. So I'm just going to hand over to you to briefly introduce yourself before we hand over to Tzviya. Is that okay?

Alexander Dawson: Yep, that's fine. Hi, everyone. I'm Alex Dawson, and I'm an invited expert in the W3C Sustainable Web Interest Group. And as Chris has mentioned, I'm the editor of the Web Sustainability Guidelines. And I've also recently been involved in co-authoring the upcoming sustainability chapter in this year's Web Almanac.

Chris Adams: Cool. Thanks for that, Alex. Tzviya, can I give you the floor to do the same?

Cool.

Tzviya Siegman: Sure. Thank you for having me. I'm Tzviya Siegman. I'm the sustainability leader at W3C. I recently joined the staff of W3C, but I've been involved here more than 10 years. I also do member engagement in North America. I recently been involved in setting up the interest group in W3C and getting used to being on the staff instead of being a member.

Chris Adams: Thanks, Tzviya. And if you're new to this podcast, my name is Chris Adams. I am the host of this podcast, but I'm also the executive director at the Green Web Foundation. I also work Inside the Green Software Foundation as one of the chairs of the policy working group as well. And I'm one of the maintainers of the library CO2.js, a tool that's used in a number of digital sustainability projects. Before we dive into this conversation, here's a quick reminder that we're going to share a transcript to this and links to all the projects that are just mentioned in our show notes. And, you'll need to look for that on podcast.greensoftware.foundation to find that. So if you're listening to this via Spotify or YouTube, you might not find them. So please remember to look that up there. Alright, so, with that, I think the two of you are sitting comfortably, right? Alex, maybe I'll just hand over to you. So, last time, around about this time last year, I believe you joined us with Anne Faubry, and you spoke to us about the second draft of the Web Sustainability Guidelines. And most recently, I saw you presenting at the Green IO London conference about, again, web sustainability, and specifically the process of making these guidelines for people to follow. So, as I understand it, you're now at, is it draft 8, or possibly draft 9? So, I'd like to ask a little bit about how they get built, but before we do that, could you just give a brief summary of what the Web Sustainability Guidelines are to the uninitiated?

Alexander Dawson: Yeah, absolutely. Essentially, the Web Sustainability Guidelines are an evidence-based set of advisory guidelines. Many people may be aware of the Web Content Accessibility Guidelines as our founding principles of accessibility. And we've kind of followed a similar set of principles, but designing and creating them for the sustainability community.

And they've been in development for about three years now. And obviously, They are to assist those who want to make digital products and services more sustainable through practical techniques. And obviously, the science is developing rapidly as is the sustainability field and of course, legislative compliance targets.

So it's a much needed feature that the web really requires. And, it's a sort of Global growing focus as climate change is becoming a ever more important topic of discussion.

Chris Adams: Cool, thanks. Alright, there's two forlorn questions I might ask. So, first of all, you spoke about the Web Sustainability Guidelines. That's quite a mouthful. Is it okay to call them like the WSGs? Is there a short term that we should use for that?

Alexander Dawson: Yep, WSGs is perfectly fine. We use WSG as our sort acronym.

Chris Adams: Got it, okay. So I use WSG, a bit like the kind of web content accessibility guidelines, or sometimes the WCAG, right? I'll call it. So WCAG and WSG. Got it. Okay. And also, I know that you're at Green.io, the conference, it's like one of the places to be going to if you're going to speak about digital sustainability. How was that? How did you find it?

Alexander Dawson: Yeah, it was amazing, really. I mean, you were there yourself. It was definitely the place to be. It was sort of like the Woodstock of sustainability, pretty much. Anyone and everyone who could be there managed to sort of cram in the place, standing remotely at the back of the conference room. There were sort of all the faces from all these sort of major players that could sort of get there.

Yeah, it was a pretty amazing event. all credit to sort of Gail and getting sort of everybody involved in the conference. It was pretty much the event of the year as far as digital sustainability goes.

Chris Adams: So, you enjoyed that.

Alexander Dawson: Definitely, yeah.

Chris Adams: All right, okay, and Tzviya, if I hand over to you, as I understand it, you work the W3C, and you're the new sustainability lead, and part of your day job is essentially guiding the existing community group that created some of these guidelines. But there's also work to create a more formal, I think they're called interest groups, which is slightly different. We'll explore that a little bit later on. Before we do that, can I just backtrack to talk about how you ended up working as a sustainability lead in the W3C? Because I had no idea there was one until I heard about your involvement in this. And honestly, I was quite pleased because it's been something inside the W3Cs like, architectural guidelines, their TAG, they said the web should be sustainable.

And now they've actually got someone who's talking about this. So that was really nice to hear. So yeah, how'd you get into this? What's the story that this came about?

Tzviya Siegman: I'll give you a short history of my career. I started working in standards back in 2008. I worked for a publishing company, and I was doing the digital side of things, looking at XML, and all of a sudden, ebooks became the thing. And it was, "oh my goodness, Tzviya, we need somebody to work on this." And we created a hundred based on PDF and CR, and I was like, this doesn't really look right, maybe I can fix it. And I did. In order to fix it, you need to read standards. And the whole ebook program came under my leadership, and I was not very high up in the food chain at that point. Eventually, I started working on the standards with an organization called the International Digital Publishing Forum. Because that's where EPUB was at the time. And over the next six years, the IDPF merged with the W3C. And I became the chair of the publishing working group. And then I joined the W3C's advisory board. And then I became chair of the advisory board. And etc. And then I got laid off. And I worked with some people within the W3C to develop this role because I have become interested in sustainability. All along I've been working in accessibility, and the part of technology that's always really interested me is not necessarily creating faster products. That's, time to market was always intimidatingly working with the product managers and things like that. At my job in publishing, I was always frustrated when project issues like accessibility got thrown to the side because there was a new feature game developed. It's nice to have a new feature, but if it's not accessible, if he doesn't have pride, then we were, yeah. And so sustainability is in that area as well. I used to work on what a manager, a former manager of mine called the illities. Accessibility, sustainability, and now I'm still, this is living the dream for me. So, I was able to sculpt this job with the W3C, which is really a dream for me. And the fact that sustainability is mentioned in the W3C's vision, I'll take a little credit for that, because I was one of the people who wrote that. So, just a little credit, because there were a lot of people involved in writing that. But here we are, and we are really excited to be working on sustainability in an interest group, which you mentioned is not quite the same as the working group, because some of the differences now or later that we're working on a specification would, I can explain the different types of specifications, but I'm really excited to be leading the community group into something more formal than just a new file, even though we had a lot of uptake, where we were able to form a policy and an interest group to be through soon.

Thank you.

Chris Adams: I see, okay, so it sounds like this is not your first rodeo. You've been through the process of seeing how standards get developed, and this is why you being involved with this helps, because there may be a bunch of people who have, who might be curious about this and have all the things you kind of wish for, but you've seen how this works, you've seen how the sausage gets made, and that's, some of your role is to help steer some of that through so we end up with something that people actually can use and adopt in their work and things like that, then.

Tzviya Siegman: Yeah, absolutely. The work in W3C, when it's an interest group or a working group, it goes through a pretty rigorous process, and I can talk about that process in more detail in the literature.

Chris Adams: Thanks! Alright, okay, thanks for that, Tzviya. So hopefully we've caught up the audience to where we are today, November 2024. We spoke a little bit about the history. And I teased about the creation of this new group, like an interest group that has some more formal backing within the W3C. So for people who are not au fait with how web standards are formed, or what an interest group is compared to a community group, can you maybe just explain a little bit about why this is a big deal and what it makes possible that wasn't before?

Tzviya, I'll hand over to you, then maybe Alex will come in with some specific examples, because he was the author of the guidelines.

Tzviya Siegman: Yeah, thank you. I'll talk a little bit about what it is that we try to accomplish with standards and what that means in W3C. In W3C, standards require interoperable implementations. Interoperable is achieved by testable implementations where we test things to make sure that they work in at least two instances. Sometimes standards are codified by regulatory bodies. We see this with something like USBC in the EU. We also see this with WCAG, the Web Content Accessibility Guidelines being pointed to by various legislation. There are a lot of standards. Like WCAG, where this is pointed to, and the W3C, we have community groups, so anybody can start a community group, it doesn't have the formal structure of a W3C group, it's people get together, they work on things, and it's the incubation process, we call it, or just people get together because they need

Chris Adams: Okay.

Tzviya Siegman: An interest group is, has the authorization of the W3C's advisory committee. Everybody has to vote on the work. A member of each W3C member organization has the ability to vote yes or no or maybe. Yes, but I would like to see this then changed on the formation of an interest group. And an interest group can write statements. A working group is when the same came with the advisory committee, but they actually have the recommendation track, which is what W3C officially calls standards. The sustainability group is an interest group where they write in statements. Because the Web Sustainability Guidelines include a lot of things that are not necessarily testable. Although there are a lot of testable statements in there, and I'll turn it over to Alex to talk about how we'll proceed with that.

Chris Adams: Okay, thanks for that, Tzviya. So if I just paraphrase that for people, there's almost like an escalating layer of authority or formality that comes through this. And it may be that the bar is somewhat higher with the things that get published by an interest group compared to a community group. And like there's an escalating scale all the way up to having like full blown standards.

And this is like the midway point. And, like, Alex, if that's about right, I'll hand over to you, Alex, and maybe you can chime in on some of it, because, yeah, you are very hands on when writing some of these, perhaps.

Alexander Dawson: Yeah, obviously, we are trying to be as rigorous as possible because throughout the creation process, we have tried to, even at the point of being a community group, treated this as seriously as possible and made sure what we've created to be as evidence led as possible. And we are still in the process of trying to create as much measurability data as we can, which is something that we are going to be increasingly focused upon as an interest group.

So, with regards to testability, which is something that obviously interest groups, having testable implementations, it's not something that we have to be as strict upon, we still want to make sure our work is as rigorous and testable as possible. Because there may come a point in the future that we may want to have that testable compliance state for working what we have created in with legislative conformance and being able to do so may require at some point, obviously in the far future, taking our work from an interest group state to a working group state to get that recommendation status.

But that is something, in the far off distant future, as Veer will probably nod and agree with. But for the moment, obviously, we want to focus on making what we have created as rigorous as possible purely because anyone who is going to utilize our work, we want to have the best quality evidence for anything we are submitting as guidance.

We want to be able to. tell people using our work, this is the best way that you can implement something in your product or service because the evidence shows that this will have the greatest impact in terms of sustainability. And it's something that we've been very much focused upon when creating the Web Sustainability Guidelines from the offset, which is why we've got so many references within our work.

We've got quite a lot of material relating to things like GRI and such. So it's something that we've been very much focused upon from the offset.

Chris Adams: Okay, and by GRI, you're referring to the Global Reporting Initiative here, right?

So that's one of the other groups that talk about, okay, this is how you, set out what counts as sustainable, for example, and they've done a bunch of work that you're referring to with that one there.

Alexander Dawson: Yeah. It's one of the measures that we've been utilizing alongside obviously academic material and many other forms of tooling as well.

Chris Adams: Alright, thanks for that, Alex. So, I'd just like maybe touch on that a little bit more, because one thing that I know that we've seen, like, in France, for example, there are something like guidelines which are kind of mandated for government websites now, and it sounds like you might be looking for something like that on a more international scale that could be adopted in other parts of the world, and I mean, for folks who are new to this, the W3C has, like, a public mailing list, and if you look on there, you'll see, like, there are people from, say, I think, Singapore. The government of Singapore basically said, "hey, we're looking for some standards like this, or something for us to adopt," and I know there are people in other parts of the world who are basically saying, "I want to push for this, but I need some kind of something either like a standard or a set of guidelines I can ask my team to be following," and it sounds like that's the kind of push, because I know the WSGs have been in some kind of usable form now, but it feels like this seems to be a real push for adoption to get larger organizations to use them, who commissioned significant projects. And we spoke about how these might not be standards with a capital S, there might be a kind of guidance for sustainable software, but in terms of providing a reasonable expectation of what you can expect a responsible practitioner to do, that seems to be what they'd be shooting for.

So maybe we could talk a little bit about what adoption looks like here, and maybe we can hear some stories about organizations expressing interest in adopting these and what that process looks like, because, yeah, this is a new field, and I know that we've just spoken about how different places are looking for this. And Alex, I suspect you've been in some of these conversations, so maybe if I hand over to you, and then maybe let Tzviya chime in, because she's seen this happen a few times outside of just sustainability.

Alexander Dawson: Yeah, in terms of adoption, meeting the success criteria is rather open to interpretation at this point. I mean, we're, as I've mentioned, we're aiming to improve measurability data as an interest group, so we can better sort of lead by evidence. Regarding if a particular technique has a greater impact or not and that's sort of on the horizon.

Currently we sort of follow a similar practice to the Web Content Accessibility Guidelines with their accessibility techniques and much of that can be seen with, in our STAR supplement, Sustainable Tooling and Reporting, as that outlines optional techniques that are currently deemed, where appropriate, machine testable, so can be sort of repeated and used to showcase which success criteria can be repeatable and, implementable to meet certain success criteria within the particular guidelines.

Now, obviously, you don't have to follow them, they're not sort of gospel, and we're working to sort of improve them where we can along the pathway. But we've been sort of trying to improve upon this to sort of help people in terms of general adoption. And regarding sort of interest from the public and private sector, we've had quite a lot of interest definitely from various organizations.

I mean, I have been sort of trying to keep track wherever possible, and there have been a number of agencies globally where they mentioned that they have been starting to utilize and implement our work and there have been a lot of government departments who have got in touch who are openly interested in utilizing what we have created, even though it's in draft format, or have interest in actually for tracking our progress or getting on board with what we've created potentially for what could be future compliance, so it's good signs and sort of generally good feeling, if nothing else, that we're potentially on the right track with what we have been creating.

Chris Adams: Okay, all right, so if I understand that correctly, so I spoke about how France has, they've set up some standards themselves already. So like, "all our websites made by the public sector have to meet these standards." In other parts of the world, there might be people saying, "well, we're going to set some of this, and rather than write all this stuff ourselves, we'll refer to these things as like, we'll defer to that, as that's what we're going to hold as our bar that everything needs to meet," for example.

That's what some of this stuff is. It seems to be like the direction that's heading in. Okay, so that gives you some idea of how that might work. But, Tzviya, I am, I'll hand over to you because, obviously, it's a bit more complicated than that. And like, there's, we can ask for certain things, but that's not the same as people actually adopting this stuff for example. Like, if it was, well, we would see a probably more accessible web, for example. So, Tzviya, can I hand over to you to talk a little bit about, like, actually adoption and how this happens, or if there's any things that you've learned over the last few years that you might share that could help here?

Tzviya Siegman: So, adoption is a really complicated topic. Something that I think many people find shocking when they start looking at standards is that we can write standards in an incredibly idealistic way. But we can't actually make anybody use them. It's very frustrating. This is why the implementation tests were important. But even with testing, we can't promise adoption. And that's why it's important for everybody working on this to become evangelists. And I often say that my job is really evangelism, and a lot of people who have worked at, who are working on sustainability come from the world of accessibility because the role is very similar in terms of evangelism. And it's really important to make sure that the set of issues is a high priority. People who are working on browsers, servers, and in their organizations, like you might have an HR department who has a goal of, let's say, reducing carbon emissions, because that's what everybody says, because as Tim Frick likes to say, they have carbon tunnel vision. They'll say they're reducing carbon by 30 percent by 2030, so just pick a number. They don't know what that means. We need to get to the developers who are actually writing the code, and we need to get to the people who are building the servers, and so on. So that They can actually do the work because the people at HR or the CEO or whoever it is who's making these commitments don't have the tools to do this. Our guidelines give us some of the tools and the guidelines are divided into sections so that this touches a lot of different departments in an organization, and we're trying to break them down so that people can pull out the different sections that are relevant to them, but that adoption step is really important. I'll also say that what you were talking about, Chris, where different governments might be able to point to the guidelines, that's really where adoption is important. But it also comes down to being able to educate people, and we're also going to be working on different education materials. I love WCAG, I'm a big fan, but a lot of people are deeply critical of WCAG because it's so hard to understand. So we're trying to make ours a lot easier to understand, and hopefully we'll be able to be really successful with it.

Chris Adams: Okay, thanks for that, Tzviya. So, you, so there's two things that kind of came out of that. So, one of them was about, Alex, you spoke about these things being testable. And presumably, this is some of the stuff that you might see when people are using, say, web page tests, which has, like, Carbon control, or EcoGrid, or some of these things. If you can test for something, then you can provide some guidance as part of the analysis process, or you can automate this and check, like, has this got better or has it got worse? That's what some of the kind of sustainability things presumably would afford, right? And that's what you're kind of referring to with some of that.

And that might be something that you're essentially able to, like, enforce a standard on, or make sure it's meeting the standard that you've set out in some kind of agreement, right?

Alexander Dawson: Yeah, absolutely. If we can provide something that's testable or something that people can utilize, then it's something that toolmakers, people creating products and services, can implement with what they're creating. And that will obviously help us do our job because for people creating tools like, Website Carbon, Ecograder, they can filter that down into their processes so that rather than individuals having to read an extensive specification, with a few clicks of a button, it can provide feedback through reports, potentially tools that can be integrated within IDEs like Visual Studio Code, things that could be integrated within browsers such as the DevTools environments within, say, Google Chrome and Firefox and such. Lighthouse Project is a prime example.

These are things that if it's machine testable, it can be integrated within tooling and that will help take a lot of the friction out of people being able to quickly identify where the problems are occurring, how much of a problem it is, and how to identify what resolution needs to be,

Chris Adams: kind of remedial action you might take. All right, okay, thanks for that. Okay, so that helps summarize that, and Tzviya, you were talking a little bit about, okay, different groups might have different stakeholders, and you were referring to public sector as one group that might have legally binding targets.

For example, we know that in the UK, they have a target to reduce emissions by however much, and in Europe, it's reduced emissions by 55 percent by the end of, wow, in five and a half years time, for example, I mean, I'm speaking to you in the middle of an election, so there's a difference about, but like, up until yesterday, there was a whole thing about the federal government being the single biggest purchaser of green energy, which was forcing a kind of switch to cleaner energy, for example, things like that.

That seems to be what you're referring to, right?

Tzviya Siegman: Yeah, there's public and private, but there's also different stakeholders, such as product managers versus developers. Individuals within an organization.

Chris Adams: Ah, I see, so like when you've got product managers, if they know what to ask for, they're able to, that helps inform that conversation with the team they're working with and say, "can we please agree to meet these standards or have something like that." They don't need to be the specialists themselves to know that if there's a standard or set of guidelines out there, that at least gives a shared set of minimum standards that the work's going to be run at, basically.

Tzviya Siegman: Yeah, absolutely.

Chris Adams: Okay, cool. That provides a bit more guidance about, I guess, the theory of change behind some of this. So, we're just starting to come up to time, and I wondered if we might be able to look forward to, like, what's on the horizon in the world of sustainable web development, and if there's anything that you folks have, that maybe, if I was to ask you, What should be on an interested listener's radar if they were interested in web sustainability? If I hand over to you, Alex, first, and then over to you, Tzviya, is there anything, like, what should people be looking out for between now and the end of the year, for example, or perhaps in Q1 2025? What's on your list, Alex?

Alexander Dawson: I think the thing that's dominating everybody's discussion at the moment is just sort of AI, isn't it, really? Everyone's talking about it, it's causing a lot of discussions around sort of how big an impact it's going to have, and it's pretty much going to be the dominating discussion around, how we're going to sort of wrangle around it in terms of legislation and measurements and tolling and Optimization and such, so I think that's going to be a major sort of domineering factor, especially considering how much infrastructure it's currently absorbing in terms of building new facilities and such, so yeah.

Chris Adams: Okay, cool. And are there any particular projects or things that you're expecting to, any releases by projects you follow, or any big things like that you would direct people to? So, they've been listening to this and they might want to find like a follow on link or follow on project to look into. What would you direct people to if they found something that's interesting but wouldn't want to go somewhere else next?

Alexander Dawson: There's not a particular one especially that I've been following. I mean, if I find any useful links or materials, normally it gets sucked straight into our project into the Web Sustainability Guidelines because we have nicely organized references for any useful material that can help people make decisions and such.

So I always like to point people to the guidelines, to the latest release, because I, nicely guard in those links and keep them up to date with all the latest material relating to sustainability. We've got sort of about 1500 odd links, all nicely categorized for people interested in sustainability.

Yeah, it's probably the largest digital sustainability reference library on the web.

Chris Adams: Blimey. Okay. All right. And, Tzviya, is there anything that you might kind of direct people's attention to? Like, we've spoken all about interest groups and community groups, but like, they still run, right? Like, they happen in the, is it monthly? I mean, how, if someone wants to find out about this, what's the process like to start

getting involved in any of this stuff, for example?

Tzviya Siegman: I'll provide links for both the interest group and the community group in W3C. For the community group, you don't need to be a member. For the interest group, you need to be a member of W3C or be what's called an invitative expert, which means provide a reason that you should be invited and, like, get a review by me and the chairs of the interest group and then show that you'll do the work. Also, something I'll be working on in the next year or so is creating a horizontal review program for the W3C and sustainabilities. The W3C prides itself on doing horizontal review on all standards in the areas of accessibility, privacy, security, and internationalization, meaning, we'll say the example of accessibility, every, there's a review of every single specification to make sure that the specification itself is accessible and will introduce accessibility problems. So I have the job of creating this for sustainability.

Chris Adams: Sorry to interrupt, can I just check, because I'm not sure I'm familiar with the horizontal, is the idea there being that you've got three or four standards, and you want them to be consistent with each other? Is that what horizontal reviews, or is there something else?

Tzviya Siegman: Horizontal review means that, so, let's say you have a new CSS specification. There are dozens of those every year. There's an accessibility checklist for the people in the CSS working group to take a look at. And then we have the opportunity to speak with people who are experts in accessibility to make

Chris Adams: okay.

Tzviya Siegman: accessibility issues onto the web. So I will be working to create a sustainability horizontal review checklist. I don't know yet how I'll be doing this, but that's part of my job as sustainability lead. I'm very excited about this because this has not been done before. So we want to make sure that the W3C is not bringing new sustainability issues to the web.

Chris Adams: Oh, I see. Okay. So if I check if I understand that, and maybe this is one concrete example, I know that there are certain bits of CSS, like there are certain filters that if you run them, you can basically cook that CPU in your laptop. I think Florian at Mozilla, he's one of the people who built the Firefox profiler.

He has this kind of party trick where he basically takes you to a single web page and it triggers one thing which just cooks your machine, because it just runs all the cores really, really hard, basically, just because it's doing a kind of gentle group. It sounds like something a bit like that, like, if someone's going to introduce a feature, they're aware of some of the knock on impacts, or they might have, yeah, okay, I think I understand that now.

Tzviya Siegman: And I'm going to just remind Alex that he's working on the web almanac.

Chris Adams: Yeah,

Tzviya Siegman: And maybe you want to plug that.

Alexander Dawson: Yeah, absolutely. We've got the new edition of the Web Almanac, which will be coming out this month. I've contributed to the sustainability chapter, and anyone who's interested in sustainability will be wanting to check out the results of that. So, yeah.

Chris Adams: Cool, and for people who are not familiar with the Web Almanac, this is essentially a bit like a kind of state of the web. Every year it comes out, tells everyone what's going on. So you've been saying, essentially it's state of sustainability of the web, that's what your chapter's focusing on, right?

Alexander Dawson: Yeah, absolutely.

Chris Adams: Brilliant, well if that's visible, we'll share a link to that in the show notes, but anyone who's curious, Web Almanac seems like a fairly easy term to search in your chosen search engine. Brilliant. Okay, well, I think we've got a good few pointers, and we'll also link to some of the community groups that we spoke about here. I suspect there's a conversation to have about how the GSF should work with the W3C for some of the groups there, because I know there is, we spoke about AI, and there's a GSF, Green Software Foundation Working Group, specifically focused on AI. It may make sense to do something along those lines for web specifically, because it's another clear sector and a clear application of software.

So, just before we go, maybe I should ask, if people want to find out more about you and your work, where should we, where should people be looking? Tzviya, if I start with you, like, where should we go? Is there a LinkedIn page or something like that you'd direct people to?

Tzviya Siegman: Sure, I'll drop my LinkedIn page, it's linkedin.com/Tzviya, I think. And there's also my bio on the W3C staff page, which I don't remember the URL off the top of my head, but I'll find out.

Chris Adams: Okay, cool. And Alex, for you as well?

Alexander Dawson: Mine's pretty straightforward. You can find my details on my website, and my name is my URL, so it's alexanderdawson.com.

Chris Adams: Alright, that seems nice and easy to Google and look up, and Alexander and Dawson are spelt like you would expect them to be spelt as well.

Alexander Dawson: Absolutely.

Chris Adams: Brilliant. Well, folks, thank you so much for giving us a bit of a kind of deep dive into the world of the W3C, and how web standards get made, and how we can actually, how they can be adopted, and wish you best of luck.

Hopefully I'll see you at one of the other community groups, or the meetings every month, and yeah, hope you have a nice week, alright? Take care, folks. Ta ra.

Tzviya Siegman: Thank you.

Chris Adams: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundationon. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode.

View Details

In this episode of Backstage, we go backstage with the Awesome Green Software (AGS) project, a pioneering initiative from the Green Software Foundation’s Open Source Working Group. Project leads Ahmad Antar and Abid Ali, along with contributor Josh Rauvola, share how AGS is building a centralized platform for developers to access tools, libraries, and frameworks to create greener, more sustainable software. They discuss the innovative tech behind AGS, the project’s progress toward launch, and its potential to make green software development accessible to organizations worldwide.

Learn more about the Awesome Green Software Project:
* Awesome Green Software * Digital Emissions

Learn more about our people:* Ahmad Antar: LinkedIn * Abid Ali: LinkedIn * Josh Rauvola: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

Resources:* Algolia [4:03] * Notion [4:04] * Scaphandre [5:07] * CodeCarbon.io [5:15]

Events:* Green Gaming with STRATEGIES (November 9 at 9:00 am CET · Katowice) [07:39] * Implications of AI-Related Data Center Electricity Use and Emissions (November 12-13 · Washington DC [07:58] * Digital Impact Pitch (November 20 at 6:30 pm CET · Virtual) [08:09] * Green Waves Hackathon Closing Day (November 22 at 8:30 am CET · TU Delft) [08:30]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
Chris Skipper: Welcome to Environment Variables, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Skipper. On this episode, we have another edition of Backstage. Here, we'll take you behind the scenes at the Green Software Foundation to highlight ongoing projects and share insights from the members directly involved.

Today, we're diving into the Awesome Green Software Project, an exciting initiative curated by the Green Software Foundation's open source working group. Today, project leads Ahmad Antar and Abid Ali have provided us with some informative content and along with some soundbites from contributor Josh Rauvola to give us the lowdown on the collection of tools, libraries, and frameworks designed to help developers create greener, more sustainable software.

So, what makes this amazing, nay awesome, collection of green software resources tick? Let's explore that in this backstage episode. The GSF is all about building software that emits less carbon. Awesome Green Software fulfills that by creating a one stop shop which compiles research, tools, code, libraries, and training from volunteers that will be used for building applications that emit less carbon into our atmosphere.

There aren't too many tools available today that organizations can use to ensure their software is following sustainability principles. But, Awesome Green Software aims to fill that void. The GSF has the Impact Framework and the Software Carbon Intensity Specification, the SCI. And now, Awesome Green Software to provide that support.

As previously mentioned, Awesome Green Software brings research and resources that will be available at one place for organizations to access, hence reducing their efforts and time to find these tools and rather focus their efforts on building impactful software. Awesome Green Software was an idea that the GSF wanted to start for a while.

GSF member Digital Emissions took the initiative and is bringing it to reality. They have made a lot of progress over the last few months. The front end and back end are almost ready, and they are getting ready to start testing soon. Awesome Green Software is still in the developmental phases, but once it's ready to launch, We are expecting many contributors from the GSF and beyond to start contributing impactful code, tools, and utilities.

It will have a great impact on the overall community because currently it is not easy to find such tools in one place. Next, I'd like to play you a soundbite from Josh. We asked him the question, what are some of the key challenges you've encountered while developing the Awesome Green Software project?

And how did you and your team work to overcome them?

Josh Rauvola: Well, one of the main challenges we've faced is consolidating a vast amount of information and resources into a single user friendly platform. There's so much valuable content out there, but it's scattered across various sources. Organizing it in a way that's easily accessible to developers and other people was a significant task.

We also had to ensure that integrating technologies like Notion for content management and Algolia for search, which we can get into later, would provide a seamless user experience. To overcome these challenges, our team focused on building a solid backend and frontend infrastructure. We've been meticulous in our approach, and we're excited to get this project out into the hands of people that truly care about the environment.

Chris Skipper: With such a comprehensive list of tools and resources, the Awesome Green Software Project provides a bird's eye view of everything related to sustainable software out there on the internet. Can you explain some of the methods that you used to compile such a comprehensive list?

Josh Rauvola: Certainly. One innovative approach we're taking is leveraging powerful AI search capabilities through Algolia. This allows users to quickly find the tools and resources they need to build sustainable software. We're also using Notion as a content management system, which simplifies the process, for contributors to add and update resources in the directory.

By combining these technologies with modern front end frameworks, we're creating a responsive and efficient platform that not only compiles existing resources, but also encourages community engagement and contributions. We're all about being as efficient as possible, so we utilized some of the tools provided on our platform to align better with our awesome green software goals.

Chris Skipper: Could you highlight some of the specific tools, technologies, or frameworks included in the Awesome Green Software Project? What are some of your favorites? And how do they support the project's sustainability goals?

Josh Rauvola: That's a great question. The project includes a variety of tools like the Carbon Aware SDK, which helps developers make their applications carbon aware by optimizing energy consumption based on grid carbon intensity. We also feature tools like Scaphandre, a power monitoring agent that helps measure the energy consumption of servers.

Personally, I'm a big fan of the CodeCarbon.io library. It allows developers to track and reduce CO2 emissions from their computing by integrating seamlessly within their code. These tools support our sustainability goals by providing practical solutions that developers can implement to reduce the carbon footprint of their software.

Chris Skipper: The final question we put to Josh was, throughout the development of the Awesome Green Software project, What valuable lessons or insights have you gained that could benefit other organizations aiming to promote sustainable software?

Josh Rauvola: Well, one of the most valuable lessons we've learned is the importance of accessibility and community engagement. Only by the amazing support of the Green Software Foundation and the team at Digital Emissions have we been able to create such a wonderful platform. Creating a centralized platform where resources are shared.

Green software, easily accessible, significantly lowers the barrier for organizations to adopt sustainable practices. By making it easier for developers to find and use these tools, we encourage wider adoption of green software practices. Now all we need to do is get the word out. I'm sure this podcast will go a long way in doing so.

Chris Skipper: Yes, hopefully it does. I'd like to extend a big thank you to Ahmad, Abid, and Josh for sharing their valuable insights on the Awesome Green Software project. It's evident that this initiative goes beyond just providing resources. Thank you. It's about creating a comprehensive platform where developers can easily access tools, libraries, and frameworks to build greener, more sustainable software.

From their use of innovative technologies like Algolia and Notion to the thoughtful selection of carbon tracking tools, Ahmad, Abid, and Josh have shown us how AGS will make a real difference for organizations like yours. Aiming to reduce their software's carbon footprint. Their dedication to making the Awesome Green Software project a one stop shop is inspiring.

And it's exciting to hear about the milestones reached so far. With the front and back end nearly ready, and testing just around the corner, the team's focus on accessibility and community engagement will undoubtedly drive broader adoption of sustainable software practices as more contributors join after the launch.

We can't wait to see how AGS will shape the green software landscape and empower developers worldwide. slide. Now, before we finish this episode of Backstage, we have a few events to read out. Firstly, a free in person event, Green Gaming with Strategies, on November the 9th at 9am CET in Katowice, Poland.

Learn how the gaming industry contributes to and can mitigate its environmental footprint. Next up, we have Implications of AI related data center electricity use and emissions. A hybrid event happening on November the 12th to the 13th in Washington DC. Explore how to map, measure and mitigate the impacts of AI data center electricity usage.

Next up, a virtual event titled Digital Impact Pitch on November the 20th at 6. 30pm CET. This virtual event will help you discover what is the impact of our daily use of digital technologies. And finally, the Green Waves Hackathon closing day on November the 22nd at 8. 30am CET at TU Delft in the Netherlands.

Network, get talks and celebrate the ideas created during the hackathon. This event is your opportunity to experience the most innovative solutions developed by the Green Waves Hackathon participants. Whether you're passionate about sustainable IT or water research, This closing day will showcase the cutting edge ideas that can help reduce environmental impact.

Join us for a day packed with insightful presentations, live demos, and the excitement of the awards ceremony. Links to all the events and the resources mentioned in the show will be in the show notes below this podcast episode. So, we've reached the end of this special backstage episode. I hope you enjoyed the podcast.

To listen to more podcasts about Green Software, please visit podcast. greensoftware.foundation and we'll see you on the next episode. Bye for now!

View Details

In this episode, we honor the memory of Abhishek Gupta, who was an instrumental figure in the Green Software Foundation and a Co-Chair of the Standards Working Group. Abhishek's work was pivotal in the development of the Software Carbon Intensity (SCI) Specification, now adopted globally. His tireless efforts shaped the future of green software, leaving an indelible mark on the industry. As we remember Abhishek, we reflect on his legacy of sustainability, leadership, and friendship, celebrating the remarkable impact he had on both his colleagues and the world. We are airing an old episode that featured Abhishek Gupta, Episode 5 of Environment Variables. Where host Chris Adams is joined by Will Buchanan of Azure ML (Microsoft), Abhishek Gupta; the chair of the Standards Working Group for the Green Software Foundation and Lynn Kaack, assistant professor at the Hertie School in Berlin to discuss how artificial intelligence and machine learning impact climate change. They discuss boundaries, Jevons paradox, the EU AI Act, inferencing and supplying us with a plethora of materials regarding ML and AI and the climate!

In Memoriam: Abhishek Gupta:
* Honoring Abhishek Gupta | GSF

Learn more about our guests:
* Chris Adams: LinkedIn / GitHub / Website * Will Buchanan: LinkedIn * Abhishek Gupta: LinkedIn * Lynn Kaack: LinkedIn / Latest Paper

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

Episode resources:
* ClimateAction.tech [3:44] * Green Web Foundation [3:49] * Green Software Foundation’s Standards and Innovation Working Group [4:14] * Montreal AI Ethics Institute [4:43] * Hertie School Berlin [5:50] * Aligning Artificial Intelligence with Climate Change Mitigation [6:32] * The IPCC [7:11] * Paper: Green AI | Roy Schwartz, Emma Strubell, Jesse Dodge [8:37] * Project: Pachama [9:33] * Montreal Institute for Learning Algorithms [10:34] * Project: This Climate Does Not Exist [10:48] * Austrian Institute of Technology | Infrared [11:32] * Jevons Paradox [20:19] * The GHG Protocol [23:27] * Legislation: The EU AI Act [25:08] * Paper; Measuring the Carbon Intensity of AI in Cloud Instances | Will Buchanan et al. [30:08] * ONNX Runtime [37:02] * TinyML [37:09] * GitHub: Dynamic Batch Inferencing - Taylor Prewitt & Ji Hoon Kang of UW * GitHub: NVIDIA Triton server on AzureML & Model Analyzer * Green Software Foundation Summit

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

**TRANSCRIPT BELOW:

Chris Skipper:** This week on Environment Variables, we have some sad news.

We have to report the untimely passing of Abhishek Gupta. Abhishek was a key part of the Green Software Foundation. He was the co chair of the Standards Working Group from the GSF's formation to his passing on September 30th of this year. I would like to read out an in memoriam that was posted by Asim Hussain, honoring the great man, his legacy of leadership, his collaboration, and the heart that he put into the Green Software Foundation.

When the Green Software Foundation was formed over three years ago, Abhishek offered to help. The standards working group was looking for a co chair, and he jumped in to help without hesitation. He led the standards working group for over three years, with the full support of everyone involved. Leading a work group isn't about imposing your will on others, It's about finding common ground, nurturing discussions, and searching for the truth.

Abhishek excelled in all of those areas. He leaves a powerful legacy with the Software Carbon Intensity SCI specification. His tireless efforts over the years led to a consensus on the specification, which was later published to ISO in late 2023, and is now being adopted globally.

The impact of the SCI is truly global, with academics and enterprises worldwide adopting it. This widespread adoption is a testament to Abhishek's vision and dedication and his influence will be felt in every software product that bears an SCI score. His legacy is not just a memory, but a living testament to his work.

He has left an unforgettable mark on the community. And will be remembered for his contributions for years to come. Aho brother, I'll see you on the other side, Asim Hussain. To honor Abhishek, we're going to revisit an older episode of Environment Variables from the very start of the podcast, episode five, How Does AI and ML Impact Climate Change?

In this episode, host Chris Adams is joined by Abhishek Gupta, Lynne Kaack, and Will Buchanan to discuss these topics. So, without further ado, here's the episode.

Abhishek Gupta: We're not just doing all of this accounting to produce reports and to, you know, spill ink, but it's to concretely drive change in behavior. And this was coming from folks who are a part of the standards working group, including Will and myself, who are practitioners who are itching to get something that helps us change our behavior, change our team's behaviors when it comes to building greener software.

Asim Hussain: Hello and welcome to Environment Variables brought to you by the Green Software Foundation. In each episode we discuss the latest news and events surrounding green software. On our show you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host Asim Hussain.

Chris Adams: Hello there and welcome to the Environment Variables podcast, the podcast about green software. I'm Chris Adams filling in for Asim Hussain, the regular host while he's on paternity leave with a brand new baby. I met Asim on climateaction.tech, an online community for climate aware techies. And I work for the Green Web Foundation where we work towards a fossil free internet by 2030, as well as working as the co chair for the Green Software Foundation's policy group. Today, we're talking about climate change, AI, and green software. And I'm joined by Lynn, Will, and Abhishek.

Will Buchanan: Thanks for having me. My name is Will. I'm a product manager on the Azure Machine Learning team. also a member of the Green Software Foundation's Standards and Innovation Working Group. Within Microsoft, I foster the Green AI community, which now has a few hundred members, and I'm also a climate activist that's focused on pragmatic solutions to complex environmental issues.

Recently, I shipped energy consumption metrics within Azure Machine Learning, and we are about to publish a paper titled Measuring Carbon Intensity of AI in Cloud Instances, which I think we'll touch on today.

Abhishek Gupta: Well, thanks for having me. I'm Abhishek Gupta. I'm the founder and principal researcher at the Montreal AI Ethics Institute. I also work as a senior responsible AI leader and expert at the Boston Consulting Group, BCG, and I serve as the chair for the Standards Working Group at the Green Software Foundation.

So I've got a few hats on there. Most of my work, as it relates to what we're going to talk about today, It runs at the intersection of responsible AI and green software. In particular, what's of interest to me is looking at how the intersections of social responsibility, the environmental impacts of software systems, in particular AI systems, can be thought about when we're looking to make a positive impact on the world while using technology in a responsible fashion. I also, as a part of the Green Software Foundation, help through the standards working group, come up with the software carbon intensity specification, where we're trying to create an actionable way for developers and consumers of software systems to better assess and mitigate the environmental impacts of their work.

Chris Adams: Okay. And Lynn, last but not least, joining us from Berlin. Thank you very much for joining us.

Lynn Kaack: Yeah thank you so much. I am an assistant professor at a policy school, public policy school, called Hertie School in Berlin. And I am also a co founder and a chair of an organization called Climate Change AI. with Climate Change AI, we facilitate work at the intersection of machine learning and And different kinds of climate domains, focusing on climate change mitigation and adaptation. And in my work, in my research, I am looking at how we can use machine learning as a tool to address different problems related to energy and climate policy. I'm also interested in the policy of AI and climate change. And today, actually, since we're talking about papers, I have a paper coming up. That is called Aligning Artificial Intelligence with Climate Change Mitigation, where we look at the different impacts from machine learning and how they affect greenhouse gas emissions.

Chris Adams: So we actually have some decent deep domain expertise and I'll try to keep this quite accessible, but we might drop into a little bits of like data science nerder on here, but the podcast has done that previously and it turns out to be something that we've got some decent feedback from because there aren't that many podcasts covering this. Okay so let's, uh, get into this topic of green AI and climate change. As we we know, IT is a significant driver of emissions in its own right. When we think about the climate crisis this year, the IPCC, which is the Intergovernmental Panel on climate Change in their big reports, which synthesized literally thousands of papers explicitly called out digital as a thing we, we should be talking about and thinking about.

And if you're a responsible technologist, it seems like a thing that we should be taking into account here. Now, I found it helpful to think about IT IT a little bit like how we think about the shipping industry, partly because they're similar in terms of emissions, which is around between 1 and 3%, depending on what you look at it, but also in that both of these acts like kind of connective tissue for society.

We also think of IT as a kind of force multiplier for The existing forms of activity. So if you use it, which is in line with the recommendations of the science, that's a good thing. But if you use it to do something, which is kind of rejecting some of the science, it might not be such a good thing. And within technology, AI and machine learning in particular is one of the fastest growing sectors and often seen as one of the biggest levers of all. So we're going to highlight some interesting projects we'll start off with. And out of that, we'll probably dive into some specifics about that or some other things you might want to take into account. If you're a technologist wanting to incorporate an awareness of climate into how you work and build greener software, then finally, we'll hopefully leave you with some actionable tips and techniques or projects that you may contribute to or use in your daily practice.

There's another term that we might be touching on here when you're making AI greener, and that's specifically Green AI. Is that the case, Will?

Will Buchanan: Correct. And that actually was coined by researchers a few years ago, Roy Schwartz, Emma Struble, Jesse Dodge. And it's really focused on making the development of the AI system itself more sustainable. And it's to be disambiguated from the term using AI for sustainability.

Chris Adams: Okay, so that's something we'll touch on both today. We'll talk about some of the external impacts and some of the internal impacts. We're going to start with something quite easy first because, well, why not? I'm just going to ask each of the people here to kind of point to maybe one project that they've seen that's using ML in quite an interesting fashion to ideally come up with some kind of measurable win. Well, if there was one project you'd actually look to that you think is kind of embodying these ideas of like green AI something which is really helping us essentially face some of the challenges, maybe you could tell us about what's catching your eye at the moment or what you'd look at.

Will Buchanan: I've been thinking a lot about natural capital recently, and I learned about a startup called Pachama, which combines remote sensing data with machine learning to help measure and monitor the carbon stored in a forest. I think it's really, really valuable because they're providing verification and insurance of carbon credits at scale. They've protected about a million hectares of forest. That's really when you have IoT and remote sensing and machine learning combining to help nature restore itself.

Chris Adams: Okay, cool. So if I understand that, they're using satellites to basically track forests and track deforestation. Is that the idea that they're doing there?

Will Buchanan: Yes, Yes, and and also to verify the amount of carbon that a forest can sequester.

Chris Adams: Okay, cool. All right. I know there's a few other projects related to this. If I just hand over to Abhishek, can you let us know what's caught your eyes recently, and then we'll see what other projects come out of this.

Abhishek Gupta: Yeah, absolutely. I think one of the projects, and I don't know, I mean, what the measurable impact has been so far. In fact, it's, it's something that's come out of MILA, which is, or, you know, called the Montreal Institute for Learning Algorithms, which is Dr. Bengio's lab in, in Montreal. In fact, one of the people who led that project is a part of Climate Change AI as well, who I'm sure Lynn can talk more about too, which is SASA. And she's done this project called This Climate Does Not Exist, which I think was a fascinating use of machine learning to visualize the impact climate change will have on, you know, places around you in a very arresting and visually capturing fashion, which I think when we think about.

What impact climate change is going to have around us. Sometimes it, it feels quite distant because it's a, it's a slow rolling thing that's coming our way. And this puts it in, in, in a way that's quite immediate, quite visually arresting. And I think stirs people to action. I, as I said, I'm not sure what the measurable impact of that has been yet, but I, I certainly feel that those are the kinds of creative users of AI when we want to galvanize people into action around climate change.

Lynn Kaack: I'm happy to also talk about a application, which is also kind of difficult in terms of measuring impact, but I think it's an another interesting component of what AI can do. And this is something that researchers at the Austrian Institute of Technology do on a project called Infrared. And they use machine learning to help design new districts and cities.

And especially at the moment in many countries, a lot of new urban districts are being built and how we build these has a huge impact on energy consumption in cities, both in terms of transportation, but also how buildings are heated or cooled. And by the use of machine learning, they can drastically improve design choices because now they can approximate their very computationally heavy models and run them much faster. which means that they can also have more runs and can try out more design configurations. So this is a rather indirect application, but it has huge implications also on emissions for, for many decades to come.

Chris Adams: So essentially it's using of housing policy as climate policy there, because there's just a huge amount of emissions built into how people live and whether they need to drive everywhere in a car and stuff like that. That's some of the stuff that it's doing and making that part easier?

Lynn Kaack: So it's not really looking at housing policy, but it's looking at how districts are designed. So they take a group of, of houses, like if the new district is to be built and then they simulate the wind flow going through the cities, which are very expensive simulation models. they take the outputs of their model and approximate it with a machine learning model, which makes it much, much faster.

So from hours or days, you go to milliseconds or below seconds for one run. And then you can try out different design configurations and understand better how The built infrastructure affects natural cooling, for example, in cities or walkability, energy impacts generally of the microclimate on, on the built environment.

Chris Adams: Wow, I had no idea that was, it was actually possible. That's really, really cool.

Will Buchanan: That's very cool. That's similar to generative design.

Chris Adams: design. This is a phrase I haven't heard actually, Will. Maybe you could elucidate or share something there, actually.

Will Buchanan: It's similar similar to to some software that Autodesk has built where you can try out many different iterations of a design and come up with optimum solutions. I think it's really cool that you're just consolidating it and running these models more efficiently.

Chris Adams: cool. And that's a bit like following, say, a fitness function saying, I have a chair, or, you know, I want to have something that works like a chair. It needs four legs and a seating pattern. Then it essentially comes up with some of the designs or iterates through some of the possibilities, something like that?

Will Buchanan: Exactly.

Chris Adams: Oh, wow. Okay. That's cool. All right. And so we've spoken about AI, and there's a few exciting, interesting ones that we can add to the show notes and list from, and for people to look into and see how that might relate to what they do, I suppose. I want to ask a little bit about measuring impact from these projects, because quite a few different ways that you can actually measure impact here.

And in many times, it can be quite a difficult thing to kind of pin down. And this is continually a thing that's come up. When I know that. So, people have tried to come up with specs like the Software Carbon Intensity, and I'm sure Abhishek, you've had some experiences here. Will, you've mentioned a little bit about, um, Actually measuring impact internally, and it sounds like you've just had to do a bunch of this work on the ML team right now and expose some of these numbers to people consuming these services in the first place. Could you talk about some of that part a bit, perhaps?

Will Buchanan: Certainly. And so, as I mentioned, we have shipped energy consumption metrics for both training and inference within Azure machine learning. And that's really complex when you think of the infrastructure required to just report that,but that doesn't necessarily account for the additional power that's consumed in the data center, such as the idle power for devices or for the utilization of your servers.

There's so many different factors there. So you really, you could encounter scope creep when you come to your measurement methodology. So it's really necessary to put boundaries around that.

Chris Adams: and when you use the term boundaries here, you're saying, I'm going to measure the environmental impact of the servers, but not the environmental impact of building the building to put the servers in. Is that the idea of when you're referring to a boundary here? Yeah.

Will Buchanan: Yes, that's a great example.

Chris Adams: Okay. All right. I think this is actually something we've come across quite a few times in other places as well, actually, because maybe it's worth asking about this kind of boundary issue that we have had here, because automatically that sounds complicated here.

And I know that Abhishek, you've had some issues at your end as well with defining this style for deciding what's in or out, because I think this is one thing that we've had to explicitly do for the software carbon intensity spec, right?

Abhishek Gupta: Exactly. And, and I think when we talk about boundaries, it's, it's, it's trying to get a sense for what are the actual pieces that are consumed, right? From an operational standpoint, from an embodied emission standpoint, and how you make those, you know, allocations across you know, what, what your system is consuming.

And I use the word system because I think again, when we talk about software, we're not just talking about a specific piece, but we're talking about really everything that it touches, be that, you know, network, be that bandwidth consumption, be that, you know, as, as Will was saying, idle power. Even when we're looking at cloud computing, it becomes even more complicated when you have your pieces of software that are sharing tenancy across the pieces of hardware and how different consumers are perhaps sharing that piece of hardware with you and thinking about whether you've booked the resource ahead of time or not, whether it's hot or cold in terms of its availability and what implications that has.

I mean, there are so many different facets to it. And each of those decisions, what I want to highlight here is that it comes with a trade off, right? So we also don't have any standards in terms of how we should go about measuring that and what should be included, what shouldn't be included. And so the way people report out these numbers today also doesn't really make it actionable for folks who are consuming or who want to consume these reports, these metrics in taking decisions as to, you know, whether something is green or not.

And I think that's one of the places that The Software Carbon Intensity Specification is trying to help folks is to help standardize it first and foremost, but also to make it actionable so that if you're someone who's environmentally conscious, you can make the right choice by being informed about what the actual impacts are.

Chris Adams: Okay, this is question that I'm curious here, because so far we've only been speaking internally about, okay, what is the environmental impact of IT itself, like it's direct emissions. But the assumption that I have here is that there are ways we might talk about the impact that it has on the outside world in terms of activity we're speeding up or accelerating or supporting there.

Is that the only issue that we need to think about, or are there any other things to take into account about like this system boundary part that we've just been talking

Lynn Kaack: Yeah. So the system effects are really important to look at and to consider. Maybe just to give an example, like if you use machine learning in, let's say the oil and gas sector to make a small part of the operation is more energy efficient, that first sight looks like something that could be considered sustainable and green, but you also have to realize that often then you are reducing costs as well, and that might change the way that oil and gas in this particular example is competitive, or the particular company is competitive, and that actually might shift also how much oil and gas we are able to use in the short run, how the price is changed.

So, these indirect effects can actually then have much larger impacts than the immediate effects of such an application. So drawing boundaries is really important and also opening this up to to have a broader system level view and really try to understand how does the technology also change then, then to larger consumption and production patterns. It's important.

Chris Adams: So if I understand that correctly, that's talking almost like the consequences of an intervention that we might make here. So even though we've might have reduced the emissions of say the drilling part by putting a wind turbine on an oil rig, for example, that might change the economics and make people more likely to use the oil, in which many cases they might burn, for example, or stuff like that.

Is that basically what you're saying there?

Lynn Kaack: Essentially what I'm saying is that efficiency improvements in particular, and often they can be done with data science or with machine learning or AI systems. They often come with cost reductions and then those cost reductions do something and change something. And often this is also considered under rebound effects, but it's not only rebound effects.

So there's systemic, the system level impacts that come from more small scale applications that need to be considered.

Will Buchanan: That's such a good good point, and I think I've also heard it called Jevon's paradox, too.

Chris Adams: Yes. Jevons paradox. This is stuff from like the 1800s with steam engines, right? Like my understanding of the Jevons paradox was when people had steam engines and they made steam engines more efficient, this led to people basically burning more coal because it suddenly became more accessible to more people and you end up using them in a greater number of factories.

So there's a kind of rebound, I think, that we need to take into account. This is something I think has been quite difficult to actually capture with existing ways of tracking the environment impact of particular projects. We have like an idea of, say, an attribution based approach and a consequence based approach. And maybe it's worth actually talking about here, about how Some of the complexities we might need to wrestle with when you're designing a system here. I mean, Abhishek, I think this was one of the things that was an early decision with the software carbon intensity part to not try to have an attribution approach versus a marginal approach. And if we're not diving too deeply into jargon here, maybe you might be able to kind of share a bit more information on that part there, because It sounds like it's worth expanding or explaining to people, to the audience, a bit better here.

Abhishek Gupta: Indeed, you know, the reason for making that choice was again, our emphasis on being action oriented, right? So as we had started to develop the software carbon intensity specification, one of the early debates that we had to wrestle with and, and, you know, Will and Will was of course a crucial part of that as well as whether folks who were a part of the standards working group was figuring out how.

For example, the GHG way of going about doing that, you know, accounting doesn't really translate all that well for software systems and how perhaps adopting a slightly different approach would lead to more better. More actionable outcomes for the folks who want to use this ultimately to change behavior because, you know, without getting into specifics of, you know, what marginal is and what consequential approaches are, and, and if we want, I mean, I'm, I'm sure you know, will, would, would be happy to dive into all of those details as would I.

But the, the, the thing that we were seeing was that we're doing all of this great work around, you know, talking about scope one, two, three emissions, et cetera, but it's not really helping to drive behavior change. And that's really the crux of all of this, right, is that we're not just doing all of this accounting to produce reports and to, you know, spill ink, but it's to concretely drive change in behavior.

And that's where we found that adopting a consequential, adopting a marginal approach actually helped make it more actionable. And this was coming from folks who are a part of the standards working group, including Will and myself, who are practitioners, who, who are itching to get something that helps, helps us change our behavior, change our team's behaviors when it comes to building greener software, broadly speaking.

Chris Adams: Okay. So that helps with explaining the difference between a consequential approach and a marginal approach, as in the consequences of me building this thing will mean that this is more likely to happen. And if I understand it, the GHG protocol that you mentioned, which is the greenhouse gas protocol, and this scoped emissions approach, this is the kind of standard way that an organization might report It's kind of climate responsibility, as it were, when, and when you say scoped emissions, that's like scope one, which is burning burning say that's, that's emissions from fossil fuels burned on site or in your car.

For example, scope two is electricity and scope three is your supply chain. If I understand what you're saying, there's like a kind of gap there that doesn't account for the impacts of this, perhaps. I mean, some people who've referred to this as scope zero or scope four, which might be, what are the impacts an organization is happening to. Essentially, we mentioned before, do something around this systemic change, or as Lynn mentioned, like this is changing the price of a particular commodity to make it more likely to be used or less likely to be used. And this is what I understand the SCI is actually trying to do. It's trying to address some of this consequential approach, because the current approach doesn't capture all of the impacts an organization might actually have at the moment. Right?

Will Buchanan: Yeah, that's a good summary. One challenge that I have noticed is that until it's required in reporting structures like the greenhouse gas protocol, then organizations don't have an incentive to really take the action that they need to avoid climate disaster. Something I encounter on a daily basis, and I think broadly we need to bring this into the public discourse.

Chris Adams: I think you're right. I think it's worth actually, Lynn, I think that when I've seen some of the work that you've done, you've done previously, this is something that's come into some of the briefings that I think that you've shared previously with the climate change AI work and some of the policy briefings for governments as well. Is there something that you might be able to add on here?

Lynn Kaack: Yeah, so something that comes to mind is, for example, like a concrete legislation that's currently being developed is the EU AI Act. And that's a place where, for the first time, AI systems are being regulated also that scale. And climate change almost didn't play a role for that regulation in the first draft.

So here it's also really evident that if we don't write in climate change now as a criterion for evaluating AI systems. It will probably be ignored for the next years to come. So the way that legislation works is by classifying certain AI systems as high risk and also just outright banning some other systems, but as high risk systems could, the original legislation stood, weren't really explicitly classified as high risk, even if they had like a huge environmental or climate change impact. And that's that I talked about a lot with policymakers and trying to encourage them to more explicitly make environmental factors and climate change a factor for evaluating systems. So that'd be a very concrete case where making climate change more explicit in the AI context is important also in terms of legislation.

Abhishek Gupta: So there's, there's a lot to be said about the EU AI Act, right? And a ton of ink has been spilled everywhere, I think, as, as, you know, it's, it's, it's, it's called the Brussels effect for a reason, right? Where the, whatever happens in the EU is taken as gospel and sort of spread across the world, which I think, as already Lynn has pointed out there, It's not, it's not perfect, right?

I think one of the things that I've seen being particularly problematic is, is the rigid categorization of what, you know, high risk use cases are and, and whether the EU AI act, as we'll see, hopefully with some, with some you know, revisions that are coming down the pipe is whether we'll have the ability to add new categories and, and not just update subcategories within the existing identified high risk categories.

And I think that's where things like considerations for environmental impacts and really tying that to this you know, societal impacts of AI, where we're talking about bias, privacy, and all the other areas, is going to be particularly important because we need multiple levers to, to try to account for, or to push on getting people to consider the environmental impacts.

And given that there is such a great momentum already in terms of privacy considerations, bias considerations. I think now is the time where we really push hard to make environmental considerations an equally first class citizen when it comes to, you know, thinking about the societal impacts of AI.

Will Buchanan: This is something I'm incredibly passionate about. I think needs to encompass the full scope of harms that are caused by an AI system. So that could be the hidden environmental impacts of either the development or the application. The application could vastly outweigh the good that you're doing, even just expanding oil and gas production by a certain percentage amount. I think it just must account for all of the harms for both ecosystems and people.

Chris Adams: And there's this idea of like a risk thing. Does this categorization actually include this stuff right now? What counts as a high risk use case, for example, when mentioned here?

Lynn Kaack: So I haven't seen the latest iteration. I think that there has been some update on, there's been a lot of feedback on the version that was published in April last year. I haven't seen the latest iteration. I think a lot of things changed in, yeah, in the first version, there was It's high risk systems where when, that affect personal safety, like human rights in the sense of, of personal wellbeing, but the completely overlooked environmental protection aspects aspects of human rights.

Chris Adams: Wow, that's quite a large one, especially when you take into account the human rights. Okay. We've spoken about the external impact, but I am led to believe there is also an internal impact from this as well. Like the AI has, has some direct impact that we might want to talk about as well. As I understand it, we spoke about 2 to 3 percent of emissions here, but if we know there's an external impact, why would we care about any of the internal impacts of AI we might be doing or why you might want to care about the internal impacts of AI as well, for example, like the direct emissions.

Will Buchanan: So by direct emissions, you're talking about, let's say, the scope, too, of the operational cost of the model.

Chris Adams: Yeah, there'll be things that we have, there's an external impact or there is a, we use this phrase scope 4, for example, to talk about all the other things that induce in the world. But there is a, a kind of stuff which happens inside the system boundary that we've spoken about. And presumably that's something we should be caring about as well, right? So there'll be steps that we can take to make the, the use of AI, particularly like say the, the models more efficient and more effective and more, all these parts here, this is something that we should be looking at as well, presumably right?

Will Buchanan: Totally. And so in our paper, which is going to be published, I think on Monday, we've calculated the emissions of several different models. And one of them was a 6 billion parameter transformer model. And the operational carbon footprint was equivalent to about a rail car of coal. And that's just for training. So it's really imperative that we address this and provide transparency this

Lynn Kaack: Is that Is that for developing a model or for training at once? I mean, is that with grid search, architecture search?

Will Buchanan: For for a single training run. So it does not account for sweeps or deployments.

Chris Adams: All right, so there's a, there's some language that we haven't heard for here, so, but maybe it might be worth asking, maybe Will, could you maybe talk about, just briefly, you said a rail car full of coal, and I don't actually know what that is, I mean, in metric terms, what does that look like?

Will Buchanan: A hundred million grams. I don't have the conversion handy, but we took the U.S EPA greenhouse gas equivalencies. And I should add the methodology that we applied was the Green Software Foundation's SCI. So we calculated the energy consumed by the model and multiplied it by the carbon intensity of the grid that powers that data center.

Chris Adams: Okay, cool, and that was per training run? So that wasn't the, in the, the equation of the entire model, is that correct?

Will Buchanan: Correct.

Abhishek Gupta: That's the other interesting part as well, right? When you're thinking about the life cycle is, or life cycle of the model, I should say, because life cycle has multiple meanings here, which is that once that model is out there, what are the inference costs, right? And are we, if this is something that's going to be used you know, hundreds, thousands, tens of thousands of times, if it's something, you know, if it's, if it's a large model that's, you know, now being used as a pre trained model and is going to be fine tuned on by, by other folks downstream, are we able to then, you know, talk about amortization of that cost across all of those use cases?

And again, I think what becomes interesting and, and is how do we account for that stuff as well, right? Because we, we don't have complete visibility on that as well. And, and I know Lynn's nodding here because her paper that's, I think coming out, being released in an hour and a half, actually the embargo gets lifted on our paper, actually talks about some of those system level impacts.

So maybe, maybe Lynn, you want to chime in and talk a little bit about that as well?

Lynn Kaack: Yeah, thank you so much. Exactly. So I think what's a crucial number that we're currently still missing is not what is emitted from a single model in a well known setting, but what is emitted overall from applying machine learning? So what are the usage patterns and practice? Like how often do people develop models from scratch?

How often do they train or retrain them? People I mean, of course, organizations and typically large organizations and companies. And how do they perform inference on how much data, how frequently? And there are some numbers out there from Facebook and Google and in their large scale applications actually inference outweighs their training and development costs in terms of greenhouse gas emissions.

So inference might become a bigger share depending on the application. So we really need to understand better how machine learning is being used in practice also to understand the direct emissions that come from it.

Chris Adams: An inference is a use of a model once it's in the wild. Is that what an inference is in this case? So there's an environment, so you could think of the making part, and then there is the usage part from the inference, right? So is that how that part works?

Lynn Kaack: Exactly. So if you use a model on a data point, we call that inference. So you feed in the data and it gives you a result. Then training means you sort of train a single configuration of the model once on your training data set, and then development is what I refer to as if you search over different configurations of the model.

So there are lots of hyperparameters that you can adjust to achieve better performance. And if new models are being developed, then there's an extensive search over those hyperparameters and architecture configurations that then of course gets really energy intensive because we are training the model thousands of times essentially.

Will Buchanan: Yeah, one of the figures that really resonated with me, I think Nvidia posted on their blog that inferencing for about 80 to 90 percent of the carbon cost of a model. think Lynn on one of your papers, it was, Amazon had also claimed around 90 percent. So these are really non trivial costs, and I'm not aware of any framework to measure this.

Lynn Kaack: Yeah. So that Amazon number just to be clear is costs or monetary costs that came from a talk, but there are numbers now published by Google and Facebook, but they look at some applications of theirs where inference outweighs training in terms of energy consumption. They're not exact numbers. It's not entirely clear which applications those are, but there is some data at least that shows that.

And I think it just highly depends on the application that you're looking at. And sometimes, you know, you build a model and then you do inference once and you have the data set that you, and then in other types, you build a model and then you apply it billion times a day. So, of course, that can then add up to a lot more energy consumption.

Chris Adams: Wow, I didn't realize that was actually an issue, because most of the numbers I've seen have been focusing on the training part. So, Will, I think this is something we spoke about before, that training, there's a kind of trend in the use, in the energy use from training already. Is this something, because I've seen figures from OpenAI, but my assumption was that basically computers are generally getting more efficient. About twice as efficient every two years, or so with like Moore's Law or Kumi's Law or things like that. But if you're seeing an uptick in usage here, is, does that mean that they're staying about the same? Or is there, is there a trend that we should be taking into account there?

Will Buchanan: So I think the computational costs of training have been doubling every 3.4 months or so, and so I think the trend is only accelerating. The models are just getting larger and larger, and you've got, I think, GPT 3 is one of the largest ones around at this point. We might challenge Moore's Law.

Chris Adams: Okay. So if Moore's Law is doubling every once every two years, I mean, what is the impact of doubling every 3.4 months? I mean, over a few years, what does that work out to be? Because I don't think I could do the exponential numbers, the exponential math, but it sounds like it's, it sounds like a pretty big number, basically, if something is doubling on every three or four months, right?

Will Buchanan: I also don't have the math handy, but I think it's important to note here, and Abhishek was talking about this earlier, models are very flexible, so you can train them once and then provide some fine tuning or transfer learning approach on top of them, and then repurpose these models for a number of different applications. And then you can even compress them, let's say using ONNX Runtime. You can be very efficient. You can really amortize the cost of that model.

Abhishek Gupta: So yeah, just building on Will's point, there's a lot of work on quantizing the weights of a trained network, applying distillation approaches, using teacher student model approaches that actually helps to shrink down the model quite a bit, especially with the whole push for TinyML, trying to shrink down models so that they can be deployed on edge devices has been something that's helped to manage to a great extent, the computational impacts.

One of the other things that I wanted to highlight as, as, you know, Will was talking about more models getting larger is, there's this almost fetish in the world today to continuously scale and keep pushing for ever larger models and in chasing SOTA, as they would say, so chasing state of the art, you know, which is great for academic publications where you get to show, "Hey, I improved state of the art performance on this benchmark data set by 0.5 percent or whatever," right? And in performance, I think what's being ignored is that that has a tremendous, tremendous computational cost. In fact, one of the hidden costs that I think doesn't get talked about enough is there's this statistic out there that, you know, 90 percent of the models don't make it into production.

And that kind of relates to things like, you know, neural architecture search and, you know, hyper parameter tuning, where you're constantly trying to refine a model to achieve better performance. A lot of that actually goes to waste because that stuff doesn't make it into production. So it's actually not even used.

And so there's a whole bunch of computational expenditure that is done that actually never sees the light of day, never becomes useful. That obviously has environmental impacts, right? Because of the operational and embodied carbon impacts, but none of that actually gets talked about, reported, documented anywhere because, well, who wants to know that, hey, I trained, you know, 73 different, you know, combinations to get to where I'm at.

You just talk about the final results.

Chris Adams: Okay, let's say that if you don't want to go down one of those rabbit holes, what should you be using or where would you start if you wanted to start applying some of these ideas about greener AI in your work on a daily basis? Does anyone have anything that they would lead with, for example?

Will Buchanan: Bigger is not always better. Sometimes you really should choose the right tool for the job. We've had some really great graduate student projects from the University of Washington's Information School, and they built some case studies and samples around green AI. As an example, a project led by Daniel Chin was comparing a sparse or a dense model of a green AI model to a dense model for an anomaly detection setting.

And they found that using sparse, meaning less trees and a shallow, smaller depth per tree, random forest would save a massive amount of carbon and provide the equivalent accuracy. So I think it saved about 98 percent in terms of the monetary cost and energy.

Chris Adams: Okay, wow, that's bigger than I was expecting. What would you say to people if they're in production, they're trying to do something now?

Lynn Kaack: I think a big goal should be to not only develop more energy efficient machine learning models, but then also ensure that those are actually being used. And surprisingly, even sometimes within the same company, certain model developments are not being passed on to other parts of the company. So really trying to develop standard models that then are also being used in practice is important.

So interoperability of energy efficient machine learning models.

Chris Adams: If people, someone does want to look at this stuff, and they do want to apply some of these ideas, you spoke a little bit about using some other models. would you suggest people look if they wanted to operationalize some of the kind of wins or some of the better ways to make green software greener, for example?

I realize you've got a paper coming out and you work on this day to day. So yeah, what would you point us to?

Lynn Kaack: So, I mean, as I understand, there's a lot of ongoing research in the machine learning community for more energy efficient machine learning. So I don't have any names on top of my head in terms of workshops or community resources where one can see what are the most energy efficient model types. For a specific application.

I know that there are some very comprehensive papers also that summarize all the different research approaches that are being taken, but I would encourage if you are looking for using like a deep learning model of some kind, just inform yourself quickly if there's also a leaner version of it. So much of the like widely used models like BERT, for example, smaller versions that can almost do the same thing.

And maybe your performance doesn't suffer much. If you're using a much lighter model.

Chris Adams: Okay, so light up models and looking around what we have there. And Will, is there a paper or a source you might point to?

Will Buchanan: I was actually going to talk about the Carbon Aware paper that we're about to publish. I think that's a slightly different track.

Chris Adams: That's up next week, right? So that'll be the 13th or 14th of June. That's when that'll be visible, correct?

Will Buchanan: Exactly.

Chris Adams: Okay, cool. All right, then. There's a load more that we could dive into. We've got copious, copious, copious show notes here. So what I'm gonna do is I'm gonna say thank you everyone for coming in and sharing your wisdom and your experiences with us, and hopefully we'll have more conversations about green software in future. Thank you folks.

Asim Hussain: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please do leave a rating and review if you like what we're doing. It helps other people discover the show and of course we want more listeners.

find out more about the Green Software Foundation, please visit greensoftware. foundation. Thanks again and see you in the next episode.

View Details

In this episode of Environment Variables, host Chris Skipper introduces "Backstage," a new segment offering behind-the-scenes insights into the Green Software Foundation's key projects. The episode highlights the "Transforming Organizations for Sustainable Software" (TOSS) project, led by Pindy Bhullar, which aims to embed sustainable practices across all aspects of business operations. The TOSS framework, divided into four pillars—strategy, implementation, operations, and compliance—provides organizations with a decision tree approach to drive sustainability in software development and IT. With collaborative efforts, workshops, and real-time feedback, the project is set to release version 1.0, with the ultimate goal of reducing carbon emissions across the industry. Learn more about our people:* Chris Skipper: LinkedIn | Website * Pindy Bhullar: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

Resources:* GitHub - Green-Software-Foundation/toss: Transforming Organisational Software Sustainability (TOSS) [01:28] * Transforming Organizational Software Sustainability | GSF * Software Carbon Intensity (SCI) Specification Project | GSF [03:47] * GitHub - Green-Software-Foundation/sci: A specification that describes how to calculate a carbon intensity for software applications. * Impact Framework [03:54] * GitHub - Green-Software-Foundation/if: Impact Framework

Events:* Sustainable AI: Myth vs Reality (October 15 at 6 pm CEST · Amsterdam) [12:49] * CNCF Sustainability Week - Cloud Native for Green Software (October 15 at 6:30 pm CEST · Hybrid · Karlsruhe) [13:02] * Code Green London October Meetup (October 15 at 7:00 pm · London) [13:25]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Chris Skipper: Welcome to Environment Variables, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Skipper. Today, we're launching an exciting new segment:

Backstage. Here, we'll take you behind the scenes at the Green Software Foundation to highlight ongoing projects and share insights from the members directly involved.

In the first episode of Backstage, you'll hear about innovative projects shaping the future of green software and the hard work behind it all. It's easy to overlook the complexity and dedication required to drive sustainability in the tech industry. But today, you'll hear more about the passion, thoughtfulness, and expertise that fuels these initiatives.

From collaborative projects to cutting edge research on sustainable computing, the Green Software Foundation is the conversation you need to be part of, and we're bringing you Deep Inside. Join us as we look into the stories, challenges, and triumphs of the people making a real impact on our environment through software.

We're no longer gatekeeping what it takes to set new standards and norms to green software. So, what does it take to inject sustainability into every aspect of software development? How are organizations and passionate climate activists in software turning ambitious goals into practical, actionable results?

Let's find out on this special Backstage episode. For this initial episode, we'll be looking at the Transforming Organizations for Sustainable Software project, better known as the TOSS project. Leading this project is the inimitable Pindy Bhullar, who provided us with some soundbites. This initiative is really important in the Green Software Foundation's broader mission to reduce carbon emissions through software.

It's all about providing changemakers in organizations with the tools, methodologies, and frameworks they need to embed green software practices and drive real, measurable change. Firstly, we asked Pindy to give us an overview of the TOSS project. It's goals and why it's so crucial for the foundation.

Pindy Bhullar: Transforming Organizations for Sustainable Software is the acronym for TOSS. Businesses will be able to utilize the TOSS framework as a guide to lay the groundwork for managing change and also improving software operations in the future. Software practices within organizations can be integrated with sustainability in a cohesive and agile manner, rather than addressing green software practices in an isolated approach.

For a company to fully benefit from sustainable transformation of their software development processes, we need to review all aspects of technology. The TOSS framework is designed to be embedded across multiple aspects of its business operations. Dividing the task framework along four pillars has allowed for simultaneous top down and bottom up reinforcement of sustainable practices, as well as the integration of new tools, processes, and regulations that emerge over time.

The four pillars include aim to foster a dynamic foundation for companies to understand where to act now, to adjust later, and expand with an organizational sustainable software transformation. The four pillars are strategy, implementation, operational, compliance, and regulations. And within each of the pillars, we have designed a decision tree that will be constructed to guide organizations in transforming their software journey.

The Green Software Foundation has created the specification to calculate carbon emissions from software, the SCI, and also developed the Impact Framework to enable firms to calculate their emissions. But in order for firms to transform their technology operations, we need to embed best practices across the wider organization.

Chris Skipper: It's clear that by integrating sustainability across multiple levels of business operations, the TOSS project is setting up organizations for long term success in their green transformation journey. Now, let's talk about the impact this project can have. Reducing the carbon footprint in software development is a huge focus for many companies today.

So, how exactly does the TOSS project help achieve that, and what kind of sustainability improvements can organizations expect by adopting this framework?

Pindy Bhullar: The TOSS project views sustainability in software development and IT operations as a holistic approach, and the primary goal is not to view software and IT as an isolated function, but integrate the carbon footprint into the functions across the organization.

The framework will help organizations to ask the questions and adapt their responses based on their needs, but also connect strategy, implementation, operations, and compliance and regulations.

Chris Skipper: It's insightful to see how the TOSS framework fosters a more integrated approach, making sustainability a core part of a company's strategy, operations, and compliance.

Now, as with any large scale initiative, developing a framework like TOSS must come with its challenges. We asked Pindy to share some of the key obstacles the team has encountered while bringing this project to life, and how have they navigated these challenges to keep the project moving forward.

Pindy Bhullar: We're all busy in our day jobs, so just being able to focus on the TOSS framework has been a challenge.

We've been having regular calls since the project inception January this year, which has enabled us to keep the discussions moving. We have overcome obstacles by building a version 0.5 of the framework and then asking volunteers from the GSF member organizations to join a series of workshops to review, question, challenge, and brainstorm. It enabled us to develop the framework further by incorporating all the great feedback.

Chris Skipper: It's great to hear how the team has managed to build the toss framework through collaborative efforts and feedback from GSF member organizations. It sounds like the workshops have played a crucial role in refining the framework.

Now, Pindy mentioned that the TOSS project incorporates a decision tree strategy. We asked Pindy to walk us through how this approach is helping organizations embed green software practices more effectively. How does this decision tree guide organizations in making sustainable choices throughout their software development and IT operations?

Pindy Bhullar: We use the decision tree approach for the TOSS project for a number of reasons, particularly in contexts where decisions involve multiple options and varying outcomes. It's also a great way to visually represent complex decisions into manageable parts, and it helps decision makers visualize the entire process in a structured, analogical format.

It also enables the evaluation of multiple potential paths and their respective outcomes. So each decision point can have different branches, each representing a different course of action. One of the benefits of decision trees is the ability to easily update or expand as new information becomes available.

This flexibility is critical in the space of green IT and green software, as this topic is constantly evolving.

Chris Skipper: It's clear that the decision tree approach adds flexibility and adaptability, making it a perfect fit for an evolving field like green IT and software. Now, let's dive into the specific tools and technologies that are supporting the TOSS project.

We asked Pindy to highlight some of the key tools or frameworks being used and explain how they align with the project's sustainability goals. How do they contribute to helping organizations achieve lower emissions and more sustainable software practices?

Pindy Bhullar: To build the framework of decision trees, we are using mirrorboards.

Initially, it helped us to brainstorm and use the ideation tools to create mind maps to generate and organize our ideas in an interactive way. We also benefited from the real time collaboration and, more importantly, the ability to create the visual charts. The tool is enabling us to progress with the TOSS framework and build the sustainable software decision trees.

Chris Skipper: Now, let's explore the collaborative side of this initiative. We asked Pindy if there have been any significant partnerships or collaborations with other organizations or teams that have enhanced the success of the TOSS project. How have these partnerships contributed to its development and progression?

Pindy Bhullar: There have been excellent collaborations during this project. The workshop sessions were critical in partnering with organizations because it enabled us to further build the TOSS decision trees. It also helped us to make faster progress, while allowing the group to discuss new ideas, make revisions, and also to bring new insights.

Chris Skipper: It's clear that collaboration has played a crucial role in pushing the TOSS project forward, with the workshops really driving the development of those decision trees. Now, let's shift focus to the progress the TOSS project has made over time. We asked Pindy to walk us through some of the significant achievements or milestones the project has achieved so far, and how has it evolved since its inception earlier this year?

Pindy Bhullar: At the start of the project, we created a business case which outlined the TOSS project and what we wanted to achieve. Then we moved into a phase of brainstorming and mind mapping, really trying to capture key points of how we wanted to develop the framework and decision trees. We started then to break down the functions that would be involved in organizations and we created the four pillars that I mentioned earlier.

And out of that, then we started to get into the detail and start to create the decision trees. We have progressed since the workshops, and now we're working towards version 1.0 of the decision trees. We have redeveloped the strategy and implementation pillar, and we're still working on the operational and compliance and regulation pillars.

From the initial ideas, we've added further content and details to the framework, and it's constantly evolving.

Chris Skipper: It's truly fascinating to hear how the TOSS project has progressed. From the initial business case to the detailed decision trees, and the continual refinement of the strategy and implementation pillars.

Now, as we look to the future, we'd love to know more about what's on the horizon for TOSS. What are the next steps in the project, and what long term impact will it have on the widespread adoption of green software practices across the industry?

Pindy Bhullar: Over the course of the next few months, we want to complete version 1. 0 of the four decision trees. Also, create the guidance documentation that will sit alongside it. And in addition, create a white paper documenting the framework. We want the long term impact of the framework to help organizations implement tools, methods for calculating their emissions, processes, ensuring that we link the strategic level of the organization all the way through to software development and operations.

Chris Skipper: I'd like to thank Pindy for sharing such valuable insights into the TOSS project. It's clear that this framework is not only about integrating sustainable practices, but transforming the entire approach organizations take to software operations. From her detailed explanation of the four pillars, strategy, implementation, operations, and compliance, it's evident that TOSS provides a holistic solution that embeds sustainability at every level.

The collaborative workshops and iterative feedback process she described have played a crucial role in refining the decision trees, and it's exciting to hear that version 1.0 is on the horizon. As the project evolves, it's clear TOSS will have a lasting impact, empowering organizations to seamlessly incorporate green software practices and meet their carbon reduction goals.

We truly look forward to seeing how the framework will continue to grow and shape the future of sustainable software. Now, we've come to the end of the episode, but before we finish off, we have a few events to read out. Firstly, we have Sustainable AI, Myth vs Reality, Gain Insights and Actionable Strategies on the Intersection of IT and Environmental Responsibility at this in-person event hosted by Sustainable IT Netherlands at Accenture in Amsterdam on October 15th, starting at 6pm Central European Standard Time.

Next up, we have CNCF Sustainability Week, Cloud Native for Green Software. Share and explore ideas, patterns, best practices, and tools in the context of the green software principles. This hybrid event is hosted by Green Software development, Karlsruhe at Blue Hands in Karlsruhe on October the 15th at 6:30 PM CEST.

And finally, we have Code Green London October Meetup. Learn about the latest in green software and network with London's green tech community. Also on October the 15th at 7:00 PM BST. This in-person event at the Red Badger in London will feature past environment variables guest Tereze Gail. Who will be talking about Salesforce's sustainable AI approach.

Hear how the world's largest enterprise software company is balancing AI innovation with environmental responsibility. So, we've reached the end of this special backstage episode. I hope you enjoyed the podcast. To listen to more episodes about Green Software, please visit podcast.greensoftware.foundation and we'll see you on the next episode. Bye for now.

View Details

This Week in Green Software, the affable Anne Currie is joined by Sara Bergman, Senior Software Engineer at Microsoft and co-author of Building Green Software. Together, they dive into the complexities of sustainable data in relation to AI and cloud computing. They explore the environmental impact of managing and storing vast quantities of data, and question the feasibility of making these processes more eco-friendly. The discussion touches on cloud providers' carbon reporting, the importance of using AI responsibly, and how businesses can optimize their cloud use to minimize their environmental footprint. Tune in for an insightful conversation on balancing technological advancements with sustainability in the age of AI.

Learn more about our people:* Anne Currie: LinkedIn | Website * Sara Bergman: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Report: Thinking about using AI? - Green Web Foundation [03:54] * Why Cloud Provider GHG Reporting isn’t enough: The Case for Product-Level Accountability [14:16] * Is sustainable data storage a paradox? | TechRadar [33:03]

Events:* GSF Global Summit in London Summit (October 1 at 6 pm BST · London) [37:56] * GSF Global Summit inGlobal Summit Munich Summit 2024 (October 1 at 1:30 pm CEST · Munich): * GSF Global Summit in Green Software Summit Hamburg (October 1 at 1:30 CEST · Hamburg) * GSF Global Summit in Dublin (October 8 at 9:00 am BST · Dublin): * Green Software Summit Berlin (October 9 at 6:30 pm · Berlin): * GSF Global Summit in Singapore Edition 2024 (October 9 and 9:00 am SGT · Singapore): * GSF Global Summit in2024 Tokyo (October 9 at 6:00 pm JST · Tokyo):

Resources:* Building Green Software [Book] [02:04] * Greening Digital and the Rebound Effect | Environment Variables [11:36] * GitHub - Green-Software-Foundation/real-time-cloud [21:35] * Green Software Maturity Matrix [21:55]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Sara Bergman: What data do we need to take in order to take meaningful action? Like, what is the level that, of course, yeah, if I could get minute by minute, like there's tons of stuff we could do and correlations we could draw, but what is the level of data that we would need to start taking meaningful action? And I think that could unlock a lot of good things.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Anne Currie: Hello, and my name is Anne and welcome to

The Week in Green Software. So this week, you won't be hearing the usual dulcet tones of Chris Adams. I'll be joining you, Anne Currie, and we'll be delving into the tricky, but interesting world of sustainable data, whether it's possible to store and manage huge quantities of data, which we will need now, particularly for AI, in a way that's eco friendly.

Or is that impossible? Well, look, I'm going to leap through to the end and say, we have to do it. And therefore it is not impossible. It just has to be done. We'll find a way of doing it. And there are ways of doing it, which we'll be talking about today. we'll also be exploring why big cloud providers' carbon reporting isn't really telling us the full story.

Or, well, we are not interpreting it in the way that it was designed to be interpreted. And we need to be more careful about that. We're reading more into it than is true. And we need to be much, much more explicit about what the carbon reports from people like AWS and Azure actually mean.

We'll also be talking about data centers and AI. And that's something that my guest today is an expert in. And talking about my guest, joining me today is my co-author on Building Green Software, the book on what we need to do to make the tech industry green, and also Environment Variables regular, the lovely Sara Bergman.

So Sara, do you want to introduce yourself?

Sara Bergman: Yeah, hi. Thanks for having me on again. Always lovely to be here. I'm so excited to have a chat with you, Anne. Yeah, my name is Sara Bergman. I am a senior software engineer at Watttime. Microsoft, author of Building Green Software. And like here, I'm always asked, what have you been up to recently? Nowadays, I'm like, what have I been up to recently?

I did a fun thing, though. I had the talk for the Norwegian, because I live in Norway, and the Norwegian tax authorities about green software. And that was really fun. I love it when Because they are actually very far ahead in their journey, they're one of the most innovative companies when it comes to IT, so it was really fun to come out and have a chat with them.

Anne Currie: That's great. And I should introduce myself as well. My name is Anne Currie and I am co-author of O'Reilly's new Building Green Software along with Sara and our other co-author, Sara Hsu. And I also do a lot of training. So I've been busy at the moment doing loads of training courses. So, workshops on building green software and also an experts training course, which is all quite good.

So, if you want to get involved in any of that stuff, you can follow me on LinkedIn. So, as usual, today, we will be talking about a couple of interesting articles, publications that have come out over the past week around green software, all things green, and as usual, all the links to the articles will be in the show notes, so you'll be able to read them yourselves afterwards.

But I'll give you a little bit of a summary about what they say. So the first article we'll be talking about today is from the Green Web Foundation. And it was written by our normal Environment Variables host, Chris Adams. So that's where he is, or that's what he's been up to today in his work at the Green Web Foundation.

And he wrote it with his colleague, Hannah Smith. And the report is all around AI's environmental impacts. And it's got some interesting figures in there. Basically, AI uses a load of electricity and at the moment, as we don't yet have a completely green grid, that means that a lot more CO2 is being emitted into the atmosphere as a result of the fact that we're training a lot of models, doing a lot of inference.

So it is an interesting report and it's, I'm going to kind of summarize, they have some actionable things, some questions for you to ask yourself at the end of the report. So I will go over those now and then Sara and I can discuss them. The first is that you should always question your use of AI.

That's kind of part of using the right tool for the job. Is AI the right tool for what you're doing? Is it overkill? Could you use a spreadsheet? That's If you are using AI and you decide it is the right tool for the job, are you using it properly? Are you using it well? Are you using the right AI tools for the job?

And the third is to try and get ideas of your footprint, of the footprints of the work that you're doing with the AI, so you actually have an idea about what impact it is having and what you're going to need to do about it in the future. So Sara, this is kind of your area. Did you enjoy the report? What did you think?

Sara Bergman: I did. It's a very long report. It's very well written. Obviously, I mean, with Chris and Hannah, you're going to get something that's well written, of course. So no surprises there. No, it's good. And I think also for people who are maybe newer to the field of green software and green AI in general, there was a lot of good background to like really help understand the intricacies of this area. And something that I particularly find interesting in the shift we are now is that they talk about different phases where your emissions kind of stem from, it's like manufacturing, training and inference. And now, like you said, we talk a lot about inferencing, like using AI, that the use phase is what we talk about.

But back when I started, sounds like I'm really old, only four years ago, not that long ago, but when I first started talking about green AI. Yeah, a lot of, a few people, not so many were talking about green AI. A lot of people were researching, but not so many people were like discussing it. And then it was a lot of focus on the training.

There was a lot of great research being done on how to minimize the impact on training. I think in the research community, that's maybe the easiest, not the easiest thing, but a good first thing to research, right? And now we're seeing more focus on. on the production side, not like inferencing. And I think that shift has been very interesting to follow.

Anne Currie: But yeah, it is fascinating, isn't it? Cause there's loads, and we've had this conversation offline, because obviously we a book together and therefore we talk together quite a lot. But we've had this conversation a lot in that it feels like there's a load of stuff to be learned about inference.

So how you actually get the answers back as a user for models from the world of things like CDNs, how do you get fast answers and easy answers to things all over the world from data that is not necessarily by default, wasn't created close to the user who's querying it?

So yeah, there's, loads of prior art there to learn from it. It's a really interesting field.

Sara Bergman: It is a very interesting field and I think an additional like spiciness of this is that now a lot of people equate AI to large language models. That's not all of the AI that exists in the world, it's just the right now the most popular and what we think maybe will be the most interesting use case, or for like productivity and stuff.

And for that we require a lot of specialized hardware, like GPUs or TPUs on CPUs, et cetera, which is another thing to kind of reason over. And, maybe if you're very good at handling your production workloads on a CPU, like this might be a new area for you where you, we need to learn as an industry. I thought that was an interesting part of the article.

Anne Currie: Yes. Yeah, it is. It is all very interesting, isn't it? it's like something that all three of us say in the book a lot, is that there's a load of clever stuff going on in the tech industry, and it's usually, there's a desire to make things efficient because it's cheaper. Otherwise, everything gets very expensive.

So if you use things as they were intended to be used and use the right tools for the job, usually that's significantly more energy efficient and therefore greener. And the same is very much true of AI, isn't it? If you use the right tools, the right hardware, the right models,

Sara Bergman: Yeah, exactly. Exactly. So that and then I think that ties into right, that was it number two on their like, use AI responsibly, which was interesting. I also like the first question that they had. Now I'm scrolling and losing it was it think about when you should use AI? Was that the phrasing?

Yeah, question your use, know when to use it. Like, do you have a favorite use case?

Anne Currie: Well, I have to say, I do love generative AI.

Sara Bergman: Yeah.

Anne Currie: it's, an interesting one, cause quite often... well, it's amazing how often it comes up where people think that it's kind of like you're either doing AI or you're green. That's it. Those are the two, two options. And they cannot be the two options.

It can't be either don't do AI and therefore it's green or do AI and therefore it's not green. They have be brought together because if there's one thing that we know, two things we know are coming in the future for humanity. One is climate change. The other is AI and use of AI and AI systems.

They cannot be mutually exclusive. They have to be brought together. I mean, and AI is just computing. It's the same kind of things that we do when we talk about in Building Green Software for all computing just needs to be applied to AI. It's not a, it's not a new thing on its own, but

Sara Bergman: and I agree. And I think that's also so interesting with this, like, larger discourse, as you say, I think not only that it exists in other areas of life, where there are some people who would be like, "no, we should just stop doing this, like, stop advancing technology, and then everything will solve itself," but that doesn't work. We cannot and does not want to go back to like a farmer society where everyone grows your own food. Like if you're into growing your own food, that's fantastic. I'm happy for you. I grow radishes on my balcony and I enjoy that thoroughly. But there's so much advantage and good for humanity and our planet that comes from technology as well.

So we need to do both. We must do both. Like, it's non negotiable. So it's more like how and when? And 'when' is hopefully starting now.

Anne Currie: Cause the trouble is, if you have that conversation, if you say, "Oh, well, I want to do AI, therefore I can't do green." People will choose AI because the businesses, if they don't, if they don't try these new tools and services as they come available, they will go out of business. So, if you say, "Oh, well, if you're going to be green, you can't use AI," then what you're telling people is don't be green.

And it's crazy. You're just making the wrong arguments. But anyway.

Sara Bergman: I fully agree for sure. And I think it was something we were in a different, or like this podcast together, but another episode and you said something that I've been carrying with me for so long. Sometimes people say something and it just get like something clicks. And what you said, and I'm going to maybe paraphrase, but things that are limited are sort of less concerning. Like, for example, if you build a super efficient washing machine, I still have only so much washing up to do. There is an end to how much I will wash it. Like this is in response to Jevons paradox, of course. And the same goes for this. Like, yeah, AI will make us more efficient, more productive.

Okay. But we'll then just do more. It's like, yeah, but the working day is sort of eight hours and we are only so many people on the planet. There is a limit to when we'll be done, whereas for crypto, for example, which always comes up when we talk about this, of course, there's no limit. I will never say I have enough money, I'm done mining. But there is a limit where I say, thank you, co-pilot for GitHub, I don't need more code suggestions.

I'm happy with my feature now, sort of.

Anne Currie: Oh, yeah. That's an issue, because, I always tend to think that one of the, one of the things about AI is that, that we're not,, we haven't yet reached the limits of what we want to do with it. But, you're right. There's, it's nowhere near. I mean, we've already come up with the thing that is the most limitless.

You've heard the use of CPU and it's CPU use that's really the problem that's, that uses a lot of electricity, is crypto. It is literally boundless how much we might want to do with it. So we've kind of already created the worst 30.

Sara Bergman: yes.

Anne Currie: AI is so

Sara Bergman: not it.

Anne Currie: it's a comparison. At least there's some people,

I don't know, we shouldn't be controversial because there are a whole load of people who say, well, there's loads of benefits of cryptos, but I personally do not, I'm not a crypto bro.

Sara Bergman: Same. No, I did write my master's thesis on blockchain. I think blockchain is a cool invention. Like, it's a cool technology. And there are use cases that are, of course, bounded. And then there are use cases that are unbounded. And I think people can use their own head to figure out what's what.

Anne Currie: We've now got ourselves into enough trouble talking about good and bad uses of technology. And to a certain extent, it's very hard to say what's a good or bad use of technology. I tend in my head to think it was a bad use of technology, I, not everyone agrees with me, but we will move on to the next article, which is one, now...

So this one, cloud provider Greenhouse Gas reporting isn't enough. The case for product level accountability. Which is, again, the link is included in the show notes. Now I know, because this talks about Azure, Sara, you, might be in a position where I'm saying things to you and you have to say, you may say that "Anne, but I cannot possibly comment."

So in which case you'll just have to leave me to talk, but that's fine. Cause I can talk endlessly about this stuff because I find it really, I think this is absolutely fascinating and there's loads of stuff to learn from this article. So the article is all about, it's highlighting the limits of cloud providers and data, the carbon footprint reports.

And it emphasizes the need for companies to track emissions at product, at data product level. And it argues that these broader reports mask the true environmental costs of specific processes like data and that things would be better if you broke the emissions down to product level. And I think that's great, but I don't think that's actually the problem.

I think it's well worth reading the article, but I think it skips over, I think, what is the more significant problem that we're having, that we're seeing, because I'm out there talking to people a lot and I know this is a significant problem at the moment, that the cloud providers' reports are doing something, a lot of the new cloud providers' reports, particularly the recent AWS releases are doing something which I can't really shout at them for because I demanded it myself some years ago and I am somewhat hoist by my own petard for this.

So many years ago, me and a fellow, a collaborator called Paul Johnston ran a, back in 2018, we ran a campaign called Sustainable Servers by 2024. And what we were campaigning for was that all of the cloud providers would commit, and this was some time ago, would commit to being carbon neutral by 2024.

And it was really aimed entirely at AWS because Google and Azure were already carbon neutral at that point and AWS was not. So, we ran this big campaign and we had petitions and all kinds of things for saying that they should be carbon neutral, collateral and tradeful. And of course, carbon neutrality is quite a limited demand.

It's basically saying, "I want you to be carbon neutral. I want you to know how much your carbon emissions are. And then buy offsets that match the carbon emissions." Now, we all know that offsets are good in the past, but they're not time matched. They don't mean that the carbon savings that you've created are time matched with the carbon emissions of your systems.

So your systems can still be throwing off carbon dioxide into the atmosphere whilst you are carbon neutral. So it was a useful, a useful measure in 2018, it was still useful. Now in 2024, it's actually not as good as it could, it's not enough. it's the bare bones. It's the least we can ask for.

But AWS have done it on time, 2024, and they are producing these reports that they're giving to AWS customers that say, "you're carbon neutral, your systems are net, not producing any carbon." But the problem is that a report that says, and that's great, but it is nowhere near enough.

It's not enough. It's great information for your finance team because your finance team don't want that data. They need that data, particularly if you're going to be, if you're in the EU or you're selling into the EU. Because the EU is now demanding carbon taxes, and carbon taxes are another form of offsetting, really.

You pay for the carbon you're emitting into the atmosphere. So if AWS produced a report saying, look, there's no net carbon you're producing into the atmosphere at the moment, which they are generally at the moment for most AWS systems, it seems. That is really a report for your finance team, so they don't have to, so they can go, "oh, that's great.

The offsetting has already been done for me." That is not a report for your tech team because they're not saying that no carbon is actually being produced by your systems. Your systems are still producing loads of carbon and you still need to adjust your systems. to reduce carbon, which you can do, but the report is kind of giving you the impression that you don't need to.

So is that something you can comment on or?

Sara Bergman: Yeah, this gets me going, right? Cause I'm all about enabling like people with feet on the ground, hands on the code is what I say. So I do agree a lot of the reporting that comes out, it's much better than it used to be. This difference, and maybe now we're slipping into the next paper a little bit, but there, of course, difference between market-based and location-based reporting in the Greenhouse Gas Protocol.

That is a feature, a fundamental feature of the Greenhouse Gas Protocol, which every single industry makes use of. Now, not only,

Anne Currie: I'm going to interrupt you at this point, just because this is something that I realized when talking to people. One of the issues is that people don't understand the difference between market-based and location-based. What does that mean? So market-based, I think that the word that people really understand is offset.

If you're market-based, it's saying you're still putting carbon into the atmosphere, but we are offsetting it, which was great 10 years ago, nowhere near good enough nowadays. location-based means actually, it's about reducing, it's about not putting carbon into the atmosphere. So that's what we want. Market offsets are a step to getting there, but they are not there.

So sorry, go on.

Sara Bergman: yeah, no, but that's, good. I also like it's like the electrons you pay for versus the electrons you use, if you want to get really down to the socket level. So yeah, I think that's something to talk about. Also, something that I kept thinking about after reading this article, and I just want to read the comment from it because I think the comment was amazing.

And the comment is, "conceptually, I agree. More data is better. However, I've never met anyone advocating for product level data who has actual operational experiences of running shared service platforms and therefore would understand the complexity of delivering these metrics. Because yes, if we're talking about, we could have one report for the finance team, that's fine, but should there be an additional one for, the people who write the code, who maintain the service? And then the question becomes, okay, but what data do we need to take in order to take meaningful action? Like, what is the level that, of course, yeah, if I could get minute by minute, like, there's tons of stuff we could do, correlations we could draw, but what is the level of data that We would need to start taking meaningful action? And I think that could unlock a lot of good things.

Maybe we don't need the world. Do you know what I mean?

Anne Currie: Yeah. I know what you mean. I totally know what you mean. I think we should step down our emissions. Well, having said that, within the Green Software Foundation, there is a project, the Real Time Metrics Project. And that is looking forward to when we can have second, millisecond by millisecond data about, so we can tune applications to, to get there.

But then we also have another project, which I run, so their real time metrics project is run by Adrian Cockcroft and I run a project called the Maturity Matrix Project, which, comes out of our book. So it's, the penultimate chapter in our book. And the Maturity Matrix Project is start, is, it says that all that real time stuff is really quite advanced.

It's way further advanced than pretty much anybody in the world currently is. What we actually need at the moment is quite simple stuff, like "just turn off machines." Turn off machines when you're not using them. And you can, you don't need real time metrics for that. The other thing that we can do that doesn't require real time metrics is, so one of the things that kind of annoys me about the new AWS Cloud Footprint report, which is, it's fine, it's not a lie, it's just giving you offsets.

It's just telling you what your offsets are. It's totally fine. But people are misusing it and misreading it as thinking it's about carbon emissions. There's another thing that AWS have said, which I really like, which is that, "look, we all do a load of work."

It's called the shared responsibility model. "We will take responsibility for the sustainability of the cloud, if you take responsibility for the sustainability in the cloud. Now" I like it, except that it's also very confusing. What they are saying is that "we will build tools that can be aligned with actual location-based zero carbon operations.

We will build those tools." Those tools in the book, we call them green platforms. They're things like serverless, spot instances, really clever instance types. You see, it kind of aligned with their whole modernization strategy, how you get into the cloud and use it well, as it was intended to be used.

So they're saying that, "but it's your responsibility to use those tools. We can build those tools, but if you don't use them, you won't be green. If you just sit in dedicated instances, you will, there's nothing we can do about it. You will never be green. We'll offset you," which is why, the reports say, "well, we'll pay for your bad behavior.

But it is still bad behavior." You'll get to carbon neutral, but you'll never get to carbon zero. And I think that those messages, which are quite complicated, can both exist, but they need to be quite clearly communicated. And at the moment, I don't think we are being so clearly communicated. What's your thoughts?

Sara Bergman: Yeah, this is also, I think this is also something I thought a lot about reading this article. Like, where is the line? Because many cloud providers, they do have clearly green ambition. They are financially incentivized in many ways to be more energy efficient, use less resources of course, because all of those things cost money for any cloud provider, even if that cloud provider is your local on-prem.

So that is one thing, they wanna make cheaper stuff that are often greener, almost always greener, but it is your responsibility to get on them. And how do you do that? Now, all three of the cloud providers do have architected frameworks that have a dedicated sustainability section.

And there for some scenarios, it's actually incredibly good. Like it's very detailed. So you can go and just like, "Oh, my scenario fits into this." I would like those sections to be longer for all of the big three and for the smaller ones, maybe to include more. But I also now maybe skipping randomly ahead, back and forth, something, a mental image that I think helps because sometimes I think the key message is getting lost.

"Okay. But the cloud is green. Why do I need to take action?" and that is a tricky conversation to have because Yeah, if you're selling the cloud, of course, you don't want to say "no, but it's not green." It's like, it just becomes a bit messy. So a mental model I like to use, which I heard from another wonderful woman here in Norway, which is if you have a car and you have a ski box, because right, we have lots of skis here.

So they can think of the car as the cloud and it's the responsibility of the car manufacturer to make that as efficient and green as possible. And they do, right? And but you, as a user, you choose how do I transport my skis in the car? Do I transport them inside the car? Yeah, maybe they that would be greener right because then there's no additional wind catch of the ski box on top, but maybe they don't fit, so you put them on the ski box on the roof. Fine, you accept that additional wind cost and thus increase the energy. But, once ski season is over, and you don't need the skis anymore, what does eeveryone do? You've remove the ski box. I don't see anyone riding around with the ski box in May, just because, right?

And the same goes for the cloud. So yeah, the cloud has lots of work, a lot of stuff in it to make it greener. But if you choose to use a ski box, that's fine. But once the ski season is over, remove the ski box. So once you're not using your test environment, remove it, shut it down.

Anne Currie: Yeah. Yeah. I like the analogy. It's very Scandinavian.

Sara Bergman: It's very Scandinavian, I'm sorry, but I am very Scandinavian, so that's what you get. I guess the same applies if you have a surfing board, I suppose you put them on the roof as well,

or a canoe,

Anne Currie: A canoe!

Sara Bergman: yeah, or a kayak, yeah. They have longer seasons though, but, so yeah, to try to translate, I feel like I was very, poor Chris who has to edit this, all my ramblings.

But yeah, as a cloud user, you have a responsibility and I think there could be two reports of showing this is what we as a cloud provider, I think all cloud providers are pretty good at this. This is what we took responsibility for. That's awesome. So much better than it was like 10, 5 years ago.

But then also how do we enable people using the cloud to take green actions? Because they want to take green actions, we want them to take green actions, like how do we enable that at the same time? Yeah.

Anne Currie: Yeah. I mean, it's, kind of like "is the cloud green?" The trouble is the, answer is as always in tech, it depends. Oh yeah. It's like, it depends. Are you using it as it was intended to be used? And if you, and the, one of the reasons why you sometimes see Gartner reports and things saying that the cloud is really poorly used,

it's because there's two stages in moving into the cloud. One, is you just kind of lift and shift. For most people, they lift and shift. Although you might argue that's actually never a really good way to go into the cloud. I've written books about this. It's not, but it's, it is a way, a common way for people to go into the cloud.

But once you've lifted and shifted, you have to then actually use the cloud, as it were, you see, you have to go beyond that. If you stop at lift and shift, it's really ungreen. It's worse than being on prem', because in the cloud, it's so easy to over provision. So you have to actually, you have to adopt the cloud, it's called cloud native and it's not really cloud native, but then you have to adopt the cloud way of doing things because otherwise you will over provision and you will then make more carbon than you did on prem', because it's harder to over provision on prem'.

Sara Bergman: Yeah, And that's a journey. And that's something I think all cloud providers are pretty good at supporting, right? That's their bread and butter in many ways.

Anne Currie: It is, they just want people to do it, but still it's hard because it's really so hard to lift and shift into the cloud that once people get there, they go, "thank God for that." And they don't want to go and look at what happens next, which is kind of one of the issues of lift and shift as opposed to kind of just slicing up and moving bits and bits one by one into the cloud, is that

these big projects, they're so painful that once you've done them, you never want to, I've done so many big projects in the past, and you always think you're going to go on and do the next stage, but you're so destroyed by that project. You just think, "Oh my God, we're all burned out. We don't even want to think about it again."

It's, yeah. Yes.

Sara Bergman: We need to glamorize DevOps or operations. It needs to be something there, more and more afterworks, I don't know. Something to make them more glamorous.

Anne Currie: These big projects are awful. I never want to do one again. But anyway. Yeah. And they're, ungreen because you then go on to the next bit where you start to actually refine and improve. So yeah, it's, we need to step back and think about how we're doing that. So, which is, I think a lot, I was signing books at a conference about kind of, DevOps and, CICD and team topologies and moving faster releases, last week.

And I think that's really green because if you can't move, you can't adopt these better tools and services that remain.

Sara Bergman: Yeah, exactly. Yeah, I also said someone, or heard someone who said like, what we need now is like performance engineering, we need to go back to basics in many senses, right? And because a lot of these learnings are not new. It's the same when people are like, "ooh, if I," now I'm going on a tangent here, but if people want to be greener, they're like, "oh, I should just rewrite, like, make my code more efficient."

And like, by all means do. But if you haven't had like a reason to do that yet, I don't think you're going to convince your management chain that sustainability is going to be the reason why you go implement it because high performance computing is not new at all. Like we've known about all these things for a very long time.

So if you haven't done it yet, I mean, kudos to you if sustainability is the thing that makes you implement it. Kudos to you. I just think it's going to be a tough sell.

Anne Currie: I've mentioned a few times on environment variables, but it always interests me, is on that note of efficient code is expensive and we don't do it anymore, sara now works on Microsoft Exchange and 25 years ago, I also worked on Microsoft Exchange, but in Microsoft Exchange 25 years ago, we had to have everything written in C because the hardware was, it was just not possible to do it using anything other than the most optimized C code, which meant that it was really expensive to do things.

It took a long time. Yeah. The world has changed. we've got better hardware and we use it. We use it to go, to not have to write everything in C.

Sara Bergman: Exactly. And we see the same on the mobile industry, right? They have more apps that do more things now because their phones can handle it. They couldn't when the first smart modes came out and just, again, going back to what we talked about earlier, I don't think we can stop technology progressing in order to be greener.

We need it to progress and be green at the same time.

Anne Currie: Yeah. Yeah. We need it all.

Sara Bergman: People are going to call us greedy.

Anne Currie: We want it all. So we're going to zip onto our final article link today, which is,

Is Sustainable Data Storage a Paradox? So it's a piece in TechRadar by Jon Howes about environmental challenges posed by cloud storage and AI, and the rising energy demands of data centers that are associated with AI and storage. So thoughts? Is green data storage possible? Sarah?

Sara Bergman: To quote you, it has to be. No, but I, okay. So there are many things here, but I think also he said that cloud is the least wasteful storage solution because it is highly optimized, blah, blah, blah, blah. So I don't know if the paradox is. Could there be other ways? Or if the paradox is, I don't know, it was a catchy title, and I'm not sure I understood what the paradox was.

But also, what I really kept thinking about, is storage really what we should be concerned about here? I (naively, maybe) would guess that compute would be much more resource intensive than the actual, like, store at rest. Then, of course, training the model, you would need to access the storage.

But again, I would be, in these days, more concerned about inference. And then, again, naively maybe, I would expect the CPU and GPU usage to be what we're worried about, not our disks.

Anne Currie: Yeah, I tend to agree. I would say with data, the opportunity there is there's quite a lot of low hanging fruit. And it's a really, good example of the shared responsibility model as well, that it's up to you, to us as users to not be wasteful in our use of data. And by waste, I don't mean storing more than we need, because I think that telling people to throw the stuff away in the world of AI is just crazy talk.

No one's going to do it. You're going to keep everything, right? We just need to see if the general AI can make use of it. The wastage is having it in a medium that's where it can be accessed more quickly than it ever needs to be accessed. So that the longer, if you say, look, I'm going to access this once a year, you can stick it all on tape and it's practically free in terms of carbon.

You can save as long as you like, there's this, that kind of like never underestimate the bandwidth of a station wagon full of tapes driving down the freeway. Tapes are pretty good. You can put a load of stuff on tapes and most data, especially data for AI, it doesn't matter if it takes you a couple of hours or even a couple of days to get it back.

You can, so you don't need to keep it on sSD, where it's just really much more carbon intensive than tape. So it's just, it's quite easy. You just need to think about it and not store things in the wrong medium. Use the tools that are best suited to the job.

Sara Bergman: yeah, be diligent about hot, warm, and cold storage. Like, what do you need, when, and how much? And yeah, also people say, "should I delete all my photos and emails?" I'm like, "no, you want them, right?" You're going to look at your photos again, you're going to maybe search or read your emails again. So don't remove them.

Maybe you know, unsubscribe to the email you never look at. That's like an option if you always get an email from your build pipeline, but you never look at it. Yeah, maybe don't need to get those emails even. Again, low hanging fruits exists. But yeah, storage mediums are not energy intensive if they're cold.

Anne Currie: Yes. Yeah. Don't keep it hot when it can be cold. Cold is the new hot. It's the new hot.

Sara Bergman: and the new green.

Anne Currie: And the new green, yeah. Right, so yeah, we've talked through all of the things. So is there anything else you want to say, coming out of what we've talked about today?

Sara Bergman: Oh, I don't think so. I think it was an interesting discussion. We are, what I love about this industry is that we're constantly on our learning curve. New things always come up, we have to adapt and adjust, and I get to put on my engineering thinking hat. And I love that. I think, we should be excited about that.

Like we have opportunities to be green, "ooh, I have opportunities to learn, opportunities to explore," not like, "ooh, this dreadful thing I have to go do." It can be fun. I mean, yeah, make it glamorous.

Anne Currie: Well, on that incredibly positive note, I will, sign us off. That's fantastic. So before I sign off today, just a reminder, all the links are in the show notes, so have a read through the articles yourself. And to tell you that this week, it is the Green Software Foundation Global Summit event.

So there are live events in quite a few cities. There's one on the first in London. There are ones in Munich and Hamburg, and there's one in Dublin, there's Berlin and Singapore. And, do feel free, I can't actually make, it's a real shame because I do really love to meet people in person.

And I think flying is one of those things where we, flying is an incredibly valuable thing. I don't tell people not to fly, but for me, the reason to not fly all the way over to London if you're in the US, for example, to go and meet people in person is, that you should set up your own local meetups, which are in person, which people can get to and from.

And because having people locally that you can talk with is incredibly useful. So set up your own summits if you can't make any of the summits that are out there.

Sara Bergman: Or your own meetup, if a summit seems a bit much, then set up your own GSF meetup.

Anne Currie: Yeah, that is an excellent idea. You'll meet a load of lovely, like-minded people, and you can chat away about saving the world, which is always a good thing to chat about. So one of the nice things about the green community is we're all aligned on trying to make positive change without turning everything off and going back to the stage.

So we've come to the end of our podcast and oh, it looks like Chris, our editor, has given me a final fun question for you, which is, if you were to design an AI that had zero environmental mental impact for a totally non-serious purpose, what would it do?

Sara Bergman: I'm embarrassed to say that I thought so much about this, because my mind went, ooh, what would I do? And then I'm like, would I optimize my life? Would I make something silly? Would I make something useful? And then I just, there were so many options that I don't know. But some of the things that like, popped up was like, organize all my photos.

I have a small child. I take a lot of photos of him. I would like for there to be some nice organization going on there. That would be very nice. Also, an AI that designed cute nails that I could do at home with like the stuff I have. Because I am not artsy, but I like fun nails. So yeah, like, like, if I am bad at doing my nails and I have four colors, what can I do that's cute?

Anne Currie: And of course, all of those things could be done zero impact because the, key thing about them is that they are not latency insensitive. You could say, well, actually, I'll wait to run my models and do my inference till the sun's shining and the wind's blowing and there's excess electricity on the grid.

The, I don't, I would, to make it so it's there, I wouldn't say, well, it's in the middle of the night and it's still night, but I'm really desperate to get my fancy nails done.

Sara Bergman: Yeah.

Anne Currie: Just wait. Just say, well, I'll, find out tomorrow morning what the AI is storming. It's all about making things less on demand, so we align with when the sun's shining and the wind's blowing.

Sara Bergman: Thanks for taking me back to technical.

Anne Currie: So thank you very much for being on. It's been, as always, delightful to talk to you.

Sara Bergman: Likewise. I had a blast. Thank you so much.

Anne Currie: It's nice. And we don't say, obviously, while we're writing the book, we talked together all the time, but now that the book's finished, then we talk together less often. So for all listeners today, links are in the show notes. And if you haven't read Building Green Software from O'Reilly, you are missing a trick because that really, it's a fun read.

Everybody seems to be enjoying it.

Sara Bergman: Yeah. I think the top thing people are like, "Oh, it's fun." I'm like, "Yeah, it's funny. It's good."

Anne Currie: So if you haven't read it, crazy! Go out and read it, or join one of my training courses, which are also fun. So thank you very much. And I'm sure we will both be back on the Environment Variables sometime in the not-too-distant future. So goodbye from me.

Sara Bergman: Bye.

Anne Currie: Cheerio.

Chris Adams: Hey everyone, thanks for listening! Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again and see you in the next episode!

View Details

Host Chris Adams sits down with CEO Olivier Corradi and Tech Lead Íngrid Munné Collado of Electricity Maps, a company that leverages data to enable decarbonization of electricity grids. They discuss the complexities of carbon intensity data, the role of accurate forecasting in renewable energy, and how this data helps optimize electricity usage for sustainability. Olivier explains the origins of Electricity Maps, their goal of providing real-time carbon footprint insights, and their theory of change—targeting citizens, corporations, and institutions to create a greener future. Tune in to hear about the history, frontiers, and future of this engaging field.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Olivier Corradi: LinkedIn | Website | X * Íngrid Munné Collado: LinkedIn | Website | X

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Our Road to Impact: How we contribute to fixing climate change [04:56] * [1812.06679] Real-Time Carbon Accounting Method for the European Electricity Markets [20:24] * SCI Specification Achieves ISO Standard Status | GSF [21:24] * Electricity Maps | Client Story: Monta [29:52] * How to save costs and emissions with a flexible electricity load? [33:32] * How the prices can change by location | X [34:28] * Another example in Texas | X * Marginal vs average: which one to use for real-time decisions? | Electricity Maps [39:21] * eCO₂grid | 50Hertz [41:58] * Investigating Apple's Clean Grid Forecast

Resources:* Energy, Business, Climate & Geopolitics | Commons For Future [09:58] * Commons For Future [10:02] * The Week in Green Software: Mapping Green Software on the Grid [10:32] * Open Source | Electricity Maps [10:53] * How to trace back the origin of electricity [15:28] * GitHub - electricitymaps/electricitymaps-contrib: A real-time visualisation of the CO2 emissions of electricity consumption [19:26] * Online Browsing Platform (OBP) [21:33] * Finland extends nuclear reactor outage, sees power prices soar | Reuters [35:15] * Breaking borders: The future of Europe’s electricity is in interconnectors | Ember [35:49] * Carlos Pérez Linkenheil on LinkedIn: #energymarket #electricityprices #epexspot #dynamictariff | 23 comments * Increasing renewables without regulation or curtailment mechanisms - Lion Hirth | LinkedIn * Giant Batteries Are Transforming the Way the U.S. Uses Electricity * Solar will get too cheap to connect to the power grid. [35:57] * The reasons for negative prices - by Julien Jomaux [37:41] * Making Testbeds for Carbon Aware Computing [38:04} * Avoid restricting the SCI by prescribing a specific metric. [38:33] * MARGINAL EMISSIONS RATE – A PRIMER [40:00] * On the Implications of Choosing Average versus Marginal Carbon Intensity Signals on Carbon-aware Optimizations | Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems [45:19] * On the Implications of Choosing Average versus Marginal Carbon Intensity Signals on Carbon-aware Optimizations * On the Limitations of Carbon-Aware Temporal and Spatial Workload Shifting in the Cloud | Proceedings of the Nineteenth European Conference on Computer Systems [45:41] * [2306.06502] On the Limitations of Carbon-Aware Temporal and Spatial Workload Shifting in the Cloud * Tammy Sukprasert | Move Your Workloads To Sweden! | #53 - Disseminate | Acast * Methodology + Validation - WattTime * VERACI-T

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Olivier Corradi: The dream is to get to street-level granularity, and this is why flow tracing, by the way, is so important, because as you increase the resolution of what you're looking at, then obviously if I'm looking at just a city, most of the electricity is actually produced outside of the city, and that's also why, by the way, the whole forecasting challenge has just become massive. Try to forecast how clean the electricity is going to be at every location on the planet. Obviously, you need really good renewable forecasts as well. And that's what civilization needs if it wants to rely significantly on these renewables that are intermittent.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams. Hello, and welcome to Environment Variables, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. We often talk about carbon intensity, or how clean electricity is on this podcast, as one of the levers for making software more sustainable.

To know this, you need to get the data from somewhere, in a form that's easy to understand and consume. So today we're sitting down with two people who live and breathe this data from Electricity Maps. Electricity Maps is a company at the forefront of enabling a data-driven decarbonization of electricity and today we're joined by both Íngrid and Olivier from the firm.

Hey folks, how's it going?

Íngrid Munné Collado: Hi.

Olivier Corradi: Hi, Chris.

Chris Adams: Cool. Folks, we'll talk about the origins of Electricity Maps in a second, but before I do, I just want to give you a bit of space to introduce the two of you, actually. We normally go by surname first, so I think Olivier Corradi, you're ahead of Íngrid, so can I give you some space to introduce yourself first, and then we'll do the same thing for Íngrid, alright?

Olivier Corradi: Of course, and thank you so much for the invitation and for inviting us to the show. So, my name is Olivier, I'm originally a machine learning engineer and data scientist. My background has been academic, I've worked as well in the research industry with IBM Research and Simulating Electricity Grids. And I would say the most relevant thing that I'm doing now is Electricity Maps that I founded eight years ago.

Chris Adams: Okay, thanks for that, Olivier. And Íngrid, over to you, I suppose.

Íngrid Munné Collado: Hi. Hi, Chris. I'm Íngrid. I'm the Tech Lead at Electricity Maps and I'm very happy to be here. More specifically, I'm part of the grid forecast team where we built, as we have said, forecast models for renewable energy sources and other signals such as carbon intensity. I've been recently involved in replacing and improving the weather forecast data that we use at Electricity Maps to achieve better forecasts.

And yeah, outside of work, when I'm not working, I'm either going to CrossFit where I'm trying to learn how to do a pull up, which I don't know, or knitting and just making sweaters. So quite, quite contrast.

Chris Adams: Cool, thank you for telling me. I'm glad you mentioned weather, actually. I mean, as an English person, we talk about weather the same way that we breathe, I suppose, and as I understand it, you folks are both calling from Denmark, right? We're a little bit chilly today than it otherwise would be, right?

Íngrid Munné Collado: Yeah, it is quite cold for September. I think it's quite usual, but it would be a bit on the colder side.

Chris Adams: Yeah, same here. We, it's, Berlin has, someone has switched off the summer, so we now had to, like, I've cycled in with my coat for the first time today, and did not enjoy that. Okay, so I should introduce myself, actually, folks, if you're new to this podcast. So my name is Chris. I work at the Green Web Foundation as the executive director there.

I also work in the Green Software Foundation as one of the co chairs of the policy working group where we Basically, work on policy to see about coming laws and things that we might actually want to respond to or help members understand what the implications of might actually be. The other thing I'll share with you is that we try our best to have quite helpful show notes for this.

So we're going to mention various projects and papers along, and if you are viewing this in Spotify or YouTube podcasts or something, you might not see them. So be sure to look up podcast. greensoftware.foundation to see the full links and the transcript. Okay, you two folks sitting comfortably?

Íngrid Munné Collado: Yeah.

Olivier Corradi: We are, sure.

Chris Adams: Brilliant, okay, then I'll begin.

Okay, first question I'll put to you, Olivier, because I've actually been a fan of Electricity Maps for quite a while, and when I first heard about Electricity Maps back in 2017, it wasn't Electricity Maps, it was electricitymap.org. And this is something that is reserved for non profit organizations. So it's 2024 now.

And I now know that the same kind of cool map that I started talking about at conferences and so on, is now available under electricitymaps.com. And as someone working in a non profit, I end up talking and thinking about theories of change all the time. So there was a really interesting post I saw on the blog, on the Electricity Maps blog post, particularly talking about this theory of inaction.

And it's rare to see start ups talk about this kind of stuff with a fluency, really. So, Olivier, can you tell me a little bit about basically, what this is, and how this informs you spending all the time on Electricity Maps, because I know there's a few other things that you've worked on before.

Olivier Corradi: Yeah, I'm happy that you actually give me the opportunity to articulate this. So in the early days when Electricity Map was started in 2016, there was this question that remained for a couple of years afterwards, which was, "should we actually be an NGO or should it be a for profit company?" And honestly, the conclusion is that it depends on how you want to impact the world and it depends on how you want to be funded and so on.

But the way that we've been looking at things is basically to say when a company will pay you for something you're delivering, that represents a change that is happening in the world that is sufficiently valuable that someone will pay you to do it. And people are taking you seriously when they're implementing it.

So this was a little bit what tipped it over towards more of the, let's say, for profit world. But in order to make sure that we never lost track of the actual impact we want to have, we started having like this framework that we stole from someone else, honestly, and adapted afterwards. But first of all the vision we have here is to imagine a world where we have low carbon electricity that's delivered everywhere across the world, every hour of the year.

And this was really why Electricity Maps was created, out of almost a frustration of folks looking at the electricity grid from a yearly perspective, instead of looking at it hour by hour. And of course it made sense before we had renewables. Now that we, the wind doesn't always blow and the sun doesn't always shine, we need that.

And the angle we're taking here is data-driven decarbonization, as you mentioned, because we're a mixture of folks who come from academia, who know how to build machine learning systems and tech. So this is our angle. So with that vision in mind, providing clean electricity every hour of the day, we realized there's three pressure points that we need to apply if we want to create that transformation.

The first one is, we identify them as citizens. Second one, corporations. And the third one, institutions. And there is this framework that, that depicts a triangle of inaction where each of these corners are pointing at the other as an excuse to not change. For example, citizens are saying, "well I actually would love to be greener, but the government is just not putting the right incentives for me to be cleaner," like the public infrastructure is not helping. Another piece of it is the citizens are pointing at corporations and saying, "well, I, too bad, like, flying is actually cheaper than taking the train. Like, I don't have a clean offering here."

And then the corporations on the other side will say, "well, but everyone wants to fly, right? I mean, the citizens are not ready for that change." They'll say, "well, I'll just keep operating like I am." Corporations will point at institutions as well and say, "well, the right tax schemes are not here for us to make flying cheaper, actually, so we'll just continue what we're doing."

And then institutions will be, "we don't have" like the, let's say, "social acceptance from the citizens to actually, exactly, to put these green tariffs. And on the other hand we're just a small organization and institution, sorry," and you have corporations like Microsoft, OpenAI, Google, that are just like, more powerful than governments.

And so you can basically map these out in a small triangle. And we said, okay, so how are we going to impact this? And then most of our initiatives can actually be mapped to this triangle, where on the citizen side, the app that we have of Electricity Maps is creating this awareness, creating the debates as well to make sure we have a factual understanding and can challenge our politicians in the right way.

There's the piece on corporations where we are working with them in order to ensure that green offerings can actually hit the ground, like that we have electric vehicles that can use electricity at the optimal time, all these things. And it's a win because we get a financial cut of this and we can grow our company and grow the impact.

And then finally, on the institutional side of things, we're trying to make sure that the right carbon accounting methodologies and so on are being pushed. We basically want to live in a world where we have an accounting that represents what's physically happening in the world. And one example is we have a data portal where our historical data can be used by any company who wants to do granular carbon accounting.

Again, moving away from this world where you're doing it on a yearly basis to an hourly basis. So this is the framework we've put in place and the way we're articulating internally as well how we allocate resources and prioritize and make sure that what we do leads to impact ultimately.

Chris Adams: Cool. Thank you for that. I have one question following up from this, because when I was doing a bit of research, I looked up this triangle of inaction, and I think I might need one of your help, one of your help in pronouncing the person's name. Is Pierre, is it Peyretou?

Olivier Corradi: Not too bad. Yeah. Well done.

Chris Adams: Okay, so for people who are listening, what we'll do is we'll share a link to some of the theory behind it.

He's actually got an online course. I think there is, there's a French school of business which does actually have some online resources to understand this kind of theory. So if you're Curious and you want to think about, okay, how does this work? Or if you'd like to see an actual triangle rather than have us describe it, follow the link and you'll see some of it there.

Okay, thanks for that, Olivier. Okay, so we've spoken a little bit about data, and you mentioned about data being in the open, Olivier, and I can actually confirm that when we spoke to Toby before, Toby is one, sorry, Tony is one of the colleagues at Literacy Maps. We did an interview with him around about November last year, actually, and he was talking all about this, Open Data Portal.

And back then we were like, "oh, sweet, there's all this data being published." And I'll be honest, you're a startup. I was like, "are they really going to publish the next year?" And then January came around and it actually did get published. I was like, "wow, this almost never happens." So I was really pleased to actually see a startup and a company follow through with making some of this data available because it's so, so, so useful and this is so hard to find otherwise.

I can speak as someone in a non profit who's been trying to find this data. It's so, so handy to have some of that available now. So yeah, thank you on that one. Okay, so the question, I'll leave some space because I think there was a response coming up there actually, Olivier.

Olivier Corradi: Oh, thank you so much for the shout out. You know, it's important for us as well to feel like what we're doing leads to direct impact and that we have folks that are demanding this data. And sometimes these feedback loops are not always present. So I appreciate you giving us the shout out.

Chris Adams: Yeah, so if anyone is listening, this is open data, so it's something that you're able to build on and we'll share a link to the actual website that makes it very clear how you can use this information. So if you're trying to build something and you're looking at historical stuff, it's totally there.

Have at it. Okay, so we spoke a little bit about carbon intensity at different parts of the world and how you need to think about it on an hourly basis rather than just an annual basis. And we might talk about why when you talk about green energy saying green energy with certificates that came from solar and then saying, using that to make usage at night be counted as green might be conceptually a little bit challenging, we might say.

So that's some of the stuff we spoke about. Now, the thing I want to ask a little bit about, and Íngrid, if I can hand this over to you. When you're working as an engineer and you start thinking about carbon intensity. It's when you use, say, APIs, you just see a single number that goes up and down.

And like, it's fun. And it's very easy to underestimate just how much work can go into this and all the complexities around this. Because as I understand it, it's more than just like, looking at what the power will look at looking at generation from a single plant. Íngrid, can I just give you a chance to actually talk about what goes into sharing some of these current and historical figures? Because I know there's some forecasting work, and we'll talk about that later, but we've just spoken about open data and some of the historical stuff, and some of the context there might be useful for people who are considering downloading some of this or messing around with it themselves.

Íngrid Munné Collado: Yeah, absolutely. And I would say that without this amazing work of collecting data, any forecast, like forecast would not be possible at Electricity Maps because we need this data to be able to produce our forecast. So let's take a look at how we collect data. This is currently done by one of our teams at Electricity Maps, the Grid Modeling and Methodology team.

And our work starts by first trying to get as much real-time data and historical data from, that is available publicly. And here we're talking about governmental institutions, transmission system operators, that for people without electrical engineering background, those are the folks that manage the electricity grid at high voltage, and that make sure that demand and production is actually matches at every single second.

So we try to collect this data and now we have data for 228 zones. And when we think about it, we might say, okay, we just collect CSVs and everything is standardized and nice, but the data is really messy. So we might get data from like in PDF files, in TXT files. We have sometimes, I can tell you a bit of an experience.

When I joined Electricity Maps, I had to build the parsers for Japan. And I'm originally from Spain, so I know a lot about electrical system in, in Spain, but when I had to dig into the Japanese electrical system, I didn't know that they have eight different organizations that collect data and each and single one of them is in a different format.

And sometimes we even had to do some image recognition to get the power of the nuclear power plants that they have in Japan. So data is very messy. It contains outliers. We have missing values, wrong values. Some production modes might be missing as well, so there's a lot of work that we have to do behind the scenes to make sure that we collect this data every hour or even in lower resolutions to make sure that we can use this data and process it.

So once we have this data in the raw format, then we process it to make sure that we don't have these outliers or missing values. And that we have a complete power breakdown. That means that if Spain, for example, has nuclear, gas, coal, and like in total eight production modes, that the data we get has eight production modes because otherwise the carbon intensity values that we might show on the app or on the API, they are not going to make any sense.

So once we have this done, then we can actually go into maybe one of the core pipelines we have at Electricity Maps. That is the flow tracing pipeline. And Tony did an amazing job in the previous episode where he explained how this works. But for those who don't know, the flow tracing pipeline makes sure that we are able to trace back the origin of electricity.

Because if I plug my laptop here in Denmark, the electricity that I'm consuming is not only the one that is being produced in Denmark, but that one that is being produced in Denmark all the exchanges that happen between Denmark and the neighboring countries. So, we have this pipeline that makes sure that we can take into account all the neighboring countries and what happens at every single hour of the day to make sure that we can know the exact mix at a given hour of the day.

That's actually when we get the origin of electricity, the power breakdown, and then we can translate this number into carbon intensity by using emission factors that we update recurrently and that this actually helps us understand one, what's the carbon footprint of one kilowatt hour that we consume at a given country.

So emission factors are different based on the source we use and based on the country we are at. And that's what you see on the map.

Chris Adams: Wow, okay, so that's, let me just run through some of that then. Just to make sure I'm understanding it. So you're essentially getting a bunch of data. You're having to do, clean some of it up. Like, that's quite common. And most of us might be used to like, working with maybe text or CSVs. But I think you said that you're essentially like doing OCR, like optical character recognition in some on like, gIFs or pictures rather than actually having to read an actual number. Okay, and then once you've got that, you've got an idea of what the generation might be, but then you then need to do a bit of, like, working out where data is, where energy is being traded across borders, essentially, because in some ways the grid does have all this stuff, you just can't look at the production, for example. Because, like, I mean, the UK has, like, new connectors to other countries all the time, and Germany uses loads and loads of France's nuclear power, for example.

So there's all the stuff like that, and then once you've got this idea that, okay, there's probably this much coming from these places, you then need to think about, okay, well, what is the carbon intensity of power from a coal fired power station, or a new coal fired power station versus an old one, and stuff like that.

So there's all that other depth as well. Okay, and that all goes into a single number.

Íngrid Munné Collado: Exactly.

Chris Adams: Alright, I am kind of, so, I see why people do this now, because when I've looked at this before, I've looked at numbers saying, "oh yeah, it's just like generation," but no, there is, generation and production are two totally different things, and you do need to take into account some of this if you want a meaningful number.

Íngrid Munné Collado: And if I can say something just to give you a rough number, a country like France, it has interconnectors like with eight different countries. So imagine if you only consider the production or generation in France without considering all the interconnectors around, you might get a completely different picture.

Chris Adams: Ah, okay, alright, thanks for providing extra context because, yeah, I can see how complicated this gets very quickly in that case. Alright, okay, one thing that you mentioned before was that there are all these complicated scrapers, and when I looked at Electricity Maps a few years ago, I was surprised by there's quite a lot of it which is open source, so like, don't believe me?

Look at the repo, for example. There's some of this out there so you can see just how messy the data might actually be or possibly contribute if there's a gap, right?

Íngrid Munné Collado: Yeah, actually, for example, when I had to work in the Japanese parsers, I got help from people in Japan. That they actually would point me to the right CSV file. Oh, and at some point the CSV changed the URL where it was stored. And it was not until someone, a contributor, helped me out and said, "Hey, check this link instead."

So we have, so all our parsers are open source and they are hosted on GitHub, on the contrib repo. And we are extremely happy about all the contributors that help us out, like be able to get this 228 zones that we have now, on the map.

Chris Adams: Okay, go yeah, Olivier, I was going to ask if you anything you wanted to add, because I believe you did a bit work on some of the academic underpinnings for some of this.

Olivier Corradi: I just wanted to add as well that if we tie it back a little bit to the triangle of inaction, what is happening here and why this is so exciting is that we're basically enabling some of the citizens to also act on climate change by being able to contribute with their unique expertise, which helps us.

There's no way Electricity Maps with, we're a bit more than 20 people now based in Copenhagen. There's no way we would have been able to cover the world if not for the help of all these wonderful contributors that have helped us all along, and it gives them also a way to contribute something meaningful where maybe before they didn't have that opportunity.

Chris Adams: Cool, and Olivier, we spoke a little bit about flow tracing, and I understand this is the you published a paper about this years and years ago, and that was one of the things to basically, the methodology that you're talking about, yes, there's some proprietary code, but the general approach that's being taken, it's in the public for people to understand, so they can challenge it and interrogate it and say, well, yeah, this is, I disagree with this thing and this is why I think this might need to be changed in the future, right?

Olivier Corradi: Absolutely and our philosophy has always been if there's something where we think we can move faster with the help of others, then let's open it up because then we can allow for contributions and so on. If it's something where we know that if we open it up, it's going to take us a lot of efforts to handle the contributions, then we don't open it up, and that's why some of the internal pipelines that Íngrid described are proprietary, because it's just faster for us to change a couple of things and not worry about what will happen if we open it up. But in general, we always try to be open, because we are trying to create a global consensus on how we account for things, so that can only be achieved through openness.

Chris Adams: Okay, you're singing from the same hymn sheet as us, like, we, the Green Software Foundation has a big thing about Open, the software carbon intensity metric is Open. If you want to pay to download it, you can buy it from the ISO for 63 Swiss francs. I don't know why you would, but that's available for people, and me, working at the Green Web Foundation, we use open as a lever, so we publish almost everything we can, either under open source or under open licenses. So, Íngrid, if I may, can I just come back to you, because we spoke a little bit about historical stuff, and you mentioned that forecasting is now a big thing, because the thing about renewable energy that we kind of alluded to before is that it changes over time. The sun goes up, sometimes the wind blows, storms move around, stuff like that.

So, can you just tell me a little bit about why this idea of forecasting is maybe more of a focus for you folks now and maybe explain a little bit about how, I guess, the sausage gets made and how that can be difficult.

Íngrid Munné Collado: Yeah, of course. So, as Olivier mentioned in the beginning, we want our data to be as actionable as possible. And now imagine that we are software developers and we run cloud jobs. And at the same time, we want to be aware of our carbon footprint. And we know that our cloud jobs might last five, six hours.

So, real-time data and historical data does not really help us achieve, like, be aware of what's the carbon footprint of our cloud job in the future, like, when is the right time to schedule this? And EV chargers might also think the same, like, when is the right time to charge? So, we saw that real-time and historical data would not help us achieve that.

Then we realized, okay, then we need to provide them with forecasts, and we know that we are providing a global API with data from all over the world for all bidding zones. Then, if we, let's go back to this software developer who wants to schedule a cloud job, because I think that's going to help the audience understand.

I can choose a data center in Sweden, but I can also choose a data center in Texas. So we can, we have the power of choosing which data center we want to run our cloud job. But at the same time, how do I know which one is the best? I don't have any idea. And at the same time, okay, but is it better to run my cloud job at 9 in the morning or 9 in the evening?

And then that's when we realized, okay, forecasts can actually solve that, but we need to provide it globally for all the zones in the world. So that's why we decided to focus on forecasting carbon intensity for the next 24 hours. That means, like, day-ahead. So we run the pipeline every hour and we provide forecast for the next 24 hours.

But then the next challenge came up. When we realized, "wait a second, is carbon intensity a metric that everybody can understand?" If I tell you that your cloud job used, I don't know, 200 grams of CO2, you don't, it's very difficult to relate. But if I tell you that if you schedule your cloud job at 9 am,

you're gonna run on 90 percent of renewable energy share. Instead of running 9 pm and then the renewable energy share is going to be 10%, it's very easy to understand and say, "oh, you know what, I'm going to do it at 9 in the morning because the renewable energy share is 90%." That's when we realized, okay, we can't just focus on carbon intensity forecasts, we need to do that with renewable energy forecasts and more specifically, wind and solar power forecasts.

Because that increases user engagement and the actionability of our forecasts.

Chris Adams: Ah, okay, that's quite a subtle change then, so, and I understand that because intuitively it's something that I just become so, kind of, you take it for granted, right? If someone is coming to this new, yes, explaining carbon intensity is conceptually quite complicated, but how much is running on clean energy is quite a bit easier to understand very quickly.

Íngrid Munné Collado: Exactly. if I can add on that, then when we said, let's start on renewable energy forecasts, it's a problem that has been not solved maybe because research evolves very fast, but it's a problem that has been laying around for years. I've worked on that field for many years. Because energy is traded on this day-ahead market, so people need this forecast to be able to trade energy in day-ahead markets or intra-day markets.

So when I started working at Electricity Maps on that field, I came from my previous job, and I came in, completely biased and thinking that this challenge would be easy to solve, because in my previous job, we had to do renewable energy forecast of specific assets. And then I would have the perfect setup for a machine learning engineer.

That means I knew the location of the wind turbines. I knew all the data regarding the wind turbines, like the blades, the installed capacity, if it was under maintenance or not. I also had access to multiple weather forecast data and I only had to build models for Denmark or the UK or Netherlands, so it was very focused, but when I joined Electricity Maps, the problem is completely different.

Here we focus on building a renewable energy forecast at country level or, bidding zone level without knowing the location of the assets, without knowing what's installed capacity, if the turbines are under maintenance or not, and that makes the problem very difficult because we know that renewable energy forecast is very linked to weather.

And if you don't know the exact location, then that's another challenge. So, I think in the grid forecasting, we did a really good job on finding a solution that generalizes well enough, and that allows us to generate this forecast for wind and solar for all zones in the world.

Chris Adams: Ah, okay, thanks for providing that extra context. So, I'm just going to check if I understand some of the terminology you used there. You said like a day-ahead market and an intraday market. So, so basically, as I understand it, if you maybe run a wind farm, for example, the day-ahead, you're going to say, "well, I reckon we can sell this many kilowatt hours or megawatt hours of power tomorrow," and that's what you'll make a bid in, and that's, there's consequences for either underbidding or overbidding for that kind of number, so that's why you'd care.

And the intraday is a bit like the kind of shorter term thing, so, you might make one big bit but then you might say there's a little bit of flexibility or you say well okay I, okay cool. And you mentioned this term bidding zone. Now bidding zone is a little bit like a country but it's not always a country.

So like America has all these different bidding zones because it has different grids and there's, that's the kind of, when you folks have mentioned the word zone that's kind of what you're referring to. It's not quite a country but it's more related to like, is there a kind of a unit of carbon intensity for a particular grid region, right?

Íngrid Munné Collado: Exactly. I mean, if we focus in Spain, for example, Spain, Portugal, France, Germany, a zone is the same as a country. But if we look at Sweden, it's split into four zones, into four bidding zones, and Norway into three. So if you check out our data, then you can compare between zone and country.

Chris Adams: Okay, and within a given country you can have radically different carbon intensity, and we might talk a little bit about some of that a little bit later then. Okay, cool.

Olivier Corradi: The dream is to get to street level granularity. And this is why flow tracing, by the way, is so important, because as you increase the resolution of what you're looking at, then obviously, if I'm looking at just a city, most of the electricity is actually produced outside of the city. And that's also why, by the way, the whole forecasting challenge just becomes massive.

Try to forecast how clean the electricity is going to be at every location on the planet. Obviously, you need really good renewable forecasts as well, and that's what civilization needs if it wants to rely significantly on these renewables that are intermittent.

Chris Adams: Wow, okay, I didn't realize street level was the dream for this, blimey. Okay, so we spoke a little bit about software and cloud jobs and stuff like that, but it's also worth just briefly touching, like, this is used outside of the cloud world. And I think one of you mentioned EVs as one of the examples here.

Could we just briefly touch on that? Because that might be one of the things which is concrete that lots of people might experience or might know someone who might have something which is, like, impacting them. Because yeah, EVs are becoming more popular now and it's probably one of the biggest new large uses of electricity in most people, in houses for example.

So yeah, Íngrid, maybe you could talk a little bit about that and then we can move on to some of the other questions.

Íngrid Munné Collado: Yeah, of course. So one of our clients is Monta. And we have a very great success story with them. Monta, for those who don't know them, is a global operating platform for EV. And one of the solutions is the smart charging feature, where they offer users to shift their charging according to the carbon intensity of the grid, the share of renewables, and that's by using our forecasts, or the price of the electricity grid.

And users are completely empowered to choose and to prioritize which signal they want to follow, if it's mostly price or low carbon or high share of renewables, and by doing that, those users took action in decarbonizing the grid. And the results are quite impressive because 70, 000 charging sessions were optimized for low carbon or high renewable share, and there was a 48 percent growth in user engagement, according to Monta, and that means that they optimized for low carbon charging, and in this process, 200 grams of CO2 were avoided for each charge on average.

So these are the numbers and this is the feedback that we're always willing to get because when we create, when we produce this forecast and we spend so much time building these forecast models is because we really want to know that people use our data and that they really use our data for this use cases.

So we were really happy to know that.

Chris Adams: Ah, thanks. Okay, so you mentioned one thing that I think was quite interesting. You mentioned, like, the cost being a thing that might change at different times of day and, broadly speaking, this is because, as I understand it, when energy is really when there's lots of green energy, renewable energy on the grid, it will be relatively cheap and somewhat green.

So, in the UK, for example, we have something like this Octopus Energy. I'm not in the UK, I'm in Germany, but I grew up in the UK. So, Octopus Energy is one company that's been doing a bunch of stuff like this about having agile and intelligent tariffs. So there's essentially a financial reason as well as a kind of basically an environmental reason for doing some of this.

And I think what I've heard in the UK, for example, I believe on an interview recently I heard just by doing some of this, essentially, when controlling some EVs, for example, I think the figure was something like 1.2 gigawatts of demand they had control over. Now that's basically the size of a nuclear power station in many cases, so that's like a significant amount of flexibility on the grid that would otherwise have to come from burning loads of fossil fuels.

Right? Okay, so maybe I can allow us to talk a little bit more about the cost thing because I know that when we talk about this, when we talk about green software, you can make an argument that yeah, you should do it because it's good for the planet, but there's also a real cost fact which comes into this that I think is actually growing and maybe this is something that I understand that you folks have been looking into as well as one of the ways to address more this triangle of inaction and align some of the incentives for more kind of grid complementary activity perhaps.

Íngrid Munné Collado: Yeah. So one of the issues we face is that we know that we want, we are implementing climate action and we want people to use our data for, in order to decarbonize the grid. But sometimes the entry barrier can be quite high when we just go there with, "hey, you have to save CO2." But sometimes it might be easier for users to understand that, "hey, if you look at the electricity prices, that you have also seen that they are not constant, you might be able to save money and CO2."

And that's very, that's a very good entry point as we mentioned in the Triangle of Inaction to increase user awareness because the main, for people it's very easy to understand price and how much they are going to pay at the end of the month and if they are going to save money and therefore it's also nice for us to get to them by I'm Price and then explain that, "hey, by doing that, you might also have an impact on CO2," but we have also a blog post where we mentioned that just optimizing for price doesn't mean that you're also saving CO2.

It's you need to implement some what we call co-optimization, where you want to either prioritize one or the other. And at the same time, maybe you might be able to save more CO2 if you optimize for higher renewable share, and at the same time, you can also save money by doing that. So that's why we think that price is a problem worth solving and that we also need to explore that area.

Chris Adams: Ah, I see. And if I understand it, and if we follow the kind of path from before, we spoke about, like, a lot of us might be used to just paying a single price for power, but the price might change depending on where you are geographically as well, and that has some implications too, like, this is one thing that I guess, this is probably the newer world we're moving into, in that, yes, there might be, like, night time tariffs, but it feels like there's a lot more dynamism, both temporally and spatially for some of this.

Íngrid Munné Collado: Absolutely. And we saw that when the war in Ukraine started, that as soon as we saw that there were less gas resources, prices skyrocketed. And for example, in Spain, where there was a price cap

The situation was solved also because Spain has other sources of getting natural gas. But countries like Denmark, Germany, they really struggled with that. And the prices really doubled for some months. And it's not only political conflicts. It's also availability of the power plants. I it was two weeks ago where Finland had some unexpected maintenance in one of the, of their, of the largest nuclear power plants.

And that cost their head prices to double. And also in Texas, we have seen extreme weather events that causes prices to change from

Chris Adams: More than double,

Íngrid Munné Collado: yeah, more than double from negative prices at some point because there, there's one area in Texas that has a lot of renewables and another area in Texas that doesn't rely on renewables and due to those extreme weather events, they have to turn off some of the power plants and they, then this affects the prices.

And something I want to mention, I'm an electrical engineering at heart. So I want to talk about the power of interconnectors, and we might think that just by increasing renewables, this is going to make prices to be cheaper, but the problem is not going to be solved, and it's not going to make prices cheaper if we don't have nice interconnectors that make these flows between countries possible.

That's why prices are just changing so much because there's so much happening and going on right now, both on installing new energy sources, weather events that we're seeing, unfortunately, due to climate change and also the lack of interconnections at the moment.

Chris Adams: Okay, so you mentioned two things that I think are interesting there. So one thing was this idea of, okay, the price can change massively. Like the Texas example, I think if we look at, like, the cost of power, right, it might be between 20 to maybe 60 US dollars per megawatt hour in Texas. For example, you're one, you mentioned, like, there's a bunch of wind in the panhandle in the kind of northwest, and then there's around Houston, there's loads and loads of demand where people use all the power, right?

And I think the figures I've heard were something in the region of negative two and a half thousand dollars at one point, and then 30 minutes drive away, the cost is three and a half thousand positive. So like, you got a almost four, five, thousand dollar swing in the pricing here. And one of the reasons is just because it's a bit like network connectivity.

You know, the pipe isn't big enough. And this is one thing that we have to kind of work around, essentially, thinking about this.

Íngrid Munné Collado: And the same issue is happening in Germany, and like, Germany doesn't have these price mechanisms that we have in the US, but in Germany, there are also, like, huge problems due to transmission capacity, because the, most of the solar power production is, takes place in one part of the country, while the demand is concentrated in the completely other opposite.

And they are now experiencing with curtailments and extreme negative prices because they don't have this transmission capacity. They also don't have storage capacity, and there are no market mechanisms that control how we increase this solar power production in the grid and how we just export this to other areas.

Chris Adams: Ah, okay. All right, thanks for the extra context. For people who are still with us, we'll share a link to the previous episode, because we spoke with chap Philipp Wiesner, who was building a bunch of this work to simulate these kind of grids to give an idea of what the pricing might actually be with different services.

And if you have data centers, how adding some storage might actually change the cost and the carbon of running various software services. So we'll add a link for that. Olivier, while you're here, I want to ask one question, if I may, about basically, optimising for carbon intensity, because that's what lots of engineers are kind of trained to do somewhat.

And I, inside the Green Software Foundation, there is a kind of standard called Software Carbon Intensity. It's the thing that you're supposed to, or that you might optimise for, essentially. And it basically lets you use two different ways of thinking about the carbon intensity of electricity.

And so one of these is called a average carbon intensity and another one is called marginal intensity and they are slightly different. And it can be quite counterintuitive when you're first coming to this because it can give you somewhat different answers or incentivize different kinds of actions.

For someone who's coming to this for the first time, can you provide a little bit of like background on how to navigate some of this and how to think about some of this? Because it's something that. I think a lot of people come to and they scratch their head quite a lot because it can be a bit confusing having two numbers which can suggest you do totally different things sometimes.

Olivier Corradi: Yeah, well, we might get into some of the weeds, so I'll try to keep the, sort of, the discussion a little bit high level so we don't get too technical. But I think the way that I'm trying to explain this, so, on the average side of things, the first thing that I will say, actually, is that the word average can be a little bit misleading, because it sounds like, like you're taking an average over a period of time, which you're not.

Actually, what we're doing here is computing what we call the flow trace signal. So it's like taking the production locally, looking at what's imported, and then concluding on what is the constitution of the electricity that I'm getting at. So it's a representation of all the power plants on the system, basically.

So that's what we'll refer to as average. And on the marginal side of things, the story goes that if you're plugging an electric vehicle to charge at a particular time, then it's not all the power plants in that system that will ramp up to give you that additional electricity. It's the one that's called the marginal.

And a loose way to define it is to say it's the cheapest power plant that still has capacity to ramp up, to produce more. So, in theory, that marginal concept makes a lot of sense, because we're saying that seems to reflect what is physically happening on the system. If you actually go a little bit more into the details, and that's where the differences start to pop up quite starkly.

Well, if you are plugging, for example, your iPhone on this, on, to charge right now. Then it's not this marginal power plant that will ramp up. In all likelihood, nothing will happen on the grid. It's just the frequency of the system that will change a little bit. But you're not shoveling a little bit more coal in the coal power plant to burn off a little bit more, right?

So, emission factor would be zero. Like, no impact on the grid, you could say. If you go the other way, and you say, now I plug, imagine a metaphorical plug on a data center that's using like 90 percent of the consumption in the grid, Then you can't have only that small power plant that has spare capacity, it's just not going to be enough to ramp up this data center.

You would need all the power plants on the grid to ramp up in this what if scenario where the data center didn't exist. And then the last example is, if you have an electric vehicle and you're plugging it in, then the electricity will be delivered instantaneously to you. And that's just not a change that a coal power plant or a gas turbine can react on.

And that starts to create some additional complexity when you think about, okay, but can this be predicted? Can the plugging in of my electric vehicle, could that have been predicted by the market? And if it's already predicted, then it's part of the business as usual scenario. It's not marginal anymore.

So when you actually try to go down to all the details, it becomes hyper complicated. And we've tried really hard to talk to all the power system engineers, the electrical engineers and the TSOs in Europe as well. And one of the most fruitful discussions we had was with 50 Hertz that concluded that they don't think you can actually reliably identify or verify what the marginal power plant is because depending on what market you're looking at, if it's day-ahead, intraday, real-time, depending on the magnitude of the changes, depending on all the interconnectivity, the marginal power plant is just a concept that philosophically makes sense, but from a data perspective, it's just hard to measure, and that's also, I believe, why most of the regulations recently on the hydrogen regulation in both the US and in Europe that is documenting what is it, what signal should you be using, whatwhen you want to prove that your hydrogen is clean, then they are settling on an average signal. So if you take a step back from all of this, you're having an argument that philosophically for me makes sense. Of course, you want to make sure that the short term impact of what you're doing is minimized.

When you start looking at the data, you have a signal that is difficult to audit. And we've been working on this for eight years now, six years, sorry, creating a marginal signal and trying to verify it. And I've just seen enough that it can be manipulated in many ways. And that's why it's a little bit difficult.

So to get back and conclude a little bit and to answer your first question, which is how would we navigate this thing? I think the advice we're generally giving is get both signals, plot the data next to each other, and depend on the use cases, ask yourself "Is user acceptance important?" Are you going to show this in an interface?

Because if you are going to show it in the dashboard of an electric vehicle, in a country like France, which is majority nuclear, or in Ontario, lots of decarbonized electricity already, it's going to be a tough sell to tell them, look, your EV is being charged on gas, which is on the margin. So this user acceptance is important.

The second piece is auditability. Are you thinking of being generally directionally correct? Or do you need an auditor to prove that the data is correct from a scope 2, scope 3 perspective? And these are typically things they're going to inform depending on if you're willing to have something that is philosophically more accurate, but in practice more wobbly or if you want to have something that's just simple to explain and sort of abides by the regulation.

Chris Adams: Ah, okay, all right, so if I try to kind of summarize it, it sounds like the marginal thing it's conceptually attractive and kind of fun and it might give me some and in very ways it's basically gives me this idea that I can make relatively small changes rather than some of the systemic changes that might be needed for some of this.

But from an audit, from an auditing point of view, because you're comparing some of this to essentially a counterfactual which might not exist, it's actually very difficult to say, "well, yeah, I definitely made this impact and if it weren't for me doing this these people wouldn't have switched this stuff on," for example.

So you kind of need to have a degree of kind of clairvoyant level of information for this to actually really check this. Okay, cool. Speaking of clairvoyant, I've just realized the reason I've used this term is it makes me think of, there is a paper by a research student, I think her name, Tammy, I'm so sorry if I pronounce her name incorrectly, Thanathorn Sukprasert, she wrote all about using the SCI and using these different signals and how they, when they agree and when they do not agree, and if you are curious about this as someone listening to this, we'll share a link to that paper because it's a really good paper, she's also doing another one which is all about, okay, what are the possible savings from carbon-aware computing?

And that is also a really fun paper to read, and maybe, Tammy, if you're free, we'd love to have you on the podcast to talk about some of that, because there's quite a lot of fun to read there. Okay, cool. Thank you for that, Olivier. I realize that was quite detailed, but it, I appreciate you talking about the fact that in other sectors, there's stuff we can look at, because, as I understand it, this whole shift towards clean or green hydrogen is somewhat comparable to data centers in the fact that you have a very concentrated amount of energy being drawn in one place. So, in the same way a data center might be tens or hundreds of megawatts, you might see something similar with, like, creating hydrogen.

Is that the idea behind some of that?

Olivier Corradi: Absolutely, and if if the way that I'm thinking about this if you really want to simplify it, if we take a step back, the opportunity we have ahead of us is large, abundant renewables that are going to be the cheapest and the fastest way for us to expand the system. I mean, nuclear is great as well, and hydro and so on, but it's just, it takes more time, and it's a little bit more expensive when you put it in directly.

And so, if we put all this renewable in the system, we better well make sure that every flexible appliance out there is aligning their consumption to the time at which the renewables are creating that electricity, because else we're just hindering their deployment. You know, it's less batteries that we need.

And I think that's generally also the thinking behind the hydrogen. We want to make sure we're electrolyzing the hydrogen at the times where all these abundant renewables are producing electricity. And so that's the simplest heuristic and the fastest way for me to explain the systemic change we're undergoing and also why we're focusing on these renewable power forecasts.

There's a lot of value there. And by the way, why they also typically align with the price of electricity.

Chris Adams: Ah, okay, thank you. I do hope we still have some people with us, because that was a bit of a deep dive. But as sometimes when we're coming to new fields, working in software engineering, you do need to kind of engage with the details sometimes. Folks, I think we're coming up to the time that we had allocated for this.

And this has been loads and loads of fun. I've really enjoyed this. If people do want to know more about what either of you are doing, can I just give you a bit of space to talk about, like, Follow me on either Twitter, LinkedIn, Mastodon, whatever, like yourselves personally. And then if there's anything you would direct people's attention to, yeah please do, and then I think we'll wrap up actually, so maybe Íngrid if I hand over to you and then you Olivier, we'll wrap up with you okay?

Íngrid Munné Collado: Absolutely, so if people want to know what I do, they can check my LinkedIn, and it's Íngrid Munne, M U N N E, and I'm also on X or Twitter with the same name. So looking forward to that.

Chris Adams: Thank you, Íngrid. And Olivier, for you.

Olivier Corradi: Likewise, like Íngrid, you can reach me on LinkedIn and Twitter. If you search for my name, you'll find me. And I think in terms of resources to watch, we try to publish blog posts that are going deep into the topic, that are thoughtful. We don't publish a lot, but when we do, it's like We, we at least try to have serious research there, so check out our website, check out our blog, and we have a couple of guides on carbon accounting as well if you want to go deeper on the topic, and a few videos on YouTube if you want to nerd out more on some of the things we just discussed.

Chris Adams: Okay, we'll add a few links for all of those and the thing I'll also share is that in the Green Software Foundation, there are ongoing discussions in the standards working groups to discuss all this stuff. So you can see all the kind of back and forth around this, so if you do want to engage with this and possibly join to actually take part in that conversation, there is that available.

So you can see what discussions have come before and how people arrive at deciding which carbon signal to be following. Alright, I think that takes us to our time. Folks, I really enjoyed this trip, and we'll make sure that everything, or as many things as we remember, are in the show notes for people who want to continue this quest to learn more about building more sustainable software. Thanks a lot, folks, and have a lovely time in Denmark. Ta ra!

Íngrid Munné Collado: Thank you. Bye!

Olivier Corradi: Bye-bye.

Chris Adams: Hey everyone, thanks for listening! Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode!

View Details

Host Chris Adams is joined by Asim Hussain to dive into The Week in Green Software, exploring the environmental impacts of artificial intelligence and how the growing adoption of AI technology affects carbon emissions, as well as the growing complexities in the measurement and reduction of these. They discuss a primer on AI's direct environmental footprint, regulatory trends in Europe and the US, and the complexities surrounding the renewable energy credits tech companies use to offset emissions. The conversation touches on real-time cloud data initiatives, carbon accounting in AI, and the future challenges of balancing sustainability with technological innovation.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Asim Hussain: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* The Environmental Impacts of AI -- Primer | Hugging Face[03:12] * How Tech Companies Are Obscuring AI's Real Carbon Footprint | Bloomberg [22:25] * AI analysed 1,500 policies to cut emissions. These ones worked | Nature [32:48]

Events:* Green IO Conference 2024 London Dates and City Locations - Sustainable Tech Partner for Green IT Service Providers

Resources:* Does the EU AI Act really call for tracking inference as well as training in AI models? | Chris Adams [12:21] * Simon Willison on openai [14:15] * EnergyStarAI (AI Energy Star Project) | Hugging Face [16:12] * Meta-Llama-3.1-8B-Instruct · Hugging Face [21:28] * Jevons paradox and greening software—why increasing efficiency makes sense | ASIM.DEV [21:51] * Olivier Corradi [27:43] * Real-Time Cloud | GSF [28:41] * GitHub - Green-Software-Foundation/real-time-cloud * Reviewing the evidence we accept for Green hosting verification | Green Web Foundation [31:06] * The Week in Green Software: Modeling Carbon Aware Software | TWiGS with Iegor Riepin [37:18]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
Asim Hussain: Three, four years ago, everybody treated all carbon offsets the same. They didn't realize there was nuance between them. Now that's changed. Everybody needs to now pay attention to the same thing in terms of renewable energy. If you do not pay attention to the fact that there is a lot of variability in a lot of this stuff, it's all going to get tarnished with the same brush in the future and any renewable energy claim is not going to be trusted.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello, and welcome to the Week in Green Software, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. This is our news roundup show in the Green Software Foundation podcast. So we aren't doing a domain expert news roundup. Deep dive where we go into a deep narrow subject, but rather we're taking a more broader view.

So we'll try to add some context and commentary to the stories that have been shared with us that we discuss with our guests. With me today is my friend, colleague and mushroom enthusiast Asim Hussain of the Green Software Foundation. Asim, it's really good to see you again. How are your holidays?

Asim Hussain: Yeah, it's been quite a long time off and just gently dipping my toes back into the swing of things. Glad to be on the show. It's a nice gentle introduction back into the world of green software. So, glad to be here again, Chris. Asim Hussain, I'm the executive director of the Green Software Foundation.

And yeah, I spend my day probably similar to you thinking about how to advocate for green software. What do we need? What do we want? What are the questions that need to be answered and what are the levers that we need to pull to get action taken in this space?

Chris Adams: Reduce the environmental impact of digital services. Yeah. Okay, cool. Thanks. I should introduce myself as well. Hello, folks. My name is Chris Adams. I am the executive director of the Green Web Foundation. That's a smaller, a different organization. We are a Dutch non profit focused around reaching a fossil free internet by 2030.

And we do that using open as a lever. So we do loads and loads of stuff with open source, open culture, and things like that. As a quick reminder, we're going to share all the stories that we have and any projects or things that come up, we'll add to the show notes. So if you want to continue your quest to learn more about green software and how to reduce the environmental impact of digital services yourself, just look at podcast.greensoftware.foundation to see this. If you're looking in Spotify or some of the other podcast tools, you might not be able to see the links. So please do go to the website to see the show notes and you will be rewarded with diligently prepared links and helpful notes, and a transcript as well.

Alright then, so, I guess, Asim, I've introduced our News Roundup format, we kind of know what we're going to do, we've done this a few times, I assume you're sitting comfortably, shall we begin?

Asim Hussain: Yeah. Yes. Yeah. Let's go for it.

Chris Adams: Alright, okay, so the first story I see here is actually a post from, from Sasha Luccioni, Bruna Trevelin, and Margaret Mitchell, Hugging Face the Environmental Impacts of AI - A Primer.

So, this is one thing we had shared, and, Asim, I'm going to ask you, you've had a chance to look at this, what made you think this was actually worth discussing, and what would you draw people's attention to if they'd heard about this? And how would you, like, persuade people this is worth a read, for example?

Asim Hussain: Well, I suppose if you're new to the space and I think there's a lot of people out there who, for whom are kind of surprised to find out that AI has an environmental impact. So this is, I mean, A lot of this stuff, obviously we've been talking about different components of it over the last couple of years, but I think it's a really good, it's actually a great summary of the different components of what makes environmental impacts of software.

It's also got information there about what are some of the legislation coming down the pipeline? What are the, some of the actions that you can do? And some some things there. So I think it's a really good kind of primer for people. I think it's the title, is the title Primer? It

Chris Adams: Yes,

Asim Hussain: Yeah. So it does what it says on the tin. And I think it's probably could do as a really great introductory piece of information. It's got some great links there as well.

Chris Adams: Yeah, the thing that it might be worth just focusing on briefly, or one thing that leapt out at me when I looked at this is that it talks about the direct environmental impacts of AI specifically. So rather than talking about AI for good, or like "isn't it great that you could use AI to, say, make it easier to deploy renewable energy, or do this, or do that?" Right?

They're talking about, "no, there's an environmental impact that you still need to address regardless of whether you use something for good or for bad," and it seems to be focusing primarily on that kind of stuff. So as a responsible engineer, these are the things to think about. These are the kind of, what you might call an impact criteria, like there's carbon emissions, there's water, there's other things like that.

And generally this is from one of the kind of most trusted hands-on group who are like at the coalface for all this stuff. I mean, maybe, is coalface the correct term?

Asim Hussain: Yeah. I always use that term as well. And then I'm like, actually, that's a

Chris Adams: Maybe if you're in, maybe if you're in US AWS East, it's coalface and then if it's on AWS west, it's hydro face.

I dunno.

Asim Hussain: I use coalface and then if I don't, then I sometimes use front lines and I'm like, "actually, that's not a good term as well." We need a term which doesn't have a war Metaphor

Chris Adams: or industrial revolution connotations

Asim Hussain: Metaphor.

But anyway, it's at the cutting edge!

Chris Adams: Yes.

Asim Hussain: Cutting edge. There you go.

Chris Adams: Okay. That, that, that will do for me. Alright then. Okay. That's the first thing. I think on a following from this, when I was reading this. I quite like that it actually touched on some of the regulatory drivers that you have, because it's very common for people to talk about the AI Act, because that's probably the first piece of legislation, but it also calls out stuff taking place in Spain, and taking place in the US, and it shows that there's a kind of growing, I guess, regulatory trend to basically say, "well, If you're going to have this piece of technology in society, then we need to have a data informed discussion about what impacts it might actually have."

So we can talk about, okay, where is it responsible to deploy this? But also just like, okay, how do we actually mitigate this? Because, I don't know, it seemed like cars are useful. And the fact that cars are useful doesn't mean that we don't talk about seatbelts, right? You still have to talk about them being safer, regardless of how useful they are, basically.

So it's really nice to have a trusted organization sharing some information like this in a relatively roundabout in a, in my view, quite concise fashion. But if you look at the set of footnotes, wow, there's so much stuff that you can dive into if you wanted to kind of go down that rabbit hole, basically.

Asim Hussain: Yeah it's a very well researched, almost a state of the art paper. And also say like, I think it's also good to know, because people don't, yes, there's regulation coming down the pipeline, and some of that stuff is more mature than other regulation. But I think when you're working inside large enterprise organizations, this is the kind of stuff that gets people to pay attention.

You can be talking for ages about, "hey, look, there's the carbon impact, it's having a... we should be looking at our AI usage" and sometimes that can land and sometimes that can't, but a regulation or the threat of a future regulation is something that I've seen personally open a lot of doors. It doesn't kind of complete the internal sale of, "we need to invest in mitigating the impacts of our AI use." But it's certainly, I've seen it kind of open up a lot more doors because regulation is something that a lot of organizations pay significant attention to, and it's also something that they will, Invest time before the regulation comes out to look at it and put effort into it.

So I, I look at that, right. And it's kind of, it's great to see those regulations that I wasn't aware of. So I'll be obviously using this as it's a great primer for me as well, but this is a really good way of capturing people's attention. So then you can have that more refined conversation about, well, how are you using your AI?

Let's have a conversation about it. How is it, how is future regulation going to affect you? So it's a really good way of opening that door. And if you're inside an organization and you are a little bit concerned about the consumption of AI that you're having, I think for me personally, like pointing out the regulation that's coming down the pipeline does open a lot of doors, enables some conversations with leaders.

Chris Adams: This actually might be a kind of somewhat appropriate time to mention some of the kind of policy stuff we're doing, because I, so in addition to doing the podcast here, I help co-chair the policy working group. And we've, I think we've, we, we're likely to be getting quite a I'm going to put a policy radar out to see precisely this kind of stuff coming up.

Because, yeah, if you didn't know, I mean, okay, today is the 6th of September, and, you've seen this whole energy efficiency directive thing in Europe, right? So, in nine days time, every datacenter that uses more than 500 kilowatts of power draw has to start reporting and posting in public all of their absolute energy use, absolute water use, the amount of energy coming from renewable energy, how much of it comes from the kind of credits that you might buy which are unbundled, how much is coming from a power purchase agreement, so the kind of green energy that you've purchased directly.

There's all this new stuff. There are some caveats around this. So not every single organization will have to, we'll probably publish, but we basically have a regulation that's saying, "look, this has to happen now in nine days at the time of this recording. So when this goes out, it probably will have already happened.

And like this gives you an idea that if you didn't know this is happening, then you probably will, we do need to know this because this is written into the law in lots and lots of countries now. Well, all across Europe, for example, and I suspect this is the kind of thing we might see in other parts of the world because when you look at the figures and look at the data that people are currently basing policy on, it's really hard to figure out what the environmental impact of, say, data centers might be or what the growth is going to be.

And if you want to plan for a grid or plan for hitting some climate targets, this is the kind of stuff you need to actually be knowing about.

Asim Hussain: But it's also useful because we've been having these conversations for a while about, I think we spoke on the podcast a couple of times in the past and when we were developing the SCI specification, it came up a lot like do you include the data? How much of the data center do you include? But the biggest problem was, is that you don't know.

If you decided to put into the specification, you've got to include certain, the concrete or whatever it is that goes into data center. If that data is not public, then what's the point of putting into specification? That's why these regulations, that specific regulation is so interesting. I'm interested to see what actually happens in nine days time and the quality of data that comes out.

The conversations I've had in the past, because when this first started being discussed, I was chatting to a lot of, not data center operators, but people that worked with data center operators. And obviously it kicked up a storm and everybody's like, well, I need this data. How do I get this data?

What is the minimum level of information I can provide to like meet? And that's where it gets really interesting for me. What is the minimum level of information I need to provide to meet the regulation? And I think in nine days time, we're going to find out what is the minimum level of information that people have figured out that they

Chris Adams: Yeah, they can get away with,

Asim Hussain: that they can get away with? Because when I had that conversations, I don't know where it landed now, to be honest with you, but they were like, is it at the building level? Is it at the rack level? You know, it's, and it was like, it's at the building level is where I was left at. So I think the more and more this regulation comes along and it kind of surfaces this data to us, then we can then use that data to make more informed choices, hopefully not from a consumer level.

I think it should be from a, not from an end user level, but from the people who use data centers and make make different choices.

Chris Adams: I think you're right. Okay, what we'll do, we'll share some, a couple of links to this, because this is something we've discussed in a few places, there's one or two working groups where this has come up, in particular, because there's also, on the, just, just before we move on from this, there's a whole, there's a current kind of, in my view, an interesting discussion going on about, okay, with this, in Europe at least, with this AI act, yes, it says that you need to talk, you need to disclose the training data, the energy used for training a model, right?

But it's not totally clear if you need to also track the inference, right? So if you think about the training part, and I've shared a link to a blog post where I've basically highlighted the bits of the law that make me think that you might need to track inference, or at least disclose some information about likely inference because you can think of like the training part as like the energy going into making a car and then the inference figures as a bit like the car's mile per gallon for that model, for example. And well yeah, well it's not totally clear yet and we've seen the law passed and we'll figure out yeah.

Asim Hussain: Cause I assume the only, I'll be honest with you. I assumed included inference. The only time I did it was when I just like read your article and I was like, oh, hang on. That's and that's where these things get very interesting to me. I mean when I was in working in enterprise like organizations and I've one of the things that was always interesting to me was whenever I asked questions or got meetings together, like "let's talk about, we've got some questions about the, how do we calculate this figure to meet with this specification?" And there's almost always legal got involved and lawyers got involved. And I was always kind of, I'm like, "I don't need to speak to a lawyer. I need to speak to an engineer."

Why am I speaking to a lawyer? Because it's all about, "let me read this text. What can we interpret from this text? What do we need to give?" So I assume just because everybody just, we know inference is where most of the emissions are these days, I just assumed it was that, but you've now actually read the text and gone, the text has, is interpretable.

Chris Adams: Well, yeah, because you think about like when this initiative was written ages ago, like a few years ago, it's gone through this massive kind of gestation process, right? And a couple of years ago, when we hadn't really got to this point where AI is being deployed in the same way, like, was it November 2023?

That was like 100 million users. OpenAI had gone from zero to 100 million users in five months. And maybe last week? We should share a link to Simon Willison's blog post because he wrote about this quite eloquently. He's like, well, OpenAI have just mentioned that they're now at 200 million weekly users. So that's like doubled in a single year. So we've gone from, so inference is now a significant part of the story in a way that it wasn't previously, basically. So it may be that the law, when it was written two years ago and began that process through it, it might not have been such a concern. And this is the thing that we're, this is why it seems a bit unclear, and I think we'll probably end up with a test case that will set a precedent for people to figure out what they should be sharing or what you might need to share if you're building new foundational models in future.

Asim Hussain: I mean, I can tell you that, that preChatGPT kind of announcing, it was very well known that inference was significant, as in way more than training for any, like, I can't reveal too much, but you know, it was known very much that that was the case and a lot of effort had been put into mitigating, not from a carbon emissions perspective, just from a cost and energy, but just all of that stuff.

So it's kind of known, it might not have been in the zeitgeist, it might not have been in the kind of the public discourse because it's so much easier to talk about this big training runner. Maybe there's just more public data about that because inference in a way, if you think about it, is going to be pretty private.

Because that's inference is basically telling everybody the business end of your where you're making money from, and they'll probably keep that pretty private. So yeah, maybe it just wasn't well known, but it was true and well known, I think, to anybody in the kind of the AI space that inference was a pretty big deal prior to this.

But yeah, it makes sense. Yeah, these acts take a long time. So yeah, a couple of years ago, all we were talking about was training. It was a good, it was a good headline to discuss. Yeah.

Chris Adams: Useful insight from the inside tracker team, alright. So there's one thing you mentioned actually, we're just on the subject of inference. There is this, in my view, really interesting project right now, EnergyStarAI, which is a project which is, you see a few names associated with, so, Sasha Luccioni, Sara Hooker, Régis Pierrard, Emma Strubel, Yacine Jernite, I think, Carole-Jean Wu, and one of our own at the Green Software Foundation, Boris Gamazaychikov.

He's at Salesforce and he's been one of the people who's writing publicly about a bunch of this stuff and also about like, quite, the small models as well as large models. And it's, I was really pleased to see his name actually. So. Hi Boris, if you're listening to this. This is a really good story to look at, because this essentially is talking about inference and saying, "well, let's find ways to make this visible for people" two years later now, basically, and say, "well, let's see if we can find ways to introduce some of the incentives to go for more efficient inference," the same way we've done with Energy Star in other kind of industries, for example.

Asim Hussain: There's really interesting, I'll try and get her on the podcast, actually, she's from IBM, her name's slipping me, so I'm not as good as names with you, you can just rattle them off, but I'll make sure to put it in. Because yeah, there's Energy Star for AI, but we're also, there's conversations inside the foundation as well now, kind of looking at SCI and how do you apply SCI to AI and kind of, there's a lot of overlap with a lot of this work as well.

But what's interesting is there's this real question about what to do when it comes to inference and training. Like if you were to report that. How do you report that for a model? And the point that was raised, and I thought it was so, because I never thought of it before, which is, if you've got a foundational model, you've done the training, you've done a big training run for a foundational model, and you're now then running inference on that, when you report, let's say, I don't know how any, I think Energy Star is just going to be like a good bad kind of label, where SCI is more like a score, like a carbon per prompt or something like that.

How do you apportion the training into the, do you include the training every time you call it? Because if you do, there's a really interesting thing that happens, which is these foundational models, like if you're using an open source model and you just, that costs 10 000 to run. Do you include that in your AI solution and then just say like, "Oh, I'm three, three grammars per prompt?"

Then somebody else uses that foundational model. Do you then divide that by two and say, well, now you're, you

Chris Adams: talking about double counting kind of question, right?

Asim Hussain: And then like, if that is how the measurement eventually lands, then if you're an unscrupulous organization, all that you would do is try and get as many people to use this foundational model as possible to then dilute your numbers.

And so I think one of the, one of my little bugbears, and it comes up quite often, is the assumption that something that works in the physical realm will work in the digital realm. And one of the things I try and educate people as much as possible is that stop trying to take something that has worked in the physical realm and apply it to digital because there's so many ways it just doesn't work.

If you're thinking about training like a scope 3 embodied carbon physical device thing. You can't divide a chip in two and I give you half and you, it's like, that chip's yours, but you can do that in the digital realm. So there's this whole supply chain accounting aspects of digital emissions, which, it just needs to be thought of differently in the world that we're in. And if you don't think about it differently, you can then have, I call them unintended, we used to call them gaming, like when people were developing the SCI, like one of the conversations we'd have on the calls is, how is somebody going to game?

How is somebody going to take SCI,

Chris Adams: Carbon Intensity here, right? Yeah, okay.

Asim Hussain: how is somebody going to game the side? That's kind of a lot of the conversations we had at the start. Cause obviously everybody was like, we want to make sure if we develop a standard, people aren't going to then

Chris Adams: Abuse it,

Asim Hussain: it. And therefore the standard has no respect in the world.

And so like a lot of how, like a lot of how I kind of work with the standards projects here is I'm a bit of an annoying devil's advocate. I love it actually because I kind of walk in and go "here are 10 ways I can hack this standard to present a better score without actually doing anything." And so I think that's some of the things we need to think of as we think of SCI for AI, as you think of Energy Star, as you think of these other things is yes, there's this happy path that everybody's a good actor,

it will work and it will give you the right signal, but we need to think about the non-happy part, where people might not even necessarily be bad actors. It's just death by a thousand cuts. You're working in an organization, you've got a deadline, you've got a bonus you have to meet, there's a customer that you're going to have to get or you lose your business.

And so you're just death by a thousand cuts. So yeah, we have to be very careful as we explore like SCI for AI and Energy Star and anything really in this space, which is talking about measuring emissions. Because if you don't think through those unintended consequences, that's a problem. And that's one of the ones I have is like, is if you're including training, how do you apportion that?

You might not actually want to include training. You might actually want a separate. You actually, you might actually only want to measure the inference, because that gives a truer figure.

Chris Adams: So to cap this off, I'm going to, as we move to the next story, I'm going to link, share two links which might be useful for this. So the first is the link to the Meta Llama 3.1 8B, their model card. They literally say "the methodology used to determine energy use and greenhouse gas emissions can be found here."

They've linked to it and they said "since Meta is openly releasing these models, the training energy use and greenhouse gas emissions will not be incurred by others." So they're basically saying you don't need to count that part. That gives an example. We'll share a link to that. The other thing we'll share a link to for the show notes is actually the Asim, for this software, carbon, yeah, this is

Asim Hussain: Yeah, this is my unintended.

Chris Adams: This is a good example because this is where you've basically said, this is me, like, red teaming this approach, and these are the ways I can basically, in bad faith, try and engage with this example.

And this will probably be useful for people who are looking at this, to get an idea of, like, how some of these standards or some of these conventions are being developed. Alright, shall we move to the next story? Because it kind of does relate a little bit to, basically, tweaking numbers to present a view of the world, basically.

So this story is now, how tech companies are obscuring AI's real carbon footprint. This is a story from Bloomberg, I believe. Asim, do you want to introduce this one?

Asim Hussain: So yeah, so I thought, well, the reason this kind of popped up on my radar was, I forgot what I posted on LinkedIn, but I was posting, I started posting a bunch of information on LinkedIn about the use of, the use of RECs and the effectively like kind of renewable claims that organization makes and how it's in a really frustrating way, it actually puts us in what we're doing in kind of competition with this very important energy transition, because the argument I'm making is, look, you can either do two things and then we'll talk about AI.

Let's keep it to AI. You can either make your AI model more efficient, so it consumes less energy. Or, you can do absolutely nothing, and just buy offsets, energy offsets, RECs, whatever you want to call them, to mitigate, theoretically, your energy offsets, your energy consumption. And that's kind of like being this "Are we friends?

Are we not friends?" How do we like, we want to support the energy transition, but at the same time, like we really want to advocate for more energy efficiency. So, and I think one of the things we've spoken about is that there's, when you do make these renewable energy claims, like one of the things that you do with all types of offsets to kind of avoid a greenwashing claim, you have to have that additionality component to your offset, which for the audience means that how do you, if I'm saying this thing is offsetting your emissions.

What is it a litmus test to say that is a true statement and is basically, are you actually adding? So for a renewable energy credit, it's like, if you weren't about this renewable energy, would that thing have happened?

Chris Adams: So you're talking about the counterfactual here, right? So you're trying to compare something against. This is, you see a load of this in the hydrogen circle, in the hydrogen, in the world of hydrogen, because Just like datacenters, hydrogen electrolysis, like the electrolyzers use loads and loads of energy, right, and one way that you can do that is just by plugging them into the grid, right, and there's various people doing various things to say, well, I'm just going to buy a bunch of, say, renewable energy credits, right, and that's going to make that count as green, and there's, that's, in some ways, that's kind of somewhat problematic because, essentially,

Asim Hussain: coal to make hydrogen.

Chris Adams: Yeah, that's not exactly what all, you're, in many cases, you're a, you're burning coal to make hydrogen, so the actual net, it's a net loss in climate terms. But also, the, there's been a big fight in the kind of hydrogen world of, to have like this notion of three pillars. Where you basically, if you're going to have something, if you're going to count something as green hydrogen, then you need to be talking about new infrastructure being added to the grid to provide that new supply.

You can't just use, you can't just take from the existing stock of green supply and then count that as green. And this is one of the things that we've seen, like, I don't, Amazon made the news, I think a few weeks, a while, because they basically acquired a data center from a company called Talon, I believe, where they're right next to a nuclear power station, right?

So this, that you, there are some people saying, "oh, this is great, isn't it good that Amazon's using a bunch of clean power," but then you've got to think about, well, okay, who was that clean power going to before? Was it going to the grid? Like, there's a whole discussion there about this. Yeah, so there's a whole set of things to be talking about and this is why this is such a kind of fraught area, basically.

Asim Hussain: I mean, but I think the way to bring it back to something that people understand is when we talk about carbon offsets, I think now it's more understood that it's kind of like you, you have carbon removal offset. So you can plant a tree. Right? And then you planted the tree, that tree will grow, and there's issues there.

That tree will grow and also suck carbon from the atmosphere. And you can say that's a carbon credit of planting a tree. Or, there's carbon avoidance offsets. And there's many various, and there's actually very good variants of carbon avoidance offsets. But there is a variant of a carbon avoidance offset where I've got a tree.

And you pay me not to cut it down. And so where's the additionality? If I'm actually planting a tree, it's happening. I'm planting a tree. I'm adding additional kind of capacity in carbon removal. And in the renewable energy markets it's exactly the same. You can have renewable energy. Which if you buy means a renewable power plant is going to get built and you can have renewable energy which is just kind of sold and if you buy it or you don't buy it there's no change nothing's going to happen there's no more new renewable plants going to get built. Only one of them has that additionality component and so, therefore, only one of them should really be used in any kind of renewable energy claims.

But both of them are allowed in terms of renewable energy claims. So in terms of what this article is talking about, when they're saying "tech companies obscuring AI's real carbon footprint," they're actually talking about companies using what's called those unbundled RECs, which is those RECs which do not have that additionality component.

And then use buying them and then saying, "well, that's mitigating my environmental impact." And what the article is talking about is really, you should be looking at higher quality, Renewable Energy Credits, ones with more additionality components to it. And I think that's really interesting. There's actually also really, Olivier Corradi from, don't know if I'm pronouncing the second name correctly.

Electricity maps. Yeah, he, when I was talking about, he shared a really interesting article he'd written a year ago, which I thought was interesting as well. I'll share that here if you've got it. Yeah. He's actually advocating for like a more nuanced approach to looking at renewable energy in that there's additionality, then there's additionality, and then there's additionality.

There's like different levels of additionality. There's like, "this definitely 100 percent would never have been built unless you bought this renewable energy credit." And there's other ones like, "we may not have been able to build it, but we had some funding from here and there." So there's kind of different levels of additionality here as well, which I thought was really interesting also.

I'd never thought of additionality more than just a binary yes/no. And he was saying it's actually more of a score for a renewable energy credit. But

Chris Adams: Yeah, there's totally a continuum there. So the thing I might share for people who are looking for something actionable to work with here is basically the numbers that you often see reported by technology firms. There's all this, there's all this nuance hidden behind it. And there's one project called the Real-Time Cloud Project inside the Green Software Foundation, which essentially is a data set of the largest three providers.

So that's Amazon, Google, and Microsoft. And they've got the figures shown in both the kind of location-based figure, which is the closest thing you might think to, like, the physical location, the physical impact on the ground. They also talk about some of the market-based figures, which is what lots of firms like to use, like market-based on an annual basis.

But they also provide a few other details and a few other ways of talking about it, because some firms are now talking about hourly, basically hourly green energy versus annual green energy, with the idea being that you, it's a way to try and avoid making claims about saying, "I'm running a data center at night with certificates coming from a solar farm." This is inherently a little bit silly. So they address that stuff. So there's a, there's now, I think it's in the final stage of what's referred to as consistency review, where every member in the GSF is able to just say, "Hey, I object to this, or I'm not sure about this." And then, yeah, there'll be an open data data set for every single region from the three largest providers, which make up more than two thirds of the entire cloud market.

So you have some meaningful numbers that have come from the actual big providers themselves that you can actually, that we can work with.

Asim Hussain: And I think, like, I think basically my, I think the point I'm generally raising out, out there with another kind of, one of the reasons this article was very interesting to me, and especially the work that Realtime Cloud is actually interesting. Three, four years ago, everybody treated all carbon offsets the same.

They didn't realize there was nuance between them. Now that's changed. Everybody needs to now pay attention to the same thing in terms of renewable energy. If you do not pay attention to the fact that there is a lot of variability in a lot of this stuff, it's all going to get tarnished with the same brush in the future and any renewable energy claim is not going to be trusted.

So I was, I'm kind of a guiding and advising organizations to pay very close attention to kind of the type of renewable energy that you're buying. And be aware that because of podcasts like ourselves, there's generally, it's a Bloomberg article talking about this right now. It is now becoming very aware in the minds of a lot of people who care about this space, who listen to our podcasts, who are paying attention, that there is nuance here.

They're paying attention. And so as an organization, you need to pay attention to this as well.

Chris Adams: Cool. Asim, I'm just going to add this one thing because I realised I should have mentioned this. So I work in an organisation where we do track some of this stuff. We track the transition of the internet away from fossil fuels to greener energy. And, I've shared a link for the show notes. Because we're basically reviewing our own evidence that we accept for green hosting.

And we've linked to a couple of papers. And specific reports, which dive into this a bit more, which have kind of also prompted us to start looking at this. So, organizations like the Science Based Targets Initiative, we mentioned there. We talk about some of the other things that we, some of the nuances around RECs.

And yeah, this is, this will be something we'll be doing. So we're going to be essentially figuring out how to do this ourselves in the open over the next few months. So, Yeah, I guess it applies to small firms as well as large firms.

Asim Hussain: Yeah, yes, absolutely.

Chris Adams: All right, should we move to the next story? So, this is a story.

Researchers analysed 1 500 climate policies to find what works. And these are the lessons for Australia. I think this is the link you shared with me, Asim. There's a very kind of Australian centric kind of point of view, which, as someone born in a small mining town in Australia called Prospect, because what else would you name a mining town other than Prospect, because it's full... you? Yeah,

Asim Hussain: I didn't know you were born in Australia.

Chris Adams: Ah yeah, born in Australia, small mining town.

Yeah, I was literally born in a mining town called Prospect, and it's near One Tree Hill. Can you guess how many trees are on that hill? And it's next to Dry Creek. Can you guess the conditions of that river? Yeah, it's descriptive rather than creative, is the term I've heard people in Germany who do similar things talk about, actually.

Okay, so you shared this story, maybe you can introduce this one here, because I think it's quite relevant in this discussion, what we were just talking about in the previous two stories, actually.

Asim Hussain: Hmm. So I think it was just really interesting. It was an analysis of like 1500 climate policies and just really looking at what worked and what didn't work. And I thought it was interesting because we spoke a lot about, we've spoken a lot about things like carbon levies and things like that on this podcast.

But what I found interesting about this article was they, again, brought nuance to the discussion and saying, "actually there's different, different policies seem to work for different types of organizations and also combinations of policies seem to work better than individual policies." So a couple of interesting ones.

So one of the highlights I got, so some of the, in developed economies, some of the most successful cases were the results of two or more policies working together. So that could be like a ban or something, as well as like a carbon tax, kind of pulling those things together. Oh, for instance, like a great example they had here was like, for instance, example, a fuel efficiency mandate for vehicles combined with subsidies for developing like charging stations and things like that. So then you've kind of got the pressure on both sides. And another thing that was really interesting was cause we spoke about kind of carbon levies and pricing was particularly effective policy in sectors dominated by profit orientated companies, such as electricity and industry.

So I just think it was really interesting to kind of think through it from that perspective.

Chris Adams: So there's a really nice example, there's a few really good examples. Good concrete examples of this to make this, like, something you can, like, get your hands around. So in America, right, we've seen the Inflation Reduction Act. So that, in many ways, are kind of it's all carrot, no stick. So the idea is that there's massive amounts of subsidies for building out, like, for, like, EVs or building out new, kind of, battery gigafactories, all this stuff like that, or things which are essentially make deployment of renewables much, much more profitable than they otherwise would be, because they're gonna, because you have all these kind of subsidies saying, well, we're going to give you a production tax levy.

So for every unit of energy you produce, you'll be able to get, you'll be, you'll get a credit that you can actually apply. So your project over the entire length of it will end up being slightly more profitable. That, there's stuff like that, that you see, which is coming from one end. But we've also seen, In America, the EPA, the Environmental Protection Agency, they've got, they've now come in with a stick, or they're coming in with a stick now, to basically say, well, we're going to have to regulate carbon emissions.

And this now means that it's going to be all new kind of coal fired power stations or gas fired power stations, there'll be all these restrictions on how you should, how you can use them. And this is particular, the reason I raise this in America specifically is we were talking a little bit about AI before, right?

Now these regulations, I don't think that many technologists are aware of right now. They basically say if you're going to run a gas-fired power station, you need to fit loads of carbon capture and storage onto it, which is, broadly speaking, if it does work, it's not something that's really used in large amounts right now.

And what you currently see right now is you see lots of utility companies basically saying, "Oh, the only way we can possibly meet demand for AI is to build all this gas right now." And the problem with that is that ends up locking in all kinds of emissions. Because once you've built something, you have this incentive to kind of try and get your return back on building this in the first place.

And this feels like," I don't think people have realized just how much of a stick this is going to be, because as far as I can tell, all the laws from the EPA basically say, look, you can't build gas like this, and you can't actually do this." So we're going to have, we've got like this case of massive build out of AI coming up against all these regulatory forces as well.

And it's going to be quite a significant fight in the next 6 to 12 months, I think, because yeah, this is, we've now had the honeymoon period of all carrot. Like you said in this piece, and now we're coming up to the stick, which is the other part, to kind of make sure that you can, make sure the significant part of the US grid is going to be decarbonized by, I think it's the mid 2030s, basically, is what they're doing, that they're aiming for with this.

But we have the same thing in the UK as well, like, UK right now, we've got a target for, the UK has agreed to try and decarbonize the grid entirely by 2030, which is great for us as an organization because we, we want a fossil free internet by 2030. So we're like, "oh, thank God the UK is doing this." The UK government, one of the big kind of manifesto policies from Labour coming in, who've just won the election is "we're going to have a clean grid, entirely clean grid by 2030."

So five years, basically five years time, they're going to get rid of all the fossil, almost all the fossil gas generation, right?

Asim Hussain: How are they going to do that?

Chris Adams: That's what we'll find out. But the thing I found out when I spoke to some people who, basically, this is actually all based on some modeling using a piece of software that we interviewed a chap called Iegor Riepin, he was talking about this in one of the episodes, we'll share a link.

That software was, basically, these kind of things were put together by some analysts on our laptop saying, well, this is what you can do. There's a report from Ember Climate where they, the report is called Escape from Gas, I think, or A Path Out of Gas. And this was one of the things that was written in 2022, when gas was super expensive, to say, "well, this is one thing you could plausibly do for this."

And yeah, when, the thing about policy, people reach for what's there. This turned into one of the things that one of the parties led on, and now we're going to see if we do see a fossil free grid and fossil free internet in the UK by 2030. Because, yeah, it's fascinating. I'm so, this is the most exciting, most excited I've been about UK politics in a very long time.

Asim Hussain: I don't know. I might dampen it for you. I'm just not, I'm just not very, I'm just, there's a lot of manifestos that come out from governance when they join and there's a lot of disappointment in the years later when they, when it doesn't manifest, when their manifesto doesn't manifest.

Chris Adams: So this is the final thing that might come in, might be relevant. So the modeling that was used for this as the basis to say, "yeah, we can do this." This one thing that ends up being, so I'll share a post to it, which I end up doing a bit of research and speaking to some of the people about this. It's actually very conservative, more conservative than the National Grid's own

estimates about, specifically in our industry, demand size and batteries. So, these are the two big things that we're likely to see a massive increase in.

Asim Hussain: That's what gas is used for more like this is specifically to get rid of gas.

Right.

Chris Adams: yeah, so the,

Asim Hussain: peaker plants and then therefore you can do a little demand, demand responsible.

Chris Adams: Partly that, the thing that they said is like, the, their plans basically are relatively conservative about the ability for demand side of reduction, making your, you know, Carbon Aware in stuff like that, right? And there is another thing that we've seen is that the UK government is actually being quite gung ho about deployment or deploying all these new data centers.

So I'm kind of thinking, is there a chance to actually say, "well, okay, if you're going to have this deployment of all these data centers, and you know that one thing you're going to need to have is a much more responsive grid, is there a path for all this kind of carbon aware infrastructure to actually serve some of the roles that you wouldn't have to typically rely on peaker gas plants to actually fit, to like kind of fit?"

There's a bunch of stuff there and I think we'll learn basically because, yeah, this has been a really ambitious goal and you've also got this other idea to like bring in something which, can be quite flexible, but only if you incentivize infrastructure to be flexible, because for the most part, we don't see an economic incentive passed down to the consumers of infrastructure to be using this right now.

So, yeah, maybe this is a help of one piece. Yeah.

Asim Hussain: Yeah, I mean, I think there's been, there was some really good work done kind of several years ago, and this will be really good because one of the things I've seen is that the, all the positive moves I saw kind of three years ago regarding new data center rollouts, hydrogen fuel cells, kind of building kind of a much more advanced data center seems to have gone back a little bit.

And yeah, You're right, I think data centers could lead the way in terms of demand response. I'm not even talking about compute demand response. You can just take batteries, you can fill data centers with batteries and then they can store and then they can do their own sucking from the grid when it's clean and powering their own infrastructure when it's dirty.

You know, there's, there's other solutions, which doesn't even necessarily need kind of a software,

Chris Adams: Yeah, exactly. I mean, this is one thing that we've seen in Ireland. There's precedent in Ireland where people have said, "if you're going to be connected to the grid, you need to be prepared to be kind of complementary or sensitive to the needs of the grid for this." So, I think there's actually room for this, and it will be really nice.

I think that this feels like, given such an ambitious target, it does feel like a role where you could actually tell a good story about green Software, and be part of the solution as opposed to part of the problem, because a lot of the discussions around like rolling out of digital infrastructure is basically saying we can't possibly meet this demand.

But if we accept that demand is dynamic, then there is a chance to actually fit this in, and that feels like definitely worth going for, particularly to kind of maintain this kind of social license for operation, particularly for technology firms.

Asim Hussain: And I think a lot of what you've just said over the last couple of minutes runs very counter to what we were saying before about, I mean, everything you just described, this is all related to that whole idea of additionality. It's all about how do we transition, truly transition the grid to be fossil free?

And you need solutions like this. Not necessarily buying unbundled RECs, but you need to actually, like, think through, "well, how do I how do I be a better citizen in the grid infrastructure, do demand response, be sensitive, not demand energy when everybody needs it and therefore we have to spin up a gas power plant or something like that."

So these are the kind of things you need to actually transition the grid.

Chris Adams: Asim, I think we might have fallen down a bit of a grid rabbit hole,

Asim Hussain: Yeah, we've done it again, haven't we?

Chris Adams: Yeah, so, we're gonna have to move on, I think we've come up to time, but Asim, it's really nice to see you again, I'm glad you had a nice holiday, and I guess we've got a bunch of new things to do this quarter, right? With various projects we have inside the Green Software Foundation, and in the other member organizations related to it.

Alright dude, it's Friday, so have a lovely weekend, and for those listening, we'll put all the links to everything we've discussed in there, and if there's something you didn't see, Please do let us know, and we'll make a point of adding it. Alright, thanks a lot folks.

Asim Hussain: Thanks, Chris. Bye.

Chris Adams: See you around soon. Bye! Hey everyone, thanks for listening!

Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again and see you in the next episode.

View Details

Host Chris Adams is joined by special guest Philipp Wiesner, a research associate and PhD student at TU Berlin, to discuss how computing systems can better align energy consumption with clean energy availability. Contributing to Project Vessim, Philipp explains how researchers are now able to model different energy consumption scenarios, from solar and wind power integration to the complexities of modern grids despite the scarcity of available testing environments. They discuss federated learning and its role in carbon-aware designs, along with challenges in tracking real energy savings. Tune in to learn about the future of carbon-aware computing and the tools being developed to help software become more sustainable.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Philipp Wiesner: LinkedIn |GitHub | Portfolio

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Let's Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud [03:26] * FedZero: Leveraging Renewable Excess Energy in Federated Learning | Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems [11:56] * Vessim: A Testbed for Carbon-Aware Applications and Systems * Cucumber: Renewable-Aware Admission Control for Delay-Tolerant Cloud and Edge Workloads

Events:* 1st International Workshop on Low Carbon Computing | (December 3) [41:26] * Code Green: The Intersection of Software Engineering and Sustainability | (September 12 at 11:00 am AEST · Virtual) [44:41] * Doing for Sustainability, What Open Source Did for Software | (September 16 at 11:20 CEST · Vienna) [45:02] * Engineering a Greener Future for IT | (September 18 at 5:00 pm BST · London) [45:24] * Collaborating On Digital Sustainability | (September 18 at 6:00 pm BST · Brighton) [45:33] * Green IO London | (September 19th - 9:00-18:00 - London) [45:45]

Resources:* Environment Variables | Episode 9 w/ Philippe Wiesner [02:48] * Vessim: A Testbed for Carbon-Aware Applications and Systems [04:42] * Towards More Carbon-Efficient Federated Learning (Flower Monthly 2024-04) [13:18] * Vessim | GitHub [24:02] * FedZero | GitHub * Let's Wait Awhile | GitHub * Kepler [26:08] * GitHub - green-coding-solutions/cloud-energy: Cloud Energy is an XGBoost & linear model based on the energy data from the SPECPower database for the cloud to estimate wattage consumption of server by just a few input variables [26:14] * [2210.04951] Ecovisor: A Virtual Energy System for Carbon-Efficient Applications [29:14] * The Trouble with European Green Electricity Certificates | Industry Decarbonization Newsletter [40:07] * Software‐in‐the‐loop simulation for developing and testing carbon‐aware applications - Wiesner - 2023

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Philipp Wiesner: Optimizing energy usage for when the sun is shining and the wind is blowing, of course it makes sense. But the big problem is that these green energy certificates, these guarantees of origin certificates, are traded independently of the physical flow of energy.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams. Hello, and welcome to Environment Variables, where we bring you the latest news and insights from the world of sustainable software development. I'm your host, Chris Adams. Today, we're diving into the world of carbon-aware computing, how computing systems can align the energy consumption with the availability of clean energy.

Natural cycles govern all kinds of things we do. We mostly go to bed at night, and the food we eat is often influenced by what season we're in, and so on. This also shows up in how energy is available to us. You can see how day follows night in the output from a solar panel. And broadly speaking, it tends to be windier around winter than it is in the summer.

Even when we burn fossil fuels, we're basically digging up energy stored millions of years ago. As we move away from fossil fuels though, where we get to use the sunlight that was conveniently stored for us, we move towards a system based around harvesting energy, like we harvest food. The way we consume energy needs to adapt as well.

And that's the idea behind carbon-aware computing. But how do we know if our carbon-aware designs are actually better for the environment? With us today is Philipp Wiesner, a research associate and fourth year PhD student at TU Berlin, Technical University Berlin, whose work focuses on carbon-aware computing.

Philipp is deeply involved in research that connects the dots between computing power and renewable energy, and today will unpack the work he's been doing, including his work on Project Vessim, a testbed for carbon-aware computing. So let's dive in. Philipp, thanks so much for coming back, and for those who haven't heard the last episode when you joined us in 2022, can I give you a bit of space to introduce yourself?

Philipp Wiesner: Yeah, so hey Chris, and thanks a lot for having me back. I'm really excited. Yeah, so I'm Philipp, I'm a PhD student, as you just said, and a research associate at TU Berlin. I'm in the research group for distributed and operating systems. And I've been doing research on carbon-aware or in general, sustainable computing since the start of my PhD or my master's thesis in 2020.

And yeah, at the start of my PhD, I was mainly looking at the basics. So that's the first podcast we had two years ago. The field was still very young and we were looking at the potential of delaying the execution of workloads to make use of cleaner energy. Later, we also looked at migrating workloads from this to different data centers and so on.

And it was all based on carbon intensity. And then from then on later, we moved on from only optimizing for carbon intensity to really better understanding how electric grids work and rather optimizing for curtailed energy, excess energy. So, for green energy that would otherwise go to waste.

Chris Adams: Cool. Thank you. Okay. So you mentioned we spoke in 2022, two years ago, and the field has moved. And while we'll share a link to that podcast, where we go into a lot of detail, can I just give you a bit of time to just provide a brief summary of the paper that you spoke about then? I think it was called Let's Wait Awhile.

That was one of the projects that you're working on, and that was one thing related to the cloud. If we can talk about that'll be a nice scene setter. Then we can talk about the new work that we, honestly, I'm really excited about in all kind of nerdy glee. So yeah, Wait Awhile. What's the deal with that one?

Philipp Wiesner: Yeah, sure. So the idea in Let's Wait a While was just that in different regions of the world and at different times we have different carbon intensities. So carbon intensity is a metric that describes how dirty or how clean is the energy that you draw from the public grid in terms of emissions per kilowatt hour.

And at the time we were looking just, if you have a single data center and you might have some flexible workloads. So workloads where you do not really care if they happen now or tonight or tomorrow morning, how much potential do we have in shifting them, delaying them, computing them a bit earlier, maybe dissecting them in different parts and computing these times in different parts and so on?

And it was like a bit of a, yeah, it was a basic work at the time.

Chris Adams: And there were some, I think, when I first read about it, there were some quite, the savings there were around the low tens of percent for, compared to what the other ones would be. It was something like that, I think, from there. So that was one thing that caught my attention while we ended up speaking about it last time.

This new work that you presented at Hot Carbon, Vessim, as I understand it, this is something which is more general and applicable to all kinds of grids rather than being focused on one or two. Can you tell me a little bit about why you worked on this and what the general idea for creating a testbed for hardware computing was in the first place?

Philipp Wiesner: Yeah, sure. So the thing is that in carbon-aware computing, it's really common to simulate. The thing is that we're often talking about highly distributed systems, often globally distributed systems. And also these approaches often only take effect if you like simulate them or like run them for weeks or months because we need different seasons.

We need different, yeah. So the thing is that in Let's Wait a While and also in basically pretty much all the papers I wrote so far, we have to simulate systems. And in pretty much all the literature so far, people simulate systems because it's just extremely expensive to actually build and operate such systems.

Only big players can do it. And also results are not reproducible. So no one can really check if the stuff that you're reporting is correct.

Chris Adams: So let me just check. So basically, there is no way to... essentially there's no counterfactual, there's no way to see if my, like, I might say "yeah I've made the savings" but without showing your workings it's quite difficult to stand by them or even challenge them actually, that's one of the things that seems to be a bit complicated with that, right?

Philipp Wiesner: Exactly, a general problem in research, to make stuff reproducible. But here we have the big problem that everyone is implementing their own simulation. So everyone is doing it by themselves and just iterating over a big time series for carbon intensity is maybe not that hard. But the moment you have more complex systems and you're working with forecasts and so on, there's a lot of things you can do wrong.

And it's quite a heavy development effort often to do things right. So, just over the years we collected a lot of experience and eventually came up with the simulator. So, Vessim is basically a big co simulation suite where you can plug and play your own simulators for renewable power generation, carbon intensity of the grid, energy storages, and so on.

And you can connect them, you can connect existing simulators, and then test your real system, real applications, as if they were interacting with this simulated energy system.

Chris Adams: Ah, I see, so let me just check if I'm So one of the things you mentioned before is that we tend to look at the grid as like, just one thing that might be changing. And even our interactions are influencing the grid as well, so there's, that's one thing you need to take into account. But you also mentioned just then, that while most of us think of electricity as just power coming out of the wall, there's actually, it's more helpful to think about it in terms of, well, there's maybe on site clean energy, which is maybe very, clean, but isn't always available, and there's maybe on site batteries where the carbon intensities might be influenced by what has gone into it.

Like if it's clean energy that's gone in, it's going to be very clean. If it's dirty grid energy, it's going to be quite dirty. And then there's the grid. So there's multiple different, kind of, ways energy might go into the system that you use for your computing, for example, and you need to account for some of those things.

And then in addition to that, different parts of the world might have totally different grids. So Poland, for example, right now, loads and loads of coal, but comparing that to Iceland, which is, or France, which is like full of nukes, it's going to be very different carbon intensity. So you can't make the same assumptions, and you'll need to essentially do something to recreate the conditions that you might be in so that you can make somewhat more robust and intelligible statements about the savings you might achieve by making any kind of carbon-aware designs.

Philipp Wiesner: Yes, exactly. So yeah, as you said, like most of the existing research is looking at carbon intensity is looking at the global grid. And the problem with this metric is in general, that it's oversimplifying how complex grids actually are. So energy markets are really complex, grids are really complex. So if we only optimize for carbon intensity, which is a relevant metric in the future, we will run into several problems.

Because it's just hiding a lot of underlying complexities. And, as you said, we can maybe avoid these complexities if we're looking more local at microgrids. So if we assume, I don't know, a data center provider is putting solar panels on their roof or like having a direct power purchase agreement with some close by wind park, then we have a lot more direct connection of who's producing and who's consuming, and Vessim is exactly designed for this, to simulate such systems so that eventually you can optimize really for the energy that you're producing or storing.

Chris Adams: I see, okay, so you're still looking at this and we're looking at more than just a grid, basically. We're saying, we're focusing on the carbon intensity because the power can be coming from different places, like the one I'm immediately thinking of, actually. So in the news, Elon Musk's talking about this new data center where he's, where they bought 100 000 Nvidia H100 GPUs using 100 megawatts of power.

And that's so much power that they can't get that from the grid. So what they've done is, it's not clean energy they've used. They've used, say, like, a bunch of mobile gas generators, plugged into the data center that's come in. So we spoke about on site clean energy, but there's actually all kinds of energy that might be going in, and we're now seeing something like this in this kind of world of centralized AI, where you do see organizations looking to things other than just the grid to power things.

So we might need to take into account a whole basically the system seems to be getting more dynamic and being able to simulate this seems to be one of the ideas that Vessim is intended to kind of support so that we can essentially show our working and understand what kind of changes we might be making, or under these conditions, this is what a carbon-aware design might achieve, for example.

Philipp Wiesner: Yeah, exactly. Yeah. As you're saying, it's unfortunately becoming more and more popular to again, build gas turbines or even small nuclear power plants right into data centers to like come up with this insane amounts of energy that they need by now. We of course, like rather focusing on renewable sources because they're also a lot more difficult to schedule.

But yeah, this is one of the use cases of Wessim. So you can like explore how does it affect my data center if I cover the roof with solar panels, build a wind park nearby. How does it affect my data center if I invest into a lot of energy storage? How can I optimize my data center to make best use of these local resources?

And then there's also a lot of like systems questions, like how do I optimize? How do I make applications aware of locally produced energy? How do I make them aware of the state of charge of local batteries? What are they allowed to know? Like there's also security questions involved. And all of this we want to make explorable, so to say,

by providing this very general purpose, extendable simulation framework.

Chris Adams: Okay, cool. That sounds, okay, this sounds lots and lots of fun, and I remember getting quite excited when I read the paper from Hot Carbon. So you've shared this, but as I understand it, some of this has actually been used for some production work, or this isn't just like a wacky paper, there's actually people, there are examples of this being used.

I know that your paper spoke about the use of "Okay, here's how we've been running this on a kind of test system in a Raspberry Pi. Here's how it works with AWS cloud instances." So there are various examples of it being used. But there is a new project that you told me about beforehand called FedZero.

Can you tell me a little bit more about that? Because that seems to be applying some of these ideas in the real world. So yeah, maybe I'll just give you the chance to plug that one, because yeah, it was a fun read.

Philipp Wiesner: No, sure. Thanks a lot. Yeah, exactly. So we're trying to, deploy Vessim in a lot of different projects now. One of the main ideas behind Vessim is also to be have like hardware and software in-the-loop integration. So you can also plug in real devices, real energy generators, and so on.

In FedZero, we didn't do that. FedZero is also fully simulated. But it's a new, it's a scheduler basically we proposed for federated learning systems. This is,

federated learning is some type of distributed machine learning training. So you have a bunch of different clients and they locally train a machine learning model.

So they locally consume energy and the scheduler basically decides when, who is training. So it's like distributed batch processing in the end. And the entire evaluation of the system was done with Vessim. We have, for example, a lot of data sets that are coming with Vessim. They've been provided, for example, by Solcast.

It's a big solar data provider. And the entire idea behind the system is to only use excess energy. So only use curtailed energy and spare computational resources to perform a distributed machine learning training to make it effectively (an exclamation mark) zero carbon! Because you don't use any energy that would have been used by anyone else, basically.

Chris Adams: Oh, I see. Okay, so there's two things that I'd like to unpack there. So could you maybe just talk a little bit about the relationship to, I think I was confusing this with Flower, perhaps. So Flower is one of the wider projects which has something to do with federated machine learning. you maybe just talk on that because I think, for people who have listened to this before, they might not be aware of Flower or the even idea what federated machine learning might be. Because I just spoke about a centralized massive data center, but that's not the only way you can do machine learning and AI training by the sounds of things.

Philipp Wiesner: No, sure. We can also go a bit more into detail. So in federated learning, we assume that our data is distributed. So it's a different clients, a very common example are hospitals that, for example, want to train a common model for skin cancer detection whatsoever, but they cannot share their private patient data.

So we need to somehow train on their data without them releasing this data. And what's happening and Flower is one of the frameworks that lets you do this, that lets you perform federated learning as we distribute the model to the different hospitals, they locally train on the data and send it back.

And we try to schedule this local training in a way that it's only using green energy. Yeah, that's the main idea.

Chris Adams: Ah, I see. So, these would be devices which might already exist, for example, you don't have to have the same kind of emphasis on having a bunch of new stuff that you're using all the time to kind of sweat the asset and make the most of it, so you could be using maybe older technology or a more kind of mixed set of computing, rather than 100 000 H100s, for example, in one straight place, for example.

Philipp Wiesner: Yes, that's true. That's true in one sense. On the other hand, we always have to see what we're optimizing for. And if you're optimizing for something like curtailed energy, like for example, in the north of Germany, we have a lot of wind parks. But the German grid is not always strong enough to get all this energy to the south where like the big consumers are, the big industries.

So often times we have an excess of energy in the north. Now if you have hundreds of kilowatt hours of excess energy in the north, it doesn't get you anywhere to turn on a bunch of iPhones or old computers to make use of this energy. So usually with our approaches we target big consumers. We target the A100s and H100s to, because they actually make a difference.

Like turning them on or off actually makes a difference to the grid. A few thousand iPhones, not so much.

Chris Adams: Okay, so you still would be using some of this kind of relatively powerful hardware, if it represents a significant power draw on the grid, for example. And, is there anything special about where these might be placed? Because I've, seen examples and I've seen people talking about the idea of like literally putting this stuff directly into, say, the towers of wind turbines.

I know this is one thing that Windnode in Germany were doing, for example, because that's basically, where the power's not being used, it's one of the most fastest ways to actually

Philipp Wiesner: yeah, clearly, yeah, that's a super important topic, like placement of data centers. Just what I said, of course, you like place these data centers again, and if we talk about Germany in like Frankfurt region or in the south of Germany, it doesn't get you anywhere because you still need to transfer the energy there.

So you would actually need to build data centers very close to where energy is produced. However, like the big problem that we're facing right now with all this LLM and GPU stuff. is that there's actually not a lot of flexibility. So, FedZero for example assumes that we have some spare resources and some excess energy, and maybe the excess energy is fair, we do have that but we do not have spare resources.

Like, whenever I keep telling people since the last six months about this project they're like, "no, there are no spare resources." Like, GPUs are used all the time, we have a GPU shortage so, carbon-aware computing on GPUs is not really working at the moment.

Chris Adams: Yeah, I'm glad you mentioned this because this was one thing I've always been struggling to make sense of because when you've got a graphics card which is like 40k and you've got only a certain amount of years to use it, for example, the cost of having it off is actually quite high. So therefore, being able to simulate what the savings might be from some carbon air computing might, would actually be meaningful.

Or, if you're not going to switch off the power, then you might need to find another way to, like, not draw power from the grid. So that kind of implies either an increased amount of storage that you might need, so that rather than switching things off, you just reduce the power you're drawing from the grid by pulling it from somewhere else, for example.

So that's another kind of way you might flex your system to... still reduce the emissions, because it may be the case that you're able to load up on clean energy when there is an excess in other places, whilst keeping that thing still running, for example.

Philipp Wiesner: Yeah, exactly. No, you're completely right. And that was different, a few years ago when you, like, were mostly talking about cloud computing on CPUs, when we were talking about carbon-aware computing, because there you usually have a big buffer, because cloud providers want to have this image of infinite scalability, so they usually have spare resources at hand.

So, yeah, like this entire load shifting stuff was somewhat reasonable. Now with GPUs, I mean, you're right, you would need to plug them off, but no one's doing that. Like, if you're buying a GPU, you're using it.

Chris Adams: Using as much as you possibly can to make it, to make the per hour cost as low as possible, because you're, I see, okay, so, this is one thing I'm really glad you allowed us to dive into this because one of the things that I would initially think about, like there's some trade offs you might be making, and I might, before I spoke to you, one of my assumptions was that by using a federated model, you might have a lower embodied carbon because you're able to use a wider set of computing, which might already exist, for example, but it sounds like, because some of these chips are, they use more power, but per instruction, they're much, much more efficient per instruction. So, you're probably not going to save that much from the total embodied carbon of your fleet, for example, by reusing existing stuff in some cases. Is that what it would be like?

Philipp Wiesner: Yeah, there's different studies on whether highly distributed training or computation in general is actually more or less efficient. It often really depends, like usually the centralized, like you won't get anything more efficient than an H100. Energy per instructions. It's super, super efficient, but then of course, if you put them all in one place, you need to cool more and so on.

So often it can be more efficient to distribute it. there's no clear answer to that. I would say it really depends on the system, whether federated distributed system is more energy efficient or a local one, but of course in distributed system, you might have more flexibility for scheduling and waiting and yeah.

Chris Adams: Ah, I see. And I'm just going to move on to another question in a second, but while we talk about that, I just wanted to speak about maybe this idea of more distributed federated learning. A lot of the time you see people talking about saying, "I need a cluster of machines in one place because they need to talk to each other."

And the closer they are, the lower the latency, the faster the responses might be. And. When you're using a more distributed version, a distributed model, if you're not doing, like, even if you're not thinking about machine learning, you still need to think about latency, how long your response comes back.

How, like, what are the trade offs that you have there when you're looking at a kind of federated model, like with Flower, or providing some of these kinds of more distributed, carbon-aware style approaches, for example? Like, how do you address that?

Philipp Wiesner: So in general, in federated learning, we differentiate between cross device and cross silo federated learning. And cross device is what you were mostly referring to as like you have a lot of iPhones, a very distributed small system. They're often connected via mobile network. So latencies are usually quite high.

And there you really need to consider this latency trade off. In cross silo federated learning, it's a bit less important because you assume that each of these clients is, as I said, like a small data center or a big data center, they are connected via fiber. So, latencies are usually very low and not super relevant compared to how long a training takes.

So like sending models back and forth, model weights is not really relevant compared to how much time you need to compute actually.

Chris Adams: Ah, thanks for explaining that, because there are various companies who are talking about having a distributed model, or saying, you need to do, you need to have, maybe, infrastructure that is complementary to the grid. And I was never able how to, how you get around the issue of speed of light, right?

Because they're going to be very, different if, even if it's just opposite ends of the country, that's going to, depending on the size of your country, that's going to be somewhat meaningful there. Okay. All right then, so we spoke a little bit about the use of Vessim, we spoke about why it exists, and like kind of this idea that you can simulate various kind of configurations of grids or configurations of power coming into the system.

I imagine there'll be some people who are listening thinking, "this sounds cool, how do I actually use this on a project when I'm designing something in a kind of carbon-aware way, or how do I actually, what am I looking for?" Could you maybe talk me through? The actual process of using Vessim specifically.

We can start with something simple like a machine learning job first and then we might talk about some other configurations like perhaps a CMS because that's what lots of people might be working on for example.

Philipp Wiesner: I mean, the entire idea of Vessim is that you do not really notice that it's a simulator. It should behave as like a proper energy system. So you can, on the one hand, you have your normal applications. It doesn't matter if it's a machine learning job or if it's a CMS or if it's anything else. You just have your applications that are running.

And then all you need to do is you somehow need to get their power usage into the simulation. You can either do that by modeling. You can, I don't know, look at the CPU usage of your application and somehow estimate how much power it would use. Or you actually let it run on a machine, plug a proper power meter, and then periodically feed this information into the simulation.

And the simulation itself you configure as you wish. So we have a lot of READMEs. You can plug and play custom simulators. We have some implemented, we're right now implementing the ones from the National Renewable Energy Laboratory. They have lots of simulators on everything from solar to wind to geothermal and whatsoever.

So you can plug your microgrid together. Also provided with energy storage. We are releasing Vessim 0.9 this week, I think, which then comes with a few more energy storage solutions. So you can really plug this together as you wish. And then you can write your own API basically to access this data center. The new applications, as in normal carbon-aware computing, can just query a REST API or something and really ask "what's the state of charge of my battery, how much energy is produced right now, what's the forecast for carbon intensity," all of this.

Chris Adams: Okay so I'm going to break that down a bit because there's a couple of quite interesting concepts that you spoke about. So first of all I feel a bit embarrassed by not mentioning this, we just assumed it, of course, was open source, but yes, this is entirely open source, anyone can access it, if they search for Vessim, V E S S I M, they'll likely find the project, because there aren't that many other things called Vessim right now, is that the case?

Philipp Wiesner: I hope so, because we were searching for a searchable name.

Chris Adams: We'll also share links to the actual project on GitHub as well. It's written primarily in Python as I understand it, so if you know Python or know someone who works in Python, and given that Python's basically the most popular programming language on Earth, or by various metrics, is one of them, then the chances are fairly high that you can start doing this.

Are there, like, presets for different grids? So in the same way that you might have a preset for, I'm viewing a website on a mobile phone, or I'm viewing a website on a desktop, you said a little bit about NREL, the National Renewable Energy Laboratory. They've said, "well, this is what the, this is how a geothermal plant might work, or this is how a wind turbine might work and this is solar panel might work."

And that gives you an idea of saying, "well, this is somewhat similar to my grid." And then there's kind of, are there some presets or things so people can come up with some approximation of what it might be in their part of the world?

Philipp Wiesner: Not yet publicly. We're working on this and we will publish it soon. But right now there's no presets, but Vessim comes with some data sets that were provided. One was provided by Watttime on carbon intensity. One was provided by Solcast on solar data. And you're right, Vessim itself is in Python, but we're like building on a library called Mosaik.

Been developed in Oldenburg, also in Germany, and this is basically the entire co-simulation system behind Vessim. And they allow you to basically plug and play any type of simulator that can be written in Java, or it can also be a real system. You can also just take a real battery and measure that and just feed this information.

So it's really very flexible in that sense.

Chris Adams: Ah, cool, I'm glad you mentioned about the power use thing, because that's the thing I was going to speak to you about, because you said that you can draw power from a physical system, so you might time series of power usage, but one thing that we've spoken about previously with other guests on this podcast is that if you know what kind of compute usage, how much of your compute of a server is, you can make some I'm a bit worried about using the word inference when we've just spoken about AI.

But like, you can, there'll be some idea of what the likely power might be, just because machines tend to use more power at 100 percent utilization versus maybe 50 percent utilization. There's various curves and things that give you some numbers. And I believe there's an organization, Green Coding Solutions, who share some of this.

But also, I think this is under the hood what, other projects like Kepler also have some reference to. So, there are different ways that exist right now to give you some numbers. Even if you don't have something plugged into a system, for example. Maybe, you don't have access to, a power meter like you're deploying in a cloud, for example.

Philipp Wiesner: Exactly. Yeah. And this is cool that you mentioned that because this is one of the, it's a master thesis that we are running right now with one of the students who has also been developing Vessim for the last two years. And we are also using Kepler and trying to really calibrate Vessim for real systems.

And of course, these calibrations can be published. So we can really see, because there's this big difference between software-based power metering and like actual hardware power metering. In software-based power metering that's like included in Intel processors and also NVIDIA graphics cards, they just estimate how much power do I draw right now.

But it comes with a certain error. And what we're doing is like we're benchmarking these machines, using the integrated software-based power metering that actually everyone has access to but also like plug a real power meter and see how big is the difference under different conditions and so on and try to, yeah, make Vessim a bit easier to configure for bigger systems. Because this is the entire idea, maybe you have access to one GPU that you can benchmark but then you want to explore, "okay, how does my system behave if I have 200 GPUs?" And you can scale up in the simulation.

Chris Adams: Okay, so when we, so when someone is starting with this, like, we're going to talk about actually running the software, but we're just setting the scene to figure out, okay, what does the setup look like? Because I think most developers might be familiar with the idea of running a test to see if it works as intended.

There's this whole new world outside of your computer system that we need to talk about that I think you might need to kind of, that people need to understand before they start thinking about what, how the system is supposed to be designed. So we spoke a little bit about the fact that Vessim is using a existing tool called Mosaik, which designed for simulating grids.

So someone's done all that work already to figure out how to simulate a grid and you're using, you're relying on some of that. So there's a bunch of work that's gone into that already that you can draw upon. And we spoke a little bit about, there are ways that you can get readings on power, so even if you don't have something plugged in, you can still get some maybe low precision but still useful numbers to help inform some of your, like, design choices.

And then, now you've got that part there. You said a little bit about maybe things being in the, software being in-the-loop here, and I think while I've spoken excitedly about the notion of ecovisors and things on previous podcasts, I think that's what you're referring to here, like if the software itself knows how much, how full a battery is, or how green the power is, it might change in certain ways or it might respond to certain things.

Could you talk a little bit about that part? Because I think the software in-the-loop part is the thing that most people who've been taking an existing project and maybe trying to extend it to be carbon-aware. That's where they might be spending their most times either thinking about how to test something or figuring out how to make and adapt their existing system so they can start coming up with some metrics.

Philipp Wiesner: Yeah, It's interesting that you mentioned Ecovisor because it was a big inspiration for this project. Because I think they spent tens of thousands of euros on this one solar array simulator and a testbed. And we wanted to, like, explore similar ideas, but we didn't have the funding at the time to just buy such a machine.

So I had to write a simulator, more or less. So this is how it all started. Sorry, what was the question?

Chris Adams: in-the-loop, software in-the-loop,

Philipp Wiesner: Ah, software-in-the-loop, sure. Yeah,

Chris Adams: We've simulated all this stuff, we know roughly how much power we're using, so the system, the software now has the data going into it. So what happens next? That's the thing.

Philipp Wiesner: Yes. So the idea is we need to run the simulation in real time, right? In wall clock time. So one second of simulated time needs to be the same as one second of real time. And if we manage this, then we can simply from the simulation, host any kind of API. We can just spin up a REST API that gives us access to the system.

And in Vessim, users can define these APIs themselves. So in Ecovisor, for example, they already came up with an API. I don't know, "/battery" and then you can query the battery state of charge, but something like this. Vessim lets you explore this. How do we abstract the complicated energy system and how do we like expose relevant information for the computing system?

And then you can just run a real normal application running on your computer, running in a docker container whatsoever. And it can send requests to this energy system API. And best case, if we did everything correctly, it behaves exactly as if you were doing a request to an actual energy system. So your application doesn't know that it's working with the simulation.

Chris Adams: Okay, so I'll try and make this a bit concrete. So when I'm working on a project, in an existing kind of carbon-aware system, I might make an API call to like, I might ask electricity maps, "Hey, what's the local grid intensity where I am right now?" For example, and like, it's a little bit like that kind of request I'd be making, but I might be making it to Vessim to say, "what's the grid intensity?

What's the state of my charge or stuff like that?"

Philipp Wiesner: Exactly. You just write a normal application that is running on a system, just that the system is power metered, so Vessim can simulate how it would be behaving if it was plugged to batteries, for example, and then it can talk to this simulated energy system.

Chris Adams: Gotcha. Okay. And we're using Vessim as just the kind of, simulator to share this stuff and it may be that in the real world, like I might be, speaking to the electricity maps API or something like that.

Philipp Wiesner: Absolutely, would be, yeah, absolutely.

Chris Adams: Okay.

Philipp Wiesner: A plug and play thingy, yeah.

Chris Adams: All right, that part, I think I understand. So then at that point, I'm then able to basically say, well, let's imagine electricity maps has given me this figure for carbon intensity, or let's imagine my, the state of my battery is high rather than low, I then might make some changes and say, well, "When the energy is low, don't do this stuff, or just delay it for maybe half an hour to check it again."

So that's the kind of stuff. So maybe you could talk a little bit about, now that we're at that point, how does that manifest into me seeing if that has actually reduced carbon emissions over a period of time, for example. Maybe we could talk about that part, because I think that's the final thing, now that we've set up our system, we've connected to, we've figured out how to get data coming into my system to tell me what the carbon intensity might be, or what batteries might be, or what the power from a wind farm might be. So yeah, maybe you can talk about that. So over a given time, has this actually helped, for example?

Philipp Wiesner: Yeah, And this is actually what makes simulations so powerful, because you can just execute a bunch of different scenarios. You can execute your scenario one time without any carbon-aware strategies. You can execute it a second time with the carbon-aware strategies. You can simulate as if you were executing it in summer or winter, or you can simulate power outages and whatsoever.

Because it's all really fast and really cheap to do. And then of course Vessim is recording all these metrics. Like for every second it's recording how much power has been drawn, produced, how much emissions were there. So afterwards you can analyze these results and compare the different runs.

Chris Adams: Ah, okay. I think I'm understanding this now and I

kind of figure out how I might build some of this now if I was to be building maybe a batch job, for example. I can kind of maybe imagine how this might work for maybe a content management system or like a CMS or WordPress or something like that. So let's say I would do, would I be looking at like, this would be my traffic the last month, run it through and then compare it to what the carbon intensity might have been.

Is that how I might do this?

for

Philipp Wiesner: Yeah, absolutely. Absolutely. And you can also use it in testing pipelines, for example, in continuous integration pipelines. You can just simulate a bunch of different scenarios for your carbon-aware application. Some of them might be power outages or something like really edge cases that you do not want to happen, but you can really test cheaply that your behavior, that your system or your application would behave as expected

Chris Adams: Ah,

Philipp Wiesner: In a reproducible manner.

Chris Adams: So you've raised something quite interesting for me here because you, when you spoke about the idea of like things, power outages or stuff like that, this kind of implies that if I've got a system here, I could see to what degree I might make a change to the software, or I might just say, well, given I have control over my infrastructure, I'm running a data center, what if I was to just put a battery inside that data center?

How would that impact the carbon footprint of using this system every month, for example? Would that, could that be something that I could simulate with that?

Philipp Wiesner: Yes, absolutely. Absolutely. And if you have a model that is able to, like a battery model, a simulator that is able to simulate battery aging, for example, you can also simulate what's happening over the course of the next three years with my batteries and so on.

Chris Adams: Ah, okay, so it's actually two way So therefore, I can look at, I can, look at, say, making interventions at my code level, and I can interventions at the kind of deployment scenario level as well, actually. Okay, that is something I hadn't actually realised before then. Okay, so we've dived into this quite a bit and I hope there are at least some people following us now.

Can we just take a step back to say because we have just been assuming that carbon emissions or carbon intensity is absolutely the figure we should be looking for and that is our North Star and you mentioned before that maybe that isn't or there's a bit more to it than that because we can't just look at this number, see if it's going down, and say, "Oh yeah, we're making progress."

Maybe you could outline on some of that, because it's a lot of nuance here that people often miss, I think.

Philipp Wiesner: Ah Yeah, sure sure sure. So carbon intensity is a metric that defines how clean or dirty the energy in the public grid is. That means if it's low, you can use it if it's high, you should maybe rather not. And the problem here is that it's hiding a lot of the underlying complexities of how grids work and how energy markets work.

So for example, one big problem that we have in energy markets is, like in carbon accounting in general, is this double spending of guarantees of origin certificates. So for example, you can easily buy certificates produced in Iceland or something. They produce almost all the energy through renewable sources, hydropower, geothermal power.

You can buy their energy and then tell everyone you're 100 percent renewable energy. But at the same time, of course, any data center that is located in Iceland will tell you that they're 100 percent renewable, which is also true. and in fact, there's not even a power line between Iceland and mainland Europe, and still you can buy their certificates.

so we have a lot of double accounting and of course, everyone is coming up with new methodologies of what's good and what's the right thing to do. And of course, everyone's also just doing what's in their favor. And this is the big problem with carbon intensity. So of course you can say now "carbon intensity in Germany is really low.

I should consume energy." But unless you have a green energy contract, you're for sure only getting the dirty fraction, because all the green energy is already sold.

Chris Adams: So let me just check if I can stop you there for a second. So what you spoke about just then was there are kind of two approaches or like there's one one approach of looking at how kind of green power is might be the existing kind of system that you see in most developed energy markets right now where there's like a market-based system where you essentially can purchase renewable energy certificates and apply that to kind of brown energy to then say it's green.

And there may be reasons why we have ended up with this scenario. As you said, there are two problems there when we talk about, say, the idea of buying green power certificates from Iceland and then applying them to dirty power in, say, Poland or Germany to say it's green. There's like a, there's one issue which is that there's literally no way to connect, there's no connection, like we definitely are not using geothermal that's generated in Germany to get there. There's no physical connection so it's not deliverable. And the other issue is that if Iceland was to do that, they would then have to stop saying their power is green because they've already sold on their greenness. And in many cases they're not doing that. They're saying, "oh, we're still green even though we've solved the greenness."

So, there is a kind of problem about the, yes, let's assume that the market, the concept was conceptually sound. There is a whole issue about people kind of cheating a bit and saying no, it's still green when they've sold the greenness on it already, basically.

Yes,

Philipp Wiesner: and exactly in this sense, optimizing for carbon intensity is cheating, because you're doing exactly this. You're like saying, "I'm using low carbon energy," but all the green, as you said, has already been sold. At the same time, it makes sense. The metric also makes sense. Optimizing energy usage for when the sun is shining and the wind is blowing, of course it makes sense.

But the big problem is that these green energy certificates, these guarantees of origin certificates, are traded independently of the physical flow of energy.

Chris Adams: Ah, okay. Okay, so there is, there's a whole discussion about this, like, where we work at the Green Web Foundation, we're kind of borrowing some of the ideas we've seen in the hydrogen sector, where they talk about if you want to say energy is green, it needs to be, I believe it is, timely, deliverable and additional.

So you need to be new power, like the, you mentioned this example of nuclear being used in other data centers, where essentially you're reallocating power that would have been going into the grid. So everyone has slightly greener power, but you say, no, that all has to go over the data center. Then that has the impact of essentially making the power that everyone else is using be seen as slightly less clean because of this accounting system, and that's one of the unfortunate artifacts of that. So that's one thing you mentioned about that. And I think the system that you might be talking about was the idea of like a location-based system, which is much more about like the physical environmental footprint of the power you're using rather than, say, the market-based approach, right?

Philipp Wiesner: Exactly. So we need a system that is somehow time based and location-based, a certificate system, then this all would make a lot more sense. But even then, grids are very complex and it's too easy to boil it all down to a single number and say at Germany, for an EPM we have this number of carbon intensity.

It would maybe make more sense if we, like, break down everything into smaller pieces, again, go more local. I have, for sure, Northern Germany separated from the South and stuff like this. But still, it makes sense, and this is what, for example, Vessim is good for, to really think about and understand how is energy actually flowing, how is the energy system actually working, because it's a bit more complex.

Chris Adams: Ah, I see. Okay, so for people who want to go down this weird accounting rabbit hole that we just kind of skirted around, I will share a link to a journalist called Hanno Böck who's dived into the world of Iceland, and in particular about this whole idea of selling green energy twice like this, because if you are looking into this, it's, as we end up with a much more decarbonised grid, this is going to come up again and again.

And right now, we do see the systems being used, like the GHG protocol, the people who actually define these standards. They're going through a process of reform and basically saying, "well, these are the changes we need to make and this is why this is possibly not fit for the purposes that it was 10 years ago," for example.

So there is a chance to make interventions and talk about this, if you want to look into this as well as looking into the other things we spoke about with Vessim. Okay, so we've spoken about this idea of setting up a kind of testbed that we've established that this is kind of open source, that anyone can pick up and start playing with right now, like the code is open source on GitHub, and as I can see, documented well with like, videos and stuff like that.

We're just coming to time, so I just want to give a bit of space for some of the future events that are coming up, because I understand that, well, part of your job, as you told me, is like, I'm the publicity chair for this all about low carbon computing, so I should probably give you a bit of space to talk about that as well.

Philipp Wiesner: Yeah, that's super nice. Thank you to just take two minutes. So we're organizing this workshop. It's the first workshop for low carbon computing, which will take place on the 3rd of December in Glasgow, and It's mainly an initiative, a local initiative from some folks at the University of Glasgow, but it's an international conference, it's an international workshop I mean.

And we expect submissions from all over the world, but mainly probably the European community, I guess. And yeah, welcome everyone to submit your work. So we have a very broad scope on really anything related to sustainable computing, from energy efficiency, carbon efficiency, embodied carbon and so on, but also topics that are often a bit underrepresented in computer science like circular economy, sufficiency, demand reduction, and all of this. exactly. So this is all very welcome. And for regular talks, all you need to submit is like a two page extended abstract by the 24th of September. Although we're like currently discussing maybe a tiny deadline extension and all accepted authors, all accepted papers will afterwards be invited to submit like a full workshop paper of up to eight pages if you're interested, which will be published in our post proceeding.

So yeah, feel free to have a look. I think we will also put a link in the

Chris Adams: a link in the show notes, for sure, absolutely. So if I understand this correctly, is this a little bit like, possibly, a kind of like a sister conference to Hot Carbon, but where it's a little bit colder, and you're more likely to kind of find a burrito served at Legal Jack's.

Is the name of a restaurant in Glasgow that eaten at before.

Philipp Wiesner: Yes, I guess like it's the first version. Let's see where it's going. But maybe we can, if it's going well, we can maybe establish it as like a European alternative to Hot Carbon or something, which will, I guess, take place in the US in the upcoming years.

Chris Adams: I see. And there's one thing I wanted to just check because when I looked at the kind of call for papers, the set of topics, it's a little bit more wide than just like let's focus on efficiency. There seems to be a kind of systemic angle that I hadn't seen quite in the same way, for example. So there are discussions about like you said,

okay, looking at the demand side as well as just the supply side, for example. And like, I think I've even seen the word frugal computing used inside here. Like, okay, this is almost like somewhat possibly like the limits conference or maybe some of those ideas somewhat comparable to inside this.

Philipp Wiesner: Yeah,

guess, yeah, I guess it's somewhere in between that, in between Hot Carbon and limits, maybe.

Chris Adams: cool. All right. Well, I am now thinking it might be nice to figure out a way to get a series of trains to get up to Glasgow, because, I really like that city.

Philipp Wiesner: Yeah, 18 the last times.

Chris Adams: Okay, cool. So that's one thing that's taking place. So the deadline was the 24th of September. Easy to apply to, there is, and that'll be taking place in December.

Philipp Wiesner: Just one last thing, it's a hybrid event. It's a hybrid event, so anyone is welcome to participate, and also authors are of course welcome to present remotely.

Chris Adams: Okay, so I don't need to get on that if I really don't want to, because, well, I might want to see people, but it takes quite a long time

Philipp Wiesner: only a one day event, so you need to consider if it's worth two days of travel.

Chris Adams: Alright, thanks for that Philipp, I appreciate that and we'll share a link to that so people know when the CFP is open how, well actually when it closes more specifically because I think it is open right now. Okay, cool. So I'll just touch on some other events that we have inside here and then I think we'll wrap up if that's okay with you.

So these are some of the other events that our producer Chris Skipper has shared. So there's an event called CodeGreen, the intersection of software engineering and sustainability. This is on September the 12th at 11am AEST. This has Sara Bergman from Microsoft Norway, and one of the, one of the authors of the book, Building Green Software, and also a regular on our podcast.

She's presenting, speaking with Michelle Sandford. And there's also an event in Vienna, in Austria. This has Asim Hussain, our Executive Director of the Green Software Foundation. He's talking about the Impact Framework, this radically transparent tool for sharing the environmental impact of your tooling, and that's on September the 16th, and I think that is in person, but then maybe we'll share a link for people to see about if they can get involved remotely.

There's also another event in the UK, Engineering a Greener Future for IT, that's on September the 18th at 5pm British Standard Time in London. And there is also another event in Brighton as well, so the UK is quite heavily represented right now, Collaborating on Digital Sustainability, that's September the 18th.

I'm going to use this platform while I still can. I'll share a link to Green IO London as well, which is the conference that I'll be keynoting at with a number of luminaries. We'll share a link to that because I, it's very front of my mind right now and I'll be there for the day. So if you listen to this and you fancy coming along, we'll share a link where you can get a free ticket to join at the conference.

And yeah, that's us. I think we've come to the time. We'll just actually make sure that all the things we've discussed, like I mentioned before, we always try to get as many of these show notes full of links as possible, because we cover a lot of ground on these free wheeling conversations, so that will be visible.

The thing you might need to do though, if you are listening via Spotify or the Apple platform, you might need to look up podcast.greensoftware.foundation, then follow the link to this podcast to see all the links, because I don't think they're made available if you just are listening to it in Spotify, for example.

And we do put quite a lot of time into doing that. And Philipp, I just want to say thank you so much for helping unpack what can be an extremely complicated topic and putting the work in to make a open source project that makes it easy for people to figure out what to do with carbon-aware computing and hopefully guide themselves to slightly more sustainable software.

Philipp Wiesner: Yeah, no, thanks a lot for having me. Yeah, had a lot of fun. It was a pleasure. Thank you.

Chris Adams: Okay, final question I should ask, if people do want to find out about you, where should people look? Are you on LinkedIn? Are you still using X slash Twitter slash what's the best way to follow your work these days?

Philipp Wiesner: Probably just Google me, I guess there's maybe one or 2, 3, 4 Philipp Wiesners that are more important than me, but if you just look at TU Berlin or Philipp Wiesner carbon-aware where I should pop up and then you can see.

Chris Adams: Cool, well your name will be in the show notes and the show title, so if anyone is curious about how to spell Philipp Wiesner and not sure how many P's they should be using, then that'll be inside there. All right, Philipp, really lovely chatting to you, mate, and thank you so much for coming along, and yeah, have a lovely week.

Philipp Wiesner: Thank you. You too. Thanks a lot.

Chris Adams: Cheers, bye!

Philipp Wiesner: Bye.

Chris Adams: Hey everyone, thanks for listening! Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode!

View Details

This week we are joined by two PhD researchers, Silke Kaiser and Chiara Fusar Bassini, from the Hertie School in Berlin. With host Chris Adams they discuss their use of data science and machine learning and how they are using them to tackle some of today’s most pressing environmental challenges. Silke shares insights into her research on predicting cycling traffic in cities to better inform urban planning and promote sustainable transport, while Chiara discusses her work on analyzing European energy data to support the renewable energy transition. Together, they explore the intersection of technology, data, and policy, highlighting the importance of data-driven decision-making in achieving sustainability goals.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Silke Kaiser: LinkedIn | Website * Chiara Fusar Bassini: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* From counting stations to to city wide estimates: data driven bicycle volume extrapolation | Silke Kaiser [09:46] * Pedalling Towards a Greener Future: The Impact of Cycling and Active Transport on Climate Change and Public Health - Catalyse [12:46] * Chapter 10: Transport | IPCC [14:10] * Estimating Coal Power Plant Operation From Satellite Images with Computer Vision [24:11] * Does the EU AI Act really call for tracking inference as well as training in AI models? [38:27] * What is the methodology used to measure the carbon footprint of training Llama 3.1? [41:12] * Climate policies that achieved major emission reductions: Global evidence from two decades | Science [44:27] * Microsoft employees spent years fighting the tech giant's oil ties. Now, they’re speaking out. | Grist [46:51] * A review of the ENTSO-E Transparency Platform

Resources:* How does AI and ML Impact Climate Change? | EV Ep 5 [05:38] * French Revolution: Cyclists Now Outnumber Motorists In Paris [07:25] * Berlin’s Efforts to Reduce Driving Stalled by German Car Culture [07:42] * Emissions of Carbon Dioxide in the Transportation Sector | Congressional Budget Office [16:47] * Electricity Maps [21:59] * Machine Learning for Sustainable Energy Systems | Annual Reviews [30:41] * CodeCarbon [40:49] * Light bulbs have energy ratings — so why can’t AI chatbots? [42:16] * The Chronic Potentialitis of Digital Enablement | Vlad Coraoma [46:10] * Blackout (Elsberg novel) - Wikipedia * International Energy Agency - an overview | ScienceDirect Topics * Taxation - an overview | ScienceDirect Topics * How fast is Germany cutting its greenhouse gas emissions? – DW – 07/10/2023 * Tackling Climate Change with Machine Learning | ACM Computing Surveys

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

**TRANSCRIPT BELOW:

Silke Kaiser:** I like the term of fighting fire with fire. You know, you're trying to make it better, but you're making it maybe even worse. But I think if we make some smart choices along the way, I rather like to compare it to the idea of fighting a forest fire with a controlled burn. What I'm trying to say is that there are different approaches that we can actually also reduce the emissions caused by AI.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host Chris Adams. Hello and welcome to Environment Variables, where we bring you the latest updates and news in the world of sustainable software development. I'm your host Chris Adams. It's important to understand that when we talk about sustainability and technology, it's easy to mix up sustainability of software with sustainability through software. Sustainability of software development is about understanding the direct impacts of technology and doing as much as we can to reduce it without delivering a worse experience for people using the software. Here, we care about the impact of code, like making it more efficient or making sure the energy we use is cleaner and coming from the cleanest possible sources. So when we talk about green software or green IT, this is what we're talking about. Sustainability through software development, this occurs through the application of software to solve a specific sustainability problem or provide us with insights that we didn't have previously to help us meet some of our sustainability goals. To make this really concrete, you can use green software and talk all day long about the sustainability of software whilst helping people drill for oil and gas. Now you can do that, but it's really not a good idea if you wanna hit any kind of societal climate goals. And if you're listening to this podcast, I think you probably don't wanna do that either. So while we usually cover the sustainability of software. It can also be helpful to look up from our keyboards sometimes to talk about the effects of software, the effects it can have for helping us reach our climate goals. So in this episode, we'll be diving deep into the work of PhD candidates who are pushing the boundaries of what's possible in sustainability ad software. In this episode, we're joined by two researchers from Berlin Institutions, the Berlin School of Economics and the Berlin Hertie School of Governance. So what insights can we gain from their research? How are they using technology to address some of the challenges around sustainability today? Let's find out. So, first of all, Silke, can I just give you folks a bit of time to introduce yourselves? I'll hand over to you, Silke, and then hand over to you, Chiara, to introduce and give you the floor. So, yeah, Silke, thank you very much for joining. The floor is yours.

Silke Kaiser: Thank you very much, Chris. I'm Silke Kaiser. I'm a PhD researcher at the Berlin School of Economics and at the Hertie School Berlin. I'm excited to be here today. My research focuses on the analysis of sustainable transport data, with particular emphasis on cycling data. I utilize various tools from machine learning, data science, and spatial statistics to explore this field.

Maybe more on a personal note, outside of academia, I would say I'm a bit of an auto enthusiast. Just earlier this week, I came back from a vacation in France, but I'm happy to be back and to join you for this episode today.

Chris Adams: I'll be Back just in time for the weather to be nice in Berlin, right?

Silke Kaiser: Exactly.

Chris Adams: Cool. Thank you for that, Silke. And, Chiara, can I do the same to give you some space to introduce yourself as well?

Chiara Fusar Bassini: Yes, thank you for that. My name is Chiara Fusar Bassini. I'm a PhD researcher at Hertie school in Berlin. I'm very excited to be here for my very first podcast. My own research focuses on the analysis of European energy markets. And I use data science and machine learning to analyze time series of dispatch of single power plants and try to look at how power plant dispatch has changed in the context of an evolving energy system. Beside being an academic, I'm also a rather lousy actor in an amateur theater group here in Berlin.

Chris Adams: Cool, thank you. So you said you're working in a theatre. Are there any particular roles you play or anything like that? Because I think you may be the first actor who's come onto the podcast actually, Kiara. Chiara.

Chiara Fusar Bassini: Well, I have a tendency to take on the roles of either mad people or police men or like with gender changes. So anything in between is business, usually like mad people it has been, like the latest role I've had was a police officer. And before that I was a mentally ill person.

Chris Adams: Wow. I did not, I was not expecting that. Okay. All right. Well, welcome onto the show. And I guess that maybe we'll see some, productions in future. Folks, if you're new to the podcast, my name is Chris Adams. I am the executive director of the Green Web Foundation. That's not the same as the Green Software Foundation.

It's one of the members of the Green Software Foundation. I'm also one of the chairs of the Policy Working Group and also one of the hosts of this podcast. Okay, so before we talk in depth about your research, I just want to check for people who are also listening to this, you've been doing this research under the supervision of Professor Lynn Kaack, I believe, is that the case?

Chiara Fusar Bassini: Precisely. We've been working with her for a few years now, each of us.

Chris Adams: Brilliant. Okay, so what we've, the reason I'm sharing this for listeners is that we did an episode 5, where we spoke to Lynn and another person, Will, oh his name has changed, I think it's Will Alpine now, talking all about climate change and AI, two years ago. So if you enjoyed this, I would suggest looking at that to learn a little bit more.

And that might provide some extra context for this discussion. All right, then. Are you two folks sitting comfortably? Happy to go ahead with this?

Silke Kaiser: I think it's good to go and share insights on our research.

Chris Adams: Good stuff. Thank you. For anyone who is listening as well, the thing I'll just share is that we will share show notes with links to all the projects and papers that come up to this. So if any of this is interesting to you, then yes, we, you can continue your quest for more knowledge and insight outside of this podcast. All right. Silke. Let's start with you. Your research focuses on predicting cycling traffic in cities using data from bike sharing systems. And this is something I believe you worked with Lynn and another researcher, Nadja Klein, on from this. Could you maybe just explain a little bit about how this actually helps people when they're trying to design how people move around in cities like, say, Berlin or Paris or things like that?

Silke Kaiser: Yes, I'd love to. So what we generally see when we think about transport in cities is that public space in cities is limited. Whether it be in Europe, the USA, or any other place. Generally, then when we think about how we want to redistribute the space among different mode shares in city, we see that there often tends to be a heated debate.

And especially as we work towards promoting more sustainable modes of transport and therefore reducing the CO2 footprint of our cities, conflicts often arise. And the question then remains, how do we actually want to prioritize these different modes of transport and allocate the space and also financial resources among them?

So, for example, take Paris as an example. I've lived in the city for several years during my studies. And what you can see in the city that in the past few years, they made a lot of changes to prioritize cyclists, which has improved the uptake of cycling, but which has also led to quite heated debates.

The same we can see here in Berlin, the city that we're currently both located in, is that we had a re-election last year here in February, and a lot about the debate actually hinged in part on the choice between prioritizing cycling and individualized motorized transport. So what I do try to do in my research is actually to provide more data to this debate, because what I see as the main challenge in these kinds of debates is that we don't have accurate data on how much cycling traffic we actually have in cities.

Chris Adams: Ah, okay. So maybe just kind of dive into there. So it's basically, we don't have the data to really have a data informed discussion, basically. That's one of the things that is the challenge here. And for context, so the three of us live in berlin. We saw, basically, the new government and the new mayor come into power on a very kind of pro car platform, basically.

So this is what you're referring to, right?

Silke Kaiser: Precisely. So, answering maybe the first part of your question, so for example, in Berlin, we have only 40 locations where we count cyclists. I think in Paris, it's around 53, in New York, it's 41. And then in Berlin, for example, we have around eight times more locations where we count motorized traffic. So we just have much more data and much more information on motorized traffic than we do have on cycling.

And then yes, in Berlin, actually, there was quite a bit of a heated debate pretty much between let's say the inner city, which was more pro cycling and in the suburbs, which were more likely pro cars. The government switched from a green to a more conservative government, which actually decided to suspend actually just this month quite some, projects, long distance commuter paths, and both bicycle parking houses in cities.

But that's just more really on the political side of the debate. And then what I really see as the main challenge is that just this data and the information is missing on where we actually would need the infrastructure most, given how much we want to prioritize cyclists.

Chris Adams: Okay, so maybe I should ask, where is the data coming from then, for this?

Silke Kaiser: So, we do have these 40 counting stations in Berlin, that's the case study that I'm looking at, and what we then figured is, well, we don't have that much precise data on cycling, but we do have an abundance of other data on cycling. So, for example, we do have, as you mentioned, the bike sharing data. We do have as well data from Strava.

That's an app popular to record yourself while doing sports. We do have data on infrastructure, we do have data on weather, we do have data on socio economic factors. And we figured, well, why don't we use all this available data to actually extrapolate from these few isolated locations to actually obtain city wide estimates.

And that's what I did in this research with Lynn Kaack and Nadja Klein. So what, precisely we do is that we train various machine learning algorithms to use all this kind of data in combination with the cycling counting station data that we have to obtain citywide estimates. And what we actually found is that only using this data is a bit tricky.

It provides us estimates for completely new locations 32%, which is you know, rather good in comparison to having no data at all, but still 32 percent is an error I take seriously. And what we then simulated, continuing with this research was, what if we make some sample counts for new locations? So for example, if I want to estimate the traffic in front of your house, Chris, the cycling volume in front of your house, we figured that if we would maybe put you, someone else, on an automated machine there to count the cyclists, and we were to count the traffic for 10 days.

And then combine it with our models, we're able to get estimates with an error of only 17%, so really rather low for complete new locations. And this gives us a good estimate of how much cycling traffic we actually have in every single street of a city.

Chris Adams: Ah, I see. Okay, so you're using the machine learning model, basically, to make the extrapolations when there's, there might not be so much data, give you more accurate so you can say, "well, I'm more confident that this many people are trying to get around using an active, non gas burning form of transportation," for example, right?

Silke Kaiser: Precisely,

Chris Adams: Ah, okay. All right. Thank you for clearing that up. And I understand. And just, we'll come back to this a little bit later, but you said you're using ML. not the same as generative AI or something like that. That's a different, there's, a whole flavor of different things you might be using there, right?

Silke Kaiser: precisely. I mean, there's many different models out there. In this paper, we used rather simple machine learning algorithms, nothing comparable to maybe what most people think of when they think about chat GPT or whichever generative AI you might think about. Those are really rather simple models making usage of the data we have.

And those models So, I just tend to have, I sometimes, you know, sometimes I think about, I mean, you can target these problems with very complicated algorithms, but sometimes using rather simple algorithms might just be sufficient. And that's what we actually found in this research.

Chris Adams: Okay, alright, thanks. When I was doing a bit of research, I realized that you also wrote a piece around, I think in a publication called Catalyse, where you're talking about active transport and why it's important for greenhouse gas emissions, because you've spoken about like mode shift, which I assume means basically moving from a Being in a car to moving and maybe a active transport, which people use like scooters, bikes, stuff like that.

That's what I think you're referring to there. Could you maybe talk a little bit about how this research actually contributes to like the adoption of cycling as one of the potential modes, because you spoke about it in Paris and I went to Paris and was being pretty transformational when I was there compared to being a few years back.

And I also bike around Berlin too. So I have a vested interest in learning this. Maybe you could like lay out why that's actually benefiting and how active transport helps. Basically, us meet our climate goals.

Silke Kaiser: Absolutely. So, when I, Referring to other research that I've read, research that I haven't done myself, but it is out there and it's been cited a lot, is that we do see that cycling has numerous benefits. It benefits your individual health. If you cycle, it's good for your physical health and then all the sicknesses or illnesses related to insufficient physical health.

We can also see that if you cycle, it's also good for me because then generally we see a reduction in noise and air pollution in cities. So it really benefits the public health, the broader public. And then yes, absolutely. I mean, I did read the IPCC report, which is a report on climate change and it comes out, the last one came out in 2023.

And what they found is that actually 15 percent of net global greenhouse gas emissions are related to transport. This of course includes all kinds of transport, but also, one of them is urban transport. And then switching, there are many levers how to tackle this, right? And within general, as in climate change, there's no one solution fits all, but switching from motorized traffic to cycling is one of those means to actually reduce those greenhouse gas emissions.

And coming a bit back to my research as well, what we find also in research and science is that all you can think about, you know, talk to your friends and family and gather some anecdotal evidence, you'll probably find that one of the biggest deterrents that keeps people from cycling is that they actually are afraid because there's not enough cycling infrastructure.

They're afraid of accidents. And that's a relevant fear. We do see many accidents in cities right now, mainly between motorized traffic and cycling, but also all kinds of other accidents. And what we do can do in cities is, to actually promote cycling, is to build more attractive infrastructure for cyclists.

This can include bicycle lanes, a better design of roundabouts. And all this attracts people to cycle, but, it actually also reduces the risk of serious and fatal accidents. So what I really try to do with my research is that again, if we have these heated debates in cities, how we want to distribute space among cyclists, cars, delivery trucks, etc.

I'm trying to provide data on where we actually have how many cyclists in which street, so that when policy makers or transport planners come around, they can use my data and actually make fact driven decisions when and where infrastructure benefits the most, the greatest number of people. And that's how I hope my research can contribute

Chris Adams: Ah, I see. Okay. So that's really helpful. And I think there are some kind of comparisons I can make, which make to maybe help me understand if, and some of the listeners. So you know how a couple of years ago, in the middle of the pandemic and COVID, one way to reduce the number of COVID cases was just to reduce the number of people taking tests, right? You know, that's not necessarily the best way to solve that, know, and it feels like

we've got a similar situation. We've got a data asymmetry problem here it looks like you're doing some work to address for that. I mean, Also, you've spoken about, as I understand it, there are various parts of, like, our economy which are easier to decarbonize than other ones.

Like if, for example, in Germany and in America, transport's the biggest, one of the places where we've seen not so much progress on reduction, on carbon emission reductions compared to things like the energy sector and stuff, which is decarbonizing relatively quickly. So this is what some of this is a reference to. Okay, so what we'll do is we'll share some links to Catalyst, I'm sorry, Catalyse, the paper there, and also some of the papers that you have. So we spoke about Paris, and we've spoke about Berlin, where we both live. Are there any other places you would point people to as examples of, okay, this is what good might look like, and this is one place which actually has quite good data to show where you've actually seen quite effective policymaking to kind of change the environment to make it easier to cycle? Because, yeah, not everyone wants to become a MAMIL, like middle aged man in Lycra wearing the helmets and everything like that.

Silke Kaiser: So, I mean, there are definitely some cities that you know that are popular for cycling, for example, just earlier this spring, I did a research day for some months in Copenhagen. And obviously Copenhagen is a bit of a dream for cyclists, right? I'm not the first one to mention this. And then there are other cities, Amsterdam, you name it, but generally I do have to admit that in my research, I haven't really come across cities that do have much better data.

I would say it's a grasping problem across different cities that data is missing. Copenhagen and Amsterdam have taken political decisions to prioritize cycling, but I do have to admit that I didn't, I haven't come so much across that they've made this as a data-driven decision, but this was more of a political decision.

Chris Adams: Ah, okay. And there's one thing I'll just ask before, Chiara, I'm, okay, I am a closet energy, well, not very closet energy nerd. I'm totally gonna, looking forward to talk about that. But Silke, I was just going to ask you, so you mentioned use of Strava and you mentioned the use of, Okay. It's useful to have these new sources of data, but there's also a question about the provenance of that data and like the circumstances under which it's collected.

So for example, we've seen Strava used in lots of other places and if you're using Strava, you tend to be a bit richer, a bit younger, a bit healthier than most people. Maybe you could talk a little bit about some of that, because there are various sources available to inform these policy sessions, and like, Strava is one.

But like, where else, like, assuming you had, you were suddenly queen of the world, where would you wish you could get some of the data from to kind of inform this in future?

Silke Kaiser: So you're absolutely right, Strava definitely is quite biased. It's the data, for example, for Berlin, I definitely know that they're all male, they're mainly male, young, and they do tend to do very sporty biking in comparison, for example, what I probably do to commute work. So it is true that some of the data we use is biased and we're trying to balance this off with the other data sources that we're having.

We're also taking socioeconomic factors into account because obviously we do not want to have, infrastructure is meant to be there for everyone and not for privileged or less privileged people. It's, meant to be equal for everyone. But then obviously I thought about a lot, well, how could we actually improve the data availability in cities?

And I definitely see two levers that we have. Well, first of all, we can place more cycling counting stations. That is a bit challenging because, for example, we have so many kilometers of roads and it's hard to track them all. There are cheaper options than the ones that we're currently employing. So this might be our one option.

Some of them are then using cameras, for example, that are just much cheaper to put them out there. And then the other question, and that's something I'm also looking forward to, to answer this question is because I'll be looking at this in my future research, is that actually how can we place the sensors that we have better across a city? Because currently look it up again for your city.

You'll probably find a similar image is that we do tend to place these censuses as very busy and scenic roads. And the question is actually, can we maybe place them at more diverse spots within a city? And if yes, how can we choose those streets to place those sensors at to actually get a more comprehensive image of the cycling traffic and then also of all kinds of socioeconomic areas and a more equal data image.

Chris Adams: Cool. Thank you for that, Silke. All right. We'll come back to you a little bit later about some of the specific techniques that we were using, because we spoke a little bit about ML and there's a lot more we might dive into there. Chiara, if it's okay, can I ask you a little bit about your research analyzing European energy data?

Because you didn't hint a little bit about how this can affect renewable energy transition, and one of the, one of the things that Germany has in particular is a target to have 80 percent of the grid running on renewables by in, wow, in five years. So that's not much time, and we've also spoken about on the grid, we've spoken about things like time shifting and location shifting as a kind of carbon-aware software, particularly in changing how data centers, like, fit into the grid, I suppose, or the energy they use. Can you maybe talk a little bit about some of the challenges you've found actually working with this data hands on? Because we At best, most of us developers, we might use it in a really nice, pretty fashion from electricity map or Watttime or in an SDK, but it sounds like you're pretty much at the front end having to figure out how the sausage gets made. So yeah, if I can ask you, maybe you could tell us a little bit more about how this data comes about and what are some of the challenges.

Chiara Fusar Bassini: I mean, if you've been using Electricity Maps, you probably have been using an application that in the back uses NSOE data. So you, in Europe, we are rather lucky because. There have been two regulation that have been released in 2011 and 2013, which forced in a way transmission operators to publish a variety of a time series of energy data from the grid and from the markets in an effort to increase transparency. And we have a number of data in a central, on a central repository, which is called the Transparency Platform. We have load data, we have generation data, we have transmission data about the grids, we have balancing data, balancing markets, but also a lot of information on individual power plants. This data is overall extremely useful, but unfortunately it's not Always accurate and it's not always complete and not all the data is not always published in a timely manner.

That very much depends on the type of data, the country itself. We are still very much better off than other markets where there's no data at all. But it's still an issue of like how good and like what the data quality actually is. Because you mentioned time and location shifting. To do time and location shifting, most likely you will be working with aggregated data.

For example, load data, load data, load forecast data. And. One could analyze, for example, a load to decide whether to shift more energy consuming activities at night or at moment where there are off peak time windows. And on the other hand, one could look at aggregated renewable generation data to try to relocate some more of energy consuming activity to time of the day where the grid is actually greener and there are a lot, there's a lot of interest in academia, but also in, in the industry sector to provide us information, to have an estimate of carbon intensity. there are a number of startups out there. You mentioned Electricity Maps, but also academics have come up with top, bottom up, top down and bottom up approaches to compute really at hourly or quarter hourly level, these carbon intensity estimates. The trick here is that you are working with, the aggregated data and aggregate the quality of aggregated data and the timeliness of aggregated data is rather high, the situation is a little bit different when you move to a more geographically granular, like a higher geographical granularity.

Chris Adams: Okay, so from Germany going to like Berlin or Germany going to another part like Frankfurt, for example, something like that. Yeah?

Chiara Fusar Bassini: Rather, when you're looking from, the aggregated generation to the generation of individual power plants, because in that sense, you might be interested to know which power plants are actually generating right now. And you might be interested to know which areas are generating more solar, for example, which areas are generating more wind. Unfortunately, we don't have data on all power plants. Which would be rather impossible in terms of like amount and extent of the data, but we have only data for power plants that are at least 100 megawatt. It's mostly conventional power plants. So, for example, we have no individual information or very little information on wind farms, for example, because Some of them are not big enough to qualify for this criteria. And also this data get published with a significant delay of four days so that you can't really use it to

do anything operational. It's also not conceived for that. And we can or we cannot use the data to properly, like we cannot do it for, we use it more for analysis than for forecasting, but nonetheless, we can use this data to understand a lot on individual power plant data, why they decide to dispatch on how they are dispatched, and especially in the context of conventional power plants, how their dispatch has changed over time because of political reasons, but also because of the increase in cycling of fossil power plants, because they have to adapt to the renewable energy generation, to more renewable energy generation.

Chris Adams: Can I just quickly stop? I just want to check I understand some of the terms you've used for listeners who might not be familiar with load, cycling, some of these things here. So when you talk about loads, you talk about energy, like basically that's power draw, what people are trying to draw from the grid.

You mentioned that. And then you also mentioned, I think, like cycling. So that's like basically scaling down a power station in response to there being loads of wind on the grid or stuff like that. Maybe is that about right?

Chiara Fusar Bassini: Yes. Thanks for asking. So to clarify, so load means the demand and in the past, I mean, demand, especially from, industry, but also from household, it has been rather predictable. And the way we faced demand, or we satisfied demand, because well, in an energy system, demand and supply need to be equalized at any time. In the past, the most of the baseload, so the main bulk of consumption, have been satisfied using traditional fossil fuel technologies, so called dispatchable, because you can, decide when and how to switch them on and off.

Chris Adams: Ah, okay.

Chiara Fusar Bassini: But the thing is, as more and more renewables enter the grid, they cannot be dispatched whenever, they can only be dispatched, or they can't choose when to dispatch a

Chris Adams: Yeah, control the sun and the wind. We can just respond. Yeah.

Chiara Fusar Bassini: They just respond to external weather factors, right? But that also implies that we still have these conventional power plants that are

dispatchable, but we now have to operate them with increased flexibility. So they have to be able to ramp up and ramp down as the load is more and more satisfied by renewable energy sources.

Sources when they are there. And we always make the assumption that say conventional power plants are a hundred percent flexible, but that's not actually the case. For example, some power plants, when they are turned on, they have to generate a minimal capacity. And if the demand for that capacity is not there, that might be an issue, or they might have some minimal times to be switched on and switch off.

So there, there is a plenty of interesting question that arise from the increase of renewables. Like how will conventional power plants cope with more renewables in the grid?

Chris Adams: Ah, I see. Okay. So one thing you're saying, she's like, yes, it's not like a computer. You can't turn it on straight away, like in milliseconds. And so that's one thing you mentioned and the fact they need to do that more is another issue. And if I understand it, what you described was quite a physical process.

It's like, we're not using bits, we're using atoms, like burning coal, things are expanding and contracting. Like, is there a risk that, you know, the, a big power plant could be damaged some more, or does that introduce any wear and tear when people need to scale something back? Because I can imagine someone saying, "hey, you're making me change how I do things, and therefore you're introducing some risk into this.

That's not what this was designed for in the first place."

Chiara Fusar Bassini: Yes, that's actually a very interesting question. What I mentioned, cycling, meaning that you operate conventional power plants more flexibly, has some consequences on the lifetime of power plants, especially if you keep on turning it on and turning it off. There are some wear and tear indeed for thermal power plants, wear and tear consequences, some of some power plants may not even be able to do so because they have some agreements with O&M managers that tell them, you know, "you can do that, but then you'll have to pay more because you will have, we'll have to do more main maintenance." And also, there are a number of obstacles that arise, especially for older power plants that have not been conceived with this flexibility option in mind, but rather to satisfy baseload.

Chris Adams: Ah, okay, thanks for clarifying that. And you're essentially doing some of the research to see how you might predict some of this better to either reduce or basically accommodate some of these changes that we might have when we've got a much more dynamic grid that is influenced by the sun shining and the wind and all the things like that, right? So maybe if we can talk a little bit about some of the techniques being used to track this and reduce the amount of, maybe, reserved capacity that needs to be done, or reduce the amount of wear and tear that might be imposed on the kind of entire system full of all different power generation. You said you spoke a little bit about using machine learning, and We spoke to Silke.

Silke mentioned that she's using some ML models, which are not like generative AI. That's a very, it's a different kind of AI. Could you maybe talk a little bit about like how that gets used, because you hinted at it, and like what some of the barriers are for using some of that, because it, that sounded quite enticing and interesting.

Chiara Fusar Bassini: Yes, before, before that, I might, I want to add on this. So there is some parallel research being done, especially like at engineering department of a lot of engineers trying to use machine learning to efficiently operate conventional power plants to reduce this wear and tear of wear and tear problems.

And in general, like damages from cycling while still satisfying a change in demand. What I'm doing is and Rather different analysis of historical usage of power plants. So to see how power plants are, have actually been operated so far in the markets, how they're, how they, how flexible they actually are.

Because sometimes we assume that they're 100%, again, we assume how they're 100 percent flexible, but how flexible are power plants that we already have in the grid? And also how available are there in cases of outages, for example, how, like. What's the percentage of time in the year that they actually could provide electricity, for example? And in terms of techniques, well, it's a lot of time series data, so most time series apt methods can be used here. It very much depends on the ultimate task, but one of the major obstacles I encounter is that this high granularity data is by far not as good as the aggregated data, especially, for example, an availability of power plants that has to be reported in a rather accurate way, but then is not one to one translatable to time series format because it's published as market messages, meaning that the data that we have is not in a format that makes it directly usable for a researcher. So there there are a number of obstacles that are really determined by the data quality rather than by the task itself.

Chris Adams: Ah, okay, so it comes down to the data a lot of the time then, basically, yeah?

Chiara Fusar Bassini: Again, like as Silke said, sometimes it's really just a matter of the data that you have, like the research that you can do is going to be determined by the quality of the data that you have.

Chris Adams: Okay, we'll touch on that a little bit later, but I guess the, that does make me think about, particularly in Germany and countries where we've seen very rapid changes. Like, Germany, there's, you know, there's a massive craze of balcony solar, for example, or we've seen loads of battery coming onto the grid, or even Pakistan. We've seen, like, a third of the power, the new power introduced this year, was come from rooftop solar, and each one of those is individually less than 100 megawatts. That's an enormous chunk of power. So there's all this new stuff that we're not, don't necessarily have access to the data for to actually figure out, okay, how will the grid work and how can we make sensible predictions on this? That's useful to know. Brilliant.

Okay. So we're speaking a little bit about the upsides and how, where some of the potential might be. We do speak about Green Software, about reducing the environmental impact of some of this, and obviously when we're doing some of this work, I've asked a little bit about the kind of models you might be using, partly because there's a question, whenever we start using technology to help us meet climate goals, it's when some of that energy is still coming from burning fossil fuels, for example, there's trade offs to be made. Does anyone want to go first, talking about how we think about these trade offs? Because as practitioners, I imagine you're at the coalface, but you're also working with some of the people who think about this every single day. And like, if you're working with Lynn, and like, Lynn was one of the founders of Climate Change AI, I reckon she probably has some reckons and you've probably had some conversations about this, right?

Silke Kaiser: Absolutely. Actually, just, I think just the last group meeting we had, we just discussed about precisely this topic, because it obviously, it is a question that keeps coming, a question that we do want to answer. And it is also like, it's in our minds, right? Because if we want to do something positive for the climate, and then actually, the net result might be negative, because our models consume that much energy.

This definitely is a topic that we think about a lot, I would say. I see Chiara nodding. I think she's agreeing with me, but, and I can see that maybe to the outside world, often this can seem a bit like, I like the term of fighting fire with fire, you know, you, you're trying to make it better, but you're making it maybe even worse, but I think if we make some smart choices along the way, I rather like to compare it to the idea of fighting a forest fire with a controlled burn. So right, that we do try, for example, in, in the models that I was employing, I did partially check how much, how big the energy usage was.

I was using simpler models, as I mentioned earlier. So the energy consumption wasn't that high, but I think it's good for us and for everyone out there using, similar models. To track your energy consumption and there are very nice packages and libraries out there, tools, all kinds of things, open source, freely available that are very good in, in managing or in measuring the energy consumption you have.

And then of course there are a whole bunch of other approaches that you can take. Right? I mean, you mentioned it's an issue if it comes from fossil fueled energy, but obviously you know, you can think about, I know that there are a lot of like. Service and data science centers, for example, out there in Iceland, where you tend to have more natural cooling, where a lot of the energy being produced is renewable.

I'm not saying that at all perfect, but what I'm trying to say is that there are different approaches that we can actually also reduce the emissions caused by AI.

Chris Adams: Ok, so there was one thing about the actual technique, like, AI is not a monolith. There's all different approaches within this, in some ways, not particularly helpful term, like the use of relatively small machine learning models, which are relatively simple, that's going to have a totally different footprint to the model used to generate SOAR, like a video or something like that.

And that's something that we probably would benefit from having a better kind of intuition off as practitioners, for example, and you spoke a little about the carbon intensity. So there's two, two things that you have there. And you mentioned some software that you have. And you said that, Chiara, if I can kind of give the floor to you, because I think you mentioned you, you've spoken about some of this before about, yeah, there are some tools and I use them as well. Can I ask you a little bit about when you've been thinking, I mean, how do you think about these trade offs? Or is it a trade off? Or is there another set of dimensions you might be thinking on rather than like forest fires and controlled burns, for example?

Chiara Fusar Bassini: Yeah, I think, there are two things that need to be thought through when using AI. Number one is like, how do you develop your model, and then what do you use your model for? So how do you develop your model? That's similar to what Silke said, for example, doing emission emission tracking while developing the code and while training the code. And at the moment, I think AI is missing some embedded indicator of the social environmental cost of the training. So. We kind of think of performance metrics such as accuracy, such as like classic cross entropy losses and so on, and we think only about precision. But sometimes we need to be a little bit more critical of whether an increase of accuracy of 0,1 percent is worth an increase in the training time of two hours or an increase in the size of the model of 25%. These are like actual numbers and scientists have coined for that the term green AI, meaning Okay, can you know, can we, in a way, embed this measure of the size of the model within the loss that we are trying to minimize in the training of our model? There is another, a good example, for example, is the Bloom model that is an alternative large language model to GPT. It is similar in size, but it required Like the CO2 emissions of the model are 20 times lower than GPT 3. And this has been made possible by, first of all, in smart usage of the training and also tracking of the carbon intensity of the grid. It system was trained, the model was trained mainly in France, which is, which has runs predominantly on nuclear power. So in like carb, much more carbon neutral system. So there are a number of things that one can consider while training their model. But also another thing that is very important, and I think that we sometimes don't really think through, is what are we using AI for? And in that sense, there is currently no standard assessment in place. Like, is this application really worth using AI? AI is, by its nature, ethically neutral. It can be used for anything from targeted advertisement that will have probably a negative impact on environment to detecting wildfires. So very positive impact. I think policymakers in that sense can make a great deal to really make a difference and start, for example, by providing a classification of which user cases are positive for environment and which are negative. It sounds, it may sound like science fiction, but it has already been done in the European AI Act in looking at the perspective of risks, like which application have a high risk and hence should be more controlled and which other have lower risk. And I think a similar classification would be also very useful for environmental purposes.

Chris Adams: I'm really glad you mentioned that because I ended up reading through the AI act for research recently. And the idea of the risk that is, you're right, there doesn't seem to that much be that much reference to the use of AI for, let's say, you know, increasing the extraction of fossil fuels, right, versus that.

That's, there doesn't seem to be much to mention about that, but there is some information about the transparency around training. And now that we've looked at it a bit closer, so within the Green Software Foundation, there is a group called the Real Time Carbon Group. We've been looking into some of the specific implications of this, and it looks like the AI Act, it also, it looks like it's probably going to suggest not just understanding the training, but also the cost of inference, like the use of the model rather than just the training of the model. If I can just quickly, you've, you, mentioned there are tools out there, and Silke also mentioned there are tools out there. If I did want to measure some of this, and if I did think there was some legislation coming for this, what tools are there available for me to measure the direct impact? So at least I know what the trade off might be.

So we understand that the carbon footprint of decarbonizing transport, like Silke mentioned, that's going to be, you know, positive, but quite, but there's ways of calculating that, but for us as practitioners, are there any software or any tools you might recommend that are kind of common in the field now? Either goes. I'm happy to, whoever's more comfortable talking about this.

Chiara Fusar Bassini: I'm thinking CodeCarbon is more probably a standard used by many scientists. I know there are more applications that might have a higher granularity, but I guess that's a

Chris Adams: That's the one that you folks have used, right? Okay, I hear CodeCarbon used a lot, and I, as I understand it, that's the one that's been used for the Bloom model when they wrote a paper about that. That's what I'm not sure Facebook have actually explained this because when I was looking at LLlama's model, so AI models have model cards, which basically, which I think, various responsible practitioners now say, "this model took this much carbon, or they had this much energy gone in to kind of create it," for example, if you go to the existing Llama 3.1 model card on Hugging Face, and you try to follow a link to the actual methodology, It's not actually explaining how it works. there's now a bug. I filed a bug to ask out, ask, well, how did you work these figures out? Because these feel like it's quite important, especially because when you look at the numbers, it's significantly larger than Bloom, basically. That's, so, so what you're referring to is CodeCarbon. That's one tool that people can use that will give you some idea that is in use in a few places already that's relatively safe to start off with. Great. Okay. And we spoke a little bit about some tools. So if someone is, wants to take their first steps, they might look at this.

And there are various projects I'm aware of to make it a bit easier to understand the impact of one versus another. I believe there's one Energy Star AI or Energy Star, AI Energy Star or something like that. There's one person who I've spoken to who's involved with it. Boris. I'm so sorry I can't pronounce your surname, but I do know you're the AI lead, the AI sustainability lead at Salesforce. Boris G is one of the people who's been writing about this. He's not the only author, but he's the person I know, and we'll share a link to that as well, because that's the first thing I've seen of a useful, like, A kind of nice idea to give you an idea of what the inference, the usage as well as the training might actually be. If you were to look at this, we've still got this issue of data or having access to data like, and Silke, I ask you, if you were like queen of everywhere for a moment, how would I change it for here, right? Let's say that you want to be responsible AI practitioners, like what are the things that we need to see in the next, in the coming years to make it possible to be like responsible practitioners so that when we do use AI, we're using it in the kind of greenest possible fashion. Silke, I asked you first about Queen of Everywhere, so maybe you go first and I'll hand over to Chiara.

Silke Kaiser: Well, that's a very good question. I definitely say, as in general, with all kinds of, you see, in more technical approaches, we do need reproducibility and traceability of what we do in our research. I mean, just as you mentioned with the Llama, I think it's important that other people are also able to understand what we did, what was the energy consumption of what did, how can they, how can we check the things that we've done and, see if, we did it properly, if it took a right approach?

And then obviously, I think this is a bit less related to, the topic that I'm or that Chiara was working on, but also in the longterm, we do need to think about ethical concerns coming down to this. And then again, I think just, really, transparency. So I really think that transparency is a good way to address this.

What take do you have on this Chiara? I think one of my major takes also from what Silke mentioned, and I'm really glad you mentioned, is the fact that when we were talking about policy making is that very often policy making is not data-driven. One problem is that we don't have the data and it can be addressed partly by regulators asking for those data, right? But another issue is also that we don't really do data-driven assessment of the policy that we implement then. And I came across very recently a paper that tries to systematically evaluate policies.

And having been implemented in the last 25 years, this very recent paper has been published like a few days ago.

And I thought it was very interesting to well, once again, the results of the paper is there's no one size fits all and some countries depending on their level of development might need different policies. And we have to keep that in mind that we can't use the same policies for a developed country whose energy consumption, for example, is no longer linearly dependent on its GDP from a different, from a developed country or a developing country that has very different issues. But I think in general, this approach of doing data-driven policymaking and science-driven policymaking is something that would really, we would really need in this space.

Chiara Fusar Bassini: I think that's something I can really agree on. I often feel that as a scientist, we feel like we're trying to really produce clear results, objective results. And then often we feel there's maybe a bit of a lack between the two. The research that we do and how much this is sometimes uptaken, by policy.

And obviously we hope that because we do really put so much effort into this and always try to be objective. We hope that this will eventually be more used more and more in the policy sector.

Chris Adams: You've touched on a really interesting point, and I can think of some examples that just occurred to me. So, we had an interview with, oh, Vlad Kor, his first name is Vlad, I'm gonna mispronounce his surname, but we spoke a little about, all about the rebound effect, and Vlad Coraoma, that's it, Vlad Coraoma had this lovely post actually on LinkedIn talking about the curse of potentialities, potential itis, which is basically talking about, we have all these kinds of really exciting projects, but whether people follow through to check whether the actual gains materialised, or the benefits materialised, there's much less effort put into that.

And we've been seeing, like you said, Chiara, from the last 25, we've been seeing predictions for things that would happen in 2020 or 2030. And 2020 is in the past now, we can check if this is, if these actually delivered, but a lot of the time we do not see that. And in our field, specifically as kind of cloud providers, or people who might be consuming services, there's some, there's a really, I'm thinking of a really good example. Microsoft has a whole thing about pushing for AI and everything like that. And we know that, as you mentioned, AI can be used for good, and can be used for bad, or used for Climate aware things, which are really helpful and things are not so good. And we've even seen like people who are workers really pushing for this. I'll share a link to an article in Grist where, written by Maddie Stone, where she talks about some of the sustainable connected community inside Microsoft, speaking to some of the management there. There's a guy called Darrell Willis. He's the vice president of energy. And they spoke and said, "hi, we are pushing for," you know, "can we please have a conversation about what we're using AI for inside our company, because we're one of the largest companies in the world and we're one of the leaders in various industries," right?

And there was a commitment to say, we're going to produce, as the management said, "we're going to start releasing information about, okay, how much of our use of AI is coming from the fossil part of the industry versus the renewable part of the industry?" And this feels like a really important data point if we're going to be looking at tens of billions of dollars used on AI.

I mean We know that it's an accelerant. If it's an accelerant of fossil fuel extraction and burning, that's a very different story to using tens of billions of dollars for renewable energy, for example. And if we've seen commitments at a management level, then it would be nice to see these. As we understand, these commitments were made, these were shared inside the team, but we don't have this, and we'll share a link to the specific terms, because actually, I'll just share the quote with you, because I think it's one thing that, if you're an employee of a cloud firm, or a customer of a cloud firm, it's the kind of thing you might want to know about, so on the call, "Darrell Willis, committed to providing employees with updates on net zero requirements as Microsoft continued to implement these energy principles. Committed to providing a breakdown of energy divisions revenue across six different sectors from oil, gas extraction, to all zero, low to zero carbon energy. So sharing this information internally." Now this feels like a thing that employees probably should be aware of or asking for. Also feels like something that if you're an investor of Microsoft or a customer, you might want to know.

Because there's an impact inside your supply chain thinking about this. And if you're choosing one provider because they have really strong GSG credentials, this may make you view it somewhat differently. We'll share the links because it seems to be the best concrete example I can think of at significant scale that we might be talking about. And I'll get down on my soapbox because that's just the thing that really leapt out when I, when you spoke about that. So we coming up to time, and we've spoken about the different uses of AI, sustainability of software, as well as some of the Things you might want to use or be aware of as a practitioner. If people do want to find out about the work that the two of you are doing, where should people be looking? So Silke, if people are interested in your work, is there a LinkedIn page or is there a website that you direct people's attention to?

Silke Kaiser: I normally try to direct people to my personal webpage, which is silkekeiser.github.io. Or you also, you can also find me on X or on LinkedIn. And I'm always happy to share news on my research as well as the articles that are out there. And I'd be happy to, if people were to look at those pieces of information.

Chris Adams: Cool, thank you. Alright, and Chiara, if I just hand over for you?

Chiara Fusar Bassini: I've seen Silke's website and you guys should really see it.

It's a very nice animation. I don't have myself a website, but I'm very active on LinkedIn. You can find me under Chiara Fosar Fusar Bassini.

Chris Adams: Chiara F U S A R, we'll put it in the link, we'll add it in show notes. So, Chiara Fusar Bassini. Brilliant. Thank you, folks. This has been lots and lots of fun. I've learned a lot from this, and this has been a really nice chat. Hopefully, we'll cross paths sometime in Berlin, but otherwise, thanks again for coming on, and have a lovely week.

Silke Kaiser: Thank you very much for having us.

Chris Adams: Ta ra! Hey everyone, thanks for listening! Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again and see you in the next episode.

View Details

TWiGS host Chris Adams is joined once again by Gaël Duez to discuss the latest news in green software around AI. They discuss insights from recent reports by Google, Meta, and Amazon, as well as looking at the implementation of the GSF’s Software Carbon Intensity metric. Similarly, the conversation touches on the distribution of renewable energies and the use of different means of measuring carbon in reporting, and how this can affect the behavior of consumers and organizations alike. Tune in for an enlightening discussion on the latest in green software.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Gaël Duez: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Green Coding AI [05:02] * Sustainability: How Did Amazon, Azure, Google Perform in 2023? - The New Stack [19:33] * Big Tech’s bid to rewrite the rules on net zero [34:20] * Can AWS really reduce the carbon footprint of AI workloads by 99% or is it 'greenwashing'? [43:36] * Are the CO2 emission reductions promised by cloud providers realistic ? | Boavizta [44:44] * Mark Butcher on LinkedIn: #sustainability #scope2 | 58 comments [45:09] * AWS, Digital Realty, Google, Meta, Microsoft, and Schneider Electric call for greater supplier transparency on Scope 3 emissions

Events:* Green IO London 2024 [1:01:15] * CNCF Cloud Native Sustainability Week 2024 [1:05:48]

Resources:* The Week in Green Software: Complex Carbon Accounting with Gaël Duez [03:54] * EcoLogits tracks the energy consumption and environmental footprint of using generative AI models through APIs. [06:43] * https://hotcarbon.org/assets/2024/pdf/hotcarbon24-final109.pdf [11:02] * Making an image with generative AI uses as much energy as charging your phone | MIT Technology Review [15:21] * Energy Star Ratings for AI Models [15:53] * http://CodeCarbon.io [17:02] * https://github.com/mrchrisadams/djangocon-eu-2024-workshop/issues/1 * Marketplace · GitHub [18:40] * Why have Irish energy companies been told to drop 'misleading' 100% renewable claims? | Euronews [30:24] * RE100 TECHNICAL CRITERIA [31:04] * https://github.com/Green-Software-Foundation/real-time-cloud/issues/59 [31:42] * ISO/IEC 21031:2024 - Information technology — Software Carbon Intensity (SCI) specification * Asim Hussain on LinkedIn: Hey, so according to a new carbon offset standard (CCP), 32% of the… | 27 comments [50:41] * Making sense of the energy reporting deadlines for datacentres in Europe * The bigger picture: A data centre revolution - Green Web Foundation [1:00:20] * Green Coding

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Gaël Duez: We cannot fully rely on companies agreeing on how they should measure their own environmental impact, even if they are well meaning, with tons of great people trying to do the right things, etc. It's not a black and white world out there, but there is a question at some point of financial pressure, shareholder pressures in many of these companies.

They're just stronger than the entire stakeholder's pressure.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host, Chris Adams. Hello, and welcome to Environment Variables, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. Round about this time last year, Gaël Duez, the voice of the Green IO podcast, came on to Environment Variables, This Week in Green Software to talk tech, sustainability, and moving from France to live on La Reunion Island.

And the ups and downs of consulting remotely on digital sustainability from a small island off the coast of East Africa. It was a fun chat. And when I asked him if he'd be up for coming on again to review a few of the latest stories around green software, he basically said, "yes, Chris, but I can't do Friday because I promised my daughter we'd pop out to go whale watching." As one does on a tropical island, I guess. So here we are, recording on a Monday morning instead. Gaël, thanks so much for coming back on. Can I give you a bit of space to introduce yourself and what you're up to these days? Also, how are the whales?

Gaël Duez: Oh Thanks, Chris. It's great to be back again on Environment Variables. And the whales were there, like several made quite a show, including a mother and her little newborn. Well, little meaning four tons. So it's always impressive to see there's a 20 tons mammals jump in the air like this and cherry on top of the cake, actually, we saw a lot of dolphins and two turtles.

So it was a perfect trip.

Chris Adams: Wow, I'm jealous. Okay. Yeah?

Gaël Duez: Actually, to connect a bit more on our sustainability topic, I'm also relieved that the best practices for whale watching are more and more enforced, such as, minimum distance to approach them, turning off the engine when they come in, or direction, et cetera.

And, I also say, on top of the pleasure of, watching them and being on the boat, etc. It's a very positive sign that we can enjoy nature without destroying it. And that's pretty cool.

Chris Adams: Cool. So it sounds like there might be, hopefully, when your daughter's taking, maybe some of her kids for whale watching, there's a chance to continue that, by the sounds of things.

Gaël Duez: Yeah, I'd like to focus on whale and dolphins rather than coral reefs, which are something that really is puzzling me, but yeah, we might, hopefully. And to answer your other question, when I'm not whale watching in Reunion, I try to be useful in the tech community, by advocating for more sustainable ways of designing, coding, hosting, and even considering the use of technology itself. And my main tools remain the Green IO podcast, as you mentioned it, as well as the Green IO conferences, which I started to organize in several cities, but I'm sure we'll get back to this point later. And besides, as you already mentioned, besides as volunteering activities, I do public speaking and consulting on systemic strategy for mostly for tech companies, for both paying the bills, but also to have an impact.

Chris Adams: Cool. Thank you for that. I will also share a link to the previous episode if you're for people who are listening, so they can get an idea of some of the other things that Gaël has been working on and been discussing previously. If you're new to this podcast, I should probably introduce myself as well. As I mentioned, my name is Chris Adams. I am the executive director of the Green Web Foundation, which is a Dutch nonprofit based around reaching a fossil free internet by 2030. And I also work as one of the policy chairs in the green Software Foundation, particularly in the policy working group. Okay, and before we dive into this podcast fully, just a quick reminder, everything we refer to, every story, we'll share in the show notes and there will be a transcript as well for you to kind of search through and look into later. Okay, so as per usual with this week in Green Software, We run through some of the latest stories or projects that have caught our eyes over the last few weeks. And Gaël, I should probably ask you, are you sitting comfortably, ready to go?

Gaël Duez: Perfect. Everything is fine.

Chris Adams: Brilliant. Okay. Let's start with the first story then. So this is the first one that kind of came up on my radar. There's a website called Green Coding AI. And we've spoken about the environmental impact of AI on this show multiple times.

We've also spoken about there is different models that you can actually use to maybe ask the same question and get something back. This one is actually a project from, the Berlin based group, Green Coding Solutions. And what they've actually done is put together a service, running on their own hardware, where you can basically try various, models to prompt them to, like, try out, say, Llama 3, one of the big versions, maybe a smaller version of some of these to see, to ask a question and see what kind of responses get back. And one of the things that's particularly interesting in my point, from my perspective is A, the transparency, but also it gives you a software carbon intensity score for every single inference when you ask a question. So you can start comparing the utility of a large model versus a small model. Gaël, I think you might've had a chance to play with some of this already.

When you looked at it, what, were there any things that sprung to mind for you when you first had a bit of a kind of kick the tires and mess around with it at all?

Gaël Duez: Well, what I was pleasantly surprised with is, as you mentioned, the use of the software carbon intensity. I, as far as I know, this is the first time that I've seen it being used for this kind of tools. I know that what is very interesting is that we can see now, not blossoming yet, but several initiatives have popped up with that kind of approach and I need to shout out and at least I need to give a big kudos to Arne and his team because once again it's very thoroughly done for what they've done in Berlin.

What I also like is the work that has been done with another initiative, and I hope that they will start discussing, with each other, which is, it used to be a data for good, project, but now it's a, an, an association on their own called Gen AI Impact. Yeah. So the association is called Gen AI Impact and they created this tool Ecologits, which is kind of just kind of the same approach.

With a very strong focus on transparency, how they calculate everything and all the code is accessible, et cetera. And there is also obviously Code Carbon by Jürgen Fais, which was kind of the trailblazer, if I recall. And I think it says something positive about the trend in the AI industry, that they need to tool up to Assess more and more precisely what is the carbon impact and hopefully soon the water impact.

And that's still, I know that it's not feasible at the moment because of the lack of transparency around water, but we will discuss water later in this episode. I'm pretty sure regarding the other news that, that we have, but it, is very important. I cannot count how many times I've got potential customers or heads of IT telling me what are the tools we can use to measure the footprint of AI.

And Also to use them to push back a little on the AI hype. everything should be AI'ed. I don't know about it. With a pinch of AI everywhere, but it comes with a cost. Now, going back to your question. So I really love the multiplicity of tools that we see at the moment. And now going back to more specifically in Green Coding AI, I think the way they, try to cover all the angles when it comes to energy, having both the CPU joules, the GPU joules, but also the temperature.

It's very interesting because the temperature, it connects a lot with a discussion I had with Professor Lee. One of the big experts on water cooling, especially in data center in tropical island or in tropical climate, sorry, not island. I'm the one on a tropical island, but there are a lot of tropical climate without tropical island, starting with Virginia in US that we tend to forget.

And he was telling me how important it is to understand that there are thresholds when you use a chip. And there's a threshold that impact massively the energy consumption. So it's not the same to have a chip being used around 25 degrees Celsius, for instance, and 30 degrees Celsius. It's just a linear progression in energy consumption versus, temperature.

And I was really delighted to see the temperature being put as a metrics, because that's where we are getting more and more in details and understanding that it's not that easy, it's not that linear, and we need to investigate things in a more systemic view. And the temperature for many people operating data centers, is absolutely pivotal when it comes to anticipating energy consumption.

So I think, yeah, I was very pleased with this CPU temperature metric that they added. I have no idea how they made to calculate it. So that's something I'm going to investigate, but I like the idea of putting this kind of metrics on the table as well.

Chris Adams: So, thank you for that, Gaël. So, what I can share with you, there's a chap, one of the chaps working at Green Coding Solutions, Didi Hoffman, was one of the people doing a significant amount of the work on this, and I've used some of their tooling, they've made open source before, and they basically pull some of the temperature figures from the, from basically the CPU itself, I mean from the system that they use, because for example, most machines can tell you how hot or cold they are, for example.

And that's for pulling some of those numbers actually from. The thing that I might share with you that I think is interesting here is, normally, Green Coding Solutions, they tend to open source as much of the work as possible. And they have one of the nicer tools out there for looking at the environmental impact of pretty much any kind of service, for example.

And the thing that So the, I did actually ask Diddy about this and said, "Diddy, this looks really cool. Are you planning on open sourcing?" He says, "yes. The only thing that has stopped me open sourcing it so far is tidying up because it is a bit of a mess." But the thing we can point you to in the meantime is a paper that he worked with, I think Professor Verena Majuntke from HTW Berlin. They submitted a paper specifically for, to Hot Carbon talking about, essentially being able to optimise different models for optimize the use of AI services specifically for particular tasks. And that paper is really interesting in my view, because they say, well, given these particular tasks, some tasks are amenable to running on small models.

And some tasks are better for large models, for example. And they were basically demonstrating how you can pretty much use a system, which looks at the prompt and then will kind of route it to the appropriately sized model to reduce the environmental impact of this. But one of the things they said was that they can look at the energy used when making an inference like, asking for a response back, but it's still a massive challenge to get any numbers from the embodied energy in making some software. And this is one of the key things that we might, maybe wasn't so obvious when we first spoke about this, that right now there are kind of three broad life cycle stages in an AI project. There's a training part where you create a model. There's an inference part where you have the use of the model. And then there's the kind of embodied carbon around this. And this is one of the first projects we've seen that really makes the figures for the inference part quite visible and quite easy to work at, and one of the key differences between this and the Ecologits project that you just mentioned before, was that this is actually running on the software itself, so they have access to the hardware, they're running the hardware themselves, and they, actually document how they do this. The, when I spoke to Samuel Rince at GenAI, I asked him, "how does your thing work?" Because that's really cool, I really would love to see some figures for the inference prices. Well, what we do is we have to make some educated guesses and estimates based on how big a model might be, how much memory might be allocated for it, and how long it's run and how big the response is.

So they're essentially annotating responses that come back from Open AI or from Mistral or from Claude or anything like that to give you some numbers for this. And this kind of does beg the question, if we see green AI instrumenting their own physical hardware, and if we know that the best we can see elsewhere is us having to instrument things ourselves. Based on guesses, why is it such a challenge to find services that provide these numbers as part of how they work? This is still a challenge in 2024. And I think these projects here demonstrate that yes, there is demand and there's also ways to do it. So if these aren't being exposed, they really should, because it becomes much easier to be a responsible technologist if you have access to the figures about the environmental impact of what you're using AI, for example. So yeah, those are the things I'd share, and I'll add some links to that to follow on from this.

Gaël Duez: I wasn't aware that they were using their own materials, and that, that's a massive change indeed, because no more educated guess, as you said, and the ability to measure yourself. Of course, it means that they create their own assumption when it comes to the hardware setup, but Yeah, I really love the idea.

And I have a question for you because I wasn't able to unpack yet all the publications from Hot Carbon. So how was this article aligned or not aligned with the last one from Sasha Luchoni when she was actually testing? So once again, on the inference side, because we know that this is where most of the impact comes from, when she was categorizing the use of a different LLM

in front of different use case and, she was, for instance raising the alarm that for speech recognition text or other, I would say, basic AI solution, using large LLM was a complete waste. And that's something that really struck me that how important it is to pick the right model for the right task and not using LLM, especially GPT 3 or GPT 4 for everything.

So I was wondering, do you know how well that was aligned or not? Their own findings.

Chris Adams: Okay, so it's been a couple of months since I read the paper, or about one month, because the actual paper was released, I think, on the 11th of July or

something. The key thing was this paper from Verena and Didi, the people at the University HTW Berlin,

and, Green Coding Solutions. Their one, while they do talk a little bit about classification of tasks, they don't go into the same detail that the paper from Sacha Luchoni, which was, that was the one that we saw in MIT Technology Review, which very much said, generating an image has the same kind of energy demand as charging a phone, for example.

So they don't provide that same kind of breakdown because their primary focus was working with text. However, there is something we should share a link to, which is some recent work in April where the, where Sasha Luchoni and other people, other luminaries at Hugging Face spent some time working on what you might refer to as like Energy Star for AI.

This idea that for different tasks, you do have models and so you can start making some more informed choices about your choice of model when you're doing some of this stuff. So we should share links to some of these things because

there is quite a lot of work taking place that I think not everyone is aware of right now and it's a really useful kind of jump off point for this.

So yeah, useful questions Gaël, thank you.

Gaël Duez: It connects well with what you've mentioned, that there's a rating should be provided by the one making these models or operating these models. And it's great to see all those initiatives, but eventually, and I think this is a nice connection to the next stories, but when you operate something, you need to be transparent about the environmental footprint of what you do.

Chris Adams: So this is actually, you're right, that's a very good point, Gaël, and maybe just the final thing I'll share with this before we move on to the next story is that for training, we've seen pretty much the industry start to settle on the use of CodeCarbon, which is an open source Python project that you can use to essentially work out the energy use for any piece of Python code, but specifically it's used for quantifying the energy usage for training.

So, this is what's used for some of the papers by, from Hugging Face. I believe this was also the tool that was used for the most recent information from Meta when they shared the carbon footprint of Llama 3, their big model as well. So you do have some existing tools that are out there. One thing I've actually tried looking at recently was I realized that you can use these tools and there are tools like GitHub and GitHub Spaces which allow you to run a virtual machine, leave and run, like some inference locally, for example, to try and like test something out, for example. And, what I found was that I was preparing a workshop for, to deliver at DjangoCon in June earlier on this year to help people, like, figure out, okay, what's the environment impact of maybe using an AI service or figure out what some of the kind of service side environmental footprints might be. I found that, there's a competitor to GitHub spaces called Gitpod. They use a slightly more up-to-date version of Ubuntu, which basically means that if you're running a virtual machine inside this, you can actually use Code Carbon and get numbers back. But when I try to use this with GitHub spaces, because they're using a slightly older version of the underlying operating Linux that's used for this, you can't get the same numbers back. And I think this is important or worth being aware of because there's a recent release from GitHub, I think. I'm not sure if it's totally available for everyone yet, but there are now some tools specifically for using inference in GitHub spaces specifically. So it'll be really lovely, and I know I'm kind of nerd sniping the GitHub team here, if they could expose some of these numbers, because the tooling totally exists now, and the bar is so low that even just having something like CodeCarbon, which is useful, but has some, when you look into the details, has a few kind of compromises and few issues. That would still be massively more useful than what we have available to right now. So yeah, there's there's definitely worth, there's definitely tools out there that organizations can use to make it easier for consumers like yourself or me to use these in a more kind of responsible fashion. All right. Thanks, Gaël. Should we look at the next story now?

Gaël Duez: Let's do it.

Chris Adams: All right. The next one. This is a story from a former VP of Sustainability Architecture, I believe, at Amazon, Adrian Cockcroft. he's written a piece for The New Stack and the title is, How did Amazon, Azure and Google perform in 2023 Sustainability? So this is a piece by Adrian Cockcroft where he's basically read through the three sustainability reports. And as someone who actually does have a significant amount of context working on the platform side as well as, since leaving Amazon looking at the tools out there and trying to collate a kind of like useful data set with the Green Software Foundation Real Time Cloud framework, he's been able to say well these things which are easy to use this is where some of the data is helpful this is where there are real challenges and he's it's really useful to get to have someone who, in my view is very much seen as like a kind of real kind of trusted message of saying look,

these bits are okay, this is where the bar is really low and we probably should be expecting quite a bit more given the amount of resources available to people. And yeah, I wanted to just check, is there anything that caught your eye or that really leapt out at you when you were looking at this? I really like this piece and I'm really glad it's actually out in the public domain.

Gaël Duez: Yeah, I love Adrian's work. I love his optimism. I'm not, I would be a bit more cautious is when he, well, especially regarding Amazon, but I guess we're all biased at some point. And what caught my eyes was we discuss a lot numbers that are not that easily assessed and separated. The very big first issue that I had is when we talk about Amazon, it's not the main, the same thing that when we talk about Google or Meta, because, or Microsoft, because there is this big on premise brick and mortar, as we used to say, chunk of Amazon's carbon footprint.

And what is strictly related to AWS should be extracted. And that's not the case with all the numbers.

Chris Adams: You're referring to AWS and

Amazon the retailer, like there's

been separate business, that's what you're talking about here. fact they're not breaking down makes it harder to understand, right?

Gaël Duez: It's, very hard because it's a bit like if we were discussing the, Fusabi report of Google plus Walmart or Sainsbury's or whatever, or Carrefour, and, I'm always very concerned about how globalized the data are.

And I've, got some cave hats with what Adrian said. I won't challenge the numbers or his analysis because I think it was well done and the trend are there. Like AWS, Amazon is doing a bit better and Google and Microsoft are slipping up as the, as he mentioned, but, focusing a bit more on Amazon, for instance, there are a few things that I'm a bit concerned about.

So the first one is that they gather everything in this big Amazon and what actually as techies, we would like to understand better is AWS on its own. I think it's big enough to have its own sustainability report. The second is that they continuously provide numbers on the market-based approach, especially for energy. And I think that there are now countless examples where it's not really how Sustainably is done. Sustainably is as much a global matter than a local matter.

And I'd like just to take the example of Ireland. So if you run as many European techies, your instance on AWS, there are a great deal of chance that by default, you will be using the Ireland region. And when you log in the dashboard or your Sustainably dashboard, exactly as Adrian mentioned, you will see that everything is fine.

You're zero percent, you're carbon neutral, everything has been offsetted, and ciao, bye bye, well done, you can, do business as usual. Now the reality of the Ireland electricity grid is that one year ago, in 2023, the amount of electricity consumed by data center equals residential urban residentials.

It means that every houses, every buildings in Ireland consumes now less, a bit less electricity than data centers. So it has put a tremendous pressure on the electricity grid and the Irish electricity grid is not the cleanest or sorry, the lowest carbon on Earth at all. So, technically speaking, when we add resources, when we add instances on AWS Irish region, we are adding pressure and pushing the Ireland electricity providers to emit, to produce more energy, which is kind of high intensive energy.

And now you've got this market based approach, which has is it's prone. I'm not like, it's not black and white here, but saying, okay, but we invested energy elsewhere. And we show it either by a, power purchasing agreement or AAC. And so that's all good on the market because everything shall be offset.

But the local realities matters and that's even more true for water. But let's put that aside for the moment. So as long as they don't at least try to localize a bit more the carbon emission and the related energy carbon emission. I think it will be always very hard to say, okay, the trend is okay, the trend is not okay.

So that's my first issue. My second issue is that, and I think it was our dear friend from SDIA, Mike Schultz, who once said, one of the most precious resource on earth today is renewable energy. Because of course it's growing, but we don't have that much. And we should always question how much we allocate to which use.

And by having this 100 percent focused on offset or net zero approach, that is the one from Amazon, Google, etc. We cannot leave the elephant in the room, which is, but what are the absolute numbers? And when the absolute number are getting higher and higher, almost from a logarithmic perspective, it's almost exponential, not fully, but almost, we should question ourselves, but where is the limit?

Because we do know that in systemic and in environmental ecology, there are, there is always a limit to how much a system can grow. So, that's my two big issues. It's not localized enough. And it doesn't talk about absolute values. It only talks about the potential of things being offset or being carbon neutral.

And we need to think more about when we slow down or even we reduce our energy consumption. That's not on the table at all. So yes, of course, there are a lot of progress being made. They buy a lot of renewable energy, but is it the best use what we can do about renewable energy? And what are the trends? I know I could speak for ages about it, but sorry, Chris, and I didn't even mention water.

Chris Adams: So just, so let's just check if I understand the key things you're referring to there. So one of them is, just to be clear, we're talking about the Republic of Ireland, as in the island of Ireland here inside Western Europe.

That's we're talking about here. And if I understand what you're referring to here, there is one of the big things, big parts of this story this year is that Amazon has made a big song and dance about saying "yes, we are now 100 percent renewable powered for all of our infrastructure." And what you're, what it sounds like you're saying is that The physical reality in Ireland doesn't necessarily match this claim because it may be that the kind of the way people are substantiating this green claim is that they're basing this on credits like renewable energy credits and while these may be kind of considered kosher or like considered like legitimate in like maybe a trade electricity trading market kind of sense, the fact that we don't see the actual location based figures for these data centers brings up all kinds of questions. And also, the, there is also questions about, are renewable energy credits the correct way to actually basically back up any claims around the use of green energy, particularly when we know that the underlying grid, there may be more power being used than it actually, than renewable energy is actually generated in Ireland itself for this, right?

Gaël Duez: Absolutely. And then to, give them credits, they use less and less, renewable energy credits, which are highly questionable tools, and they use more and more PPA, which are Purchasing Power Agreement, where actually they commit to add new renewable energy via partnership, long term partnership with electricity producer.

So it actually increases the amount of renewable energy available for everyone on the grid. So I'm not saying that everything is bad or everything is great. My question is if you, for instance, just staying within Europe, invest in northern Germany in a wind farm to produce that amount of gigawatt of renewable energy, that's great.

That's necessarily, that's something that is very useful for the German market and for German users, but it will not offset the fact that there are still gas and even, correct me if I'm wrong, coal based port plant in Ireland, and that the use, the rise of energy use in this part of the world will emit more greenhouse gases.

So, once again, it's the incredible ability of humankind to tell itself stories, which has made us what we are today, has also a dark side, which is it's not because we decide that we create a fancy story called the market or the energy market, et cetera, that it is completely disconnected of the physical reality of thing, as you mentioned.

And the physical reality of thing is, it's great to add more renewable energy to the grid every day. Anywhere on earth, because anywhere on earth, we need more renewable energy, but it cannot really offset or compensate the fact that if we put some stress on electricity grid somewhere, it will add the emission of greenhouse gases and, eventually everywhere around the world, because I think it's any like carbon molecule that take 15 days to do a round trip.

So, it's a global challenge.

Chris Adams: If I understand what you're saying, basically, the instruments being used do not fully capture the physical realities of what's taking place. And while there may be progress, we probably need more progress in order to actually face the challenges that are being kind of set out by the actual, the real science that we're seeing. I'll share a couple of little points around Ireland specifically before we move on to this. So Ireland is actually one of the few countries where Green and IT claims around green energy have actually been challenged by the Advertising Standards Agency, specifically saying if you're a green energy firm and you're saying you're using green energy. We've, there have basically been cases where the Advertising Standards Agency in Ireland has said, you can't make these claims in Ireland if you're using just renewable energy credits as the basis for making this claim. So that's one thing we've seen. And that has interesting implications for technology firms that are using these green energies if they're substantiating their kind of claims around green energy by using these certificates.

If you've already had a ruling saying, "nah you're not allowed to do that." The other thing that surprised me, when I was looking into this, because the Renewable Energy 100 is a ranking of the top of a large number of firms who are significant investors in renewable energy. They actually don't accept the use of these kinds of renewable energy credits if they're not physically deliverable.

And one of the challenges you see in Ireland is that there's a limited amount of capacity to move the kind of like green energy that might be generated elsewhere in the world to there for this. So that's one of the challenges that you see. And we'll share links to both of those two things because for people who are kind of wonkish and want to get down to some of the bottom of this, they're really, I think they provide some interesting background to this.

We'll also share a link to the real time, to the Green Software Foundation Real Time Cloud dataset where there's been a bunch of work into trying to find some location based figures for this stuff so you can come up with some more accurate numbers than what we're seeing here. And I think, okay, I'll leave the last word with you, then we'll move on to the next story.

Go for it.

Gaël Duez: There are two things that I'd like to give credits to Adrian in his article. It's like stressing how much there are two sides of the story. And there's reports that focus a lot on sustainably of the cloud. And that's definitely what Amazon, Google, et cetera, are trying to do. But there is also this question of sustainably in the cloud, which is how as a user I can do or not a better job mitigating, reducing my carbon emissions, my water consumption, et cetera.

And he's right to say that not significant, no significant progress has been made on Amazon side and on AWS side story. And they are still infant phase at Google and even at Microsoft when it comes to transparency. And as a CTO, as an software engineer. And when you look at these dashboards and you see that everything is fine, everything is offsetted, you've reached carbon neutrality, it doesn't empower you to do the right things, which is optimizing, reducing your carbon emissions, your water consumption, etc. So that part, empowering consumers is still lagging of what we should expect from these tech behemoths. And my last comment is that I was very pleased that he mentioned and he reviewed, thoroughly the water consumption because for water and that my message about global versus local, it doesn't really matter.

It doesn't really make any sense to analyze the water consumption in terms of global consumption. It's water is a local matter. And it's really region per region, even data center per data centers. How much water comes in? How much water comes out? And in which state? Is it reusable, not reusable? Is it a closed loop or not?

In most of the data centers, including the one from the hyperscalers, are far from a closed loop. I know that Google has experienced once and they told quite a lot about it and it makes total sense. But we need more. precise and localized information on water. And that's a massive challenge as well. We focus a lot on carbon, but water is the next big issue that we need to pay attention to.

Chris Adams: Alright, water, that's the next horizon. I'm going to park that because we'll come back to it a little bit later. The next story is actually from the Financial Times. This is talking about Big Tech's bid to rewrite the rules on net zero. Now, at the time of this going out, it may be that the really nice looking piece may be hard for people to see, but no, the link does seem to work actually still, thankfully. The Financial Times has a really interesting piece, basically talking about the large technology firms that we often see coming up again and again. And this is a bit of a deep dive into some of the things you just referred to about like location based carbon footprints for electricity, because that's one of the key drivers of emissions for our use of digital services, and the market based approaches. And this pretty much dives deeply into something of a bun fight that's taking place where you have two kind of schools of thought where there's one set of companies like, to an extent, Microsoft and Google are pushing for this notion of 24/7 renewable energy and are having a quite kind of tight accounting process. And then you have another approach being largely put forward by Meta and Amazon talking about their kind of emissions first approach saying, no, what we should be looking at is decarbonizing the entire grid, not so much looking at our carbon footprint. And there's a couple of things that are really interesting inside this.

There's a few nice interactive graphics for you to see how people make green claims around energy usage. But one thing that I think is actually really stark is this set of charts showing the difference when you try looking at these figures. So, if you were to look at, say, the carbon footprints from, say, Microsoft, you can see, like, from 2018 to, like, now, you've got a figure of maybe, you see one chart showing the market based footprint, which is, pretty close to zero for Microsoft and close to zero for Meta and likewise for Apple. And then you see the location based figure for Microsoft. It's something in the region of like 8 million tons or zero tons, for example. And likewise with Meta, you're seeing 4 million tons versus zero tons. And Amazon's got the same issue where you're looking at like 15 million tons of location based carbon footprint from using electricity versus 3 million tons from using this.

So you, this really gives an idea of how these two different perspectives end up changing how you might report on this and how you might think about the environmental impact of using some of these tools. And like, to an extent, there is, there are reasons why you have a market based approach because, these come out of the fact that people who are inside large firms are looking for ways to be recognized for the investments they're making so they can justify this internally.

So there is a role that some of these play, but it often, it obviously gets quite a bit more complicated than that, especially because this is the year that the Greenhouse Gas Protocol, the kind of gold standard for reporting, is currently being overhauled to rethink how you should report this stuff and how you should be allowed to talk about energy being green or not green in this context. So Gaël, is there anything that kind of leapt out at you when you had looked through this? Because I would love more people to see this. I think it's a really fascinating story.

Gaël Duez: I think I've already commented it in advance when I was referring to the struggle between market based and local based approach. And once again, I think we should stress how important it is to understand that the way we build things in our mind and in our society as humans is one thing, and the physical reality of the world is another thing.

And when you add energy on a grid, wherever, et cetera, you have no clue on how it will be used, even if it will be used, because when you create PPA, it's potential energy to be used. You create new capacities, whether those capacities will be used or not remains a challenge. Obviously, they will be used, but not necessarily 100%, etc.

And I think the right approach is clean up your own mess. Everyone should start with this. So, I'm fine with having part of the sustainability report explaining what has been done and what could be the approach of market based, but the truth is local based approach. And when you see these figures, they're actually very consistent.

Yes, they're increasing massively their investments in data centers to fuel the AI boom. Their entire business model is based on infinite growth. The numbers go up, that's pretty, pretty logical. And what I've just kind of, when I read this piece of news, it also connected a lot with the crisis at the SBTI, the Science Based Target Initiative, that happened this year, when there was very strong push to allow more offset techniques to be recognized as science based,

Chris Adams: Ah, you're referring to the Scope 3 thing. The push people being able to use offsets in their supply not just electricity, as a way to kind of decarbonize that without having to necessarily make some of the changes to like reform the supply chain. Is that what you're referring to here?

Gaël Duez: Absolutely. Thanks for making it much clearer than I was about to say. So, I think the struggle is everywhere because we see that the low hanging fruits, most of them has been already taken care of in this big corporation and they're entering the bumpy road where you've got harder choice to do. And when you face this kind of choices, well, either you do the right things and you go back to the physical reality of our world, or you try to change a bit the narrative or change a bit the rules, and I think this is exactly what we've been seeing at the science based target initiative where, some companies were obviously not able at all to meet the decarbonizing plan that they proposed just a few years ago, and they were trying to change a bit the rules.

And that should really question ourselves when it comes to transparency and acknowledge that even the most well intentioned CEO, the most well intentioned C suite, they cannot really do the right things without a bit of external help, whether it comes from pressure from activists or governments or UN, you name it, but we cannot fully rely on companies agreeing on how they should measure their own environmental impact.

Even if they are well meaning with tons of great people trying to do the right things, et cetera. It's not a black and white world out there. But there is a question at some point of financial pressure, shareholder pressures in many of these companies. They're just stronger than the entire stakeholders pressure.

Chris Adams: I think I know what you're referring to here, and what I'll do is we'll share a link to some of the stories about the SBTI, the Science Based Targets Initiative, the whole kind of bun fight that took place there, that ended up resulting in the then CEO stepping down from the organization, partly because there was so much pushback against this idea that you might be able to use offsets for looking at your supply chain emissions is in this same fashion. So we'll definitely add a link to that, thanks for that Gaël. The other thing that we maybe might maybe you must referring to inside this is there are some really nice quotes. Is that what you're talking about here does actually there's some relevance back to the Financial Times piece here, about when you look at the decarbonizing energy in this particular space. One of the approaches being used, which is described as Emissions First, for example, this is the one that's being largely put forward by Meta and Amazon. And one of the arguments for this is that we should be able to be optimized for absolute impact, not necessarily our own carbon footprint.

So given a hundred euros or a hundred dollars, we should be able to deploy that in the most effective place globally, wherever it might be. So one of the arguments being made is that we, if we want a data center in say, North Virginia, we should be allowed to basically purchase the right to claim the emission reductions in somewhere like India, which has a very coal heavy grid, and then kind of count that against our own emissions. And on one level, yes, you are reducing the environmental impact, you can make the argument, but it also means that some of the cheapest possible emissions in India are now being bought by one of the richest, some of the richest companies in the world. And this is very similar to the dynamic you were referring to with offsets, where, essentially, if you have a kind of, climbing scale in terms of how difficult it will be to reduce emissions over time. If you grab all the low hanging fruit, that raises all kinds of equity issues about what's left over for people who don't necessarily have the same resources available to them as Facebook or Meta or Amazon, for example, when looking at this. So, this is one of the challenges you do, find. But I'd really urge people to look over the FT piece and what we can do is we'll share a link to an archive link for this if the one, if it's behind a payroll, because it's a really fascinating piece and it's really worth looking into. Okay, Asim, sorry, Gaël, should we move on to the next story here?

Gaël Duez: Yes. I'm honored that you thought was... I

Chris Adams: Bit of a Monday morning moment here. Okay, so this is actually a story speaking about AWS again, by moving an AI workload to AWS, you can reduce the carbon footprint by up to 99%. That's the argument being laid out inside this. And this is a piece from The Stack, which is not the same as The New Stack, who covered our previous story.

It's another organization. This one basically takes apart some of these questions, or at least dissects some of these claims and say, well, what's the basis for this? Gaël, I wanted to kind of give you a bit of space to talk about this because I know that you've read this and I know that this is something that is... and you often advise firms who are actually trying to figure out how do I reduce the environmental impact of the services I'm using. So when you read this, what leaps out at you and what kind of things are the kind of most salient points would you say?

Gaël Duez: Well, I think my main reaction was, "oh no, yet another one."

Okay. So there is the SCI piece, which is interesting, but let's go back to basics about it. And I encourage listeners to have a look at two great resources. The first one is an article from the Boavizta Association investigating the claims made by several hyperscalers that when you migrate from your services, from a traditionally hosted perspective to a hyperscaler perspective, you save 60, 70, 80, 90 percent of carbon emissions.

And the second source is actually a man, and I was very pleased to see him being quoted and interviewed in the article, which is, he's Mark Butcher. He has been very vocal about hyperscaler claims, how they measure things, the scope three not being that well taken into consideration. Mark works at Positive Cloud and he works with a lot of clients across the UK on these topics.

And why I'm mentioning this too is that hyperscalers, when they say, basically "move your instances more, move your computing power to our facilities, because we are so much more efficient than the other data centers or the other hosting solutions," they might be right, but the others are a role, a world on their own.

And this is really the question of the baseline. Yes. If I run two or three servers in my office building, in a small room with a very old air conditioning, yes, I might reach a PUE of 2, 2.2, maybe 3, whatever, et cetera. But most of the clients, they don't start with these baselines. They start with servers and instances being managed in already quite professional and by seasoned providers, okay, and I won't provide any name here, who have already reached a decent PUE and the gain is much smaller.

So that's. On, from which baseline do you start?

Chris Adams: I see, like the example given here is like a really inefficient thing. If you compare really an inefficient setup compared

to this idealized, going to give you a disproportionately large saving. That's

Gaël Duez: And this is when you study the case studies, which have been provided by hyperscalers. it's literally my grandma managing a data center. Worst practices possible that are accounted as a baseline. And this is not the truth. Many data centers already reach pretty decent or, pretty good actually,

power efficiency. So where you start from matters. And that's my, point number one, my point number two, and we go all the way back to this local versus market based approach. But I'm sorry to say I'm, I, feel a bit like I'm, rambling here. But once again, if, even if, okay, I run the worst possible data center on Earth, I've got

maybe a PUE of two, maybe three, et cetera, but I run it in a very low carbon place, say France, if you account, for, the nuclear, a share of energy, say Scotland, for instance, and I recall Mark wrote something about it, Mark Butcher wrote something about comparing the energy intensity of North Scotland and Ireland.

And once again, just by migrating your instances there. You might, let's say, divide by two, your energy consumption, thanks to better energy efficiency by AWS, because they're very active in Ireland, but you can do the same math with Google or Azure, but then you start operating in a country which is, and that's the case between, for instance, Northern Scotland and Ireland, six times more energy carbon intensive when it comes to electricity production.

Chris Adams: So let me check if I understand, well, I think with the point you're getting at, you're basically saying, yes, you may, the infrastructure may be more efficient, but if the local energy is dirtier, it doesn't necessarily matter that it's six times more efficient. If, say, the infrastructure is twice as efficient, but the energy is six times worse, then it's still, you're not coming out ahead. That's what I think you seem to be making the argument there

Gaël Duez: I actually, I was actually, I was not the one making the argument. Mark did it and

Chris Adams: but that's, that's you're saying. Okay.

Gaël Duez: but that's exactly what I'm saying. And so this question of where do we start from the baseline is super important. Then there is a specificity of the AI itself. And we should always remember that most of the time by AI people, and I think this article is a bit misleading here as well, they think generative AI, which is part of AI on its own.

We start from so high. It's still very infant. The LLM are not that old. And of course you can decrease very significantly the energy consumption and the emissions of your AI model, because we are, we've just started to do so, but what will be the trend for, I would say, everyone rather than AWS is an open question.

Obviously, they're doing a better job reducing and optimizing everything, but it's fair to assume that other actors as well are doing the same. So I'm always very concerned when we take a very new algorithm, I would say, or a new part of the AI industry and say, "Oh, look, we're going to reduce by that, that much."

But of course, it's like with cryptocurrency. They've started at such an inefficient way that they made a great progress. Still, they consume a lot of energy. So you see that's my point. So I will be always super cautious with this kind of stuff. And then comes the good part of it, which is using the, as the software carbon intensity, but maybe Chris, you want to elaborate a bit more on

Chris Adams: So, it's nice to see an international standard being used in reports like this, but in order for a standard to be used, you need to follow the standard. And one of the key things that the standard actually does is it, basically, when I've looked through this, I look through the report, I can't see any numbers for any of this.

So, it's like you have a car saying, well, this car is twice as efficient as this other car. If you don't have any numbers about, like, the miles per gallon or the equivalent like that, it's very hard to be able to trust that number, for example, or trust any of these claims here. So you have an issue about, well, there's a lack of underlying numbers. Also, the thing we see is that a significant part of this is based around the environmental impact of the energy itself. Again, we don't have the numbers for this, but in particular, one of the key things, one of the key claims being used in the report was we're going to take into account these market based figures here.

Now, the Software Carbon Intensity specs explicitly says we don't use these inside this. So, you've essentially got people using this term, Software Carbon Intensity, without actually following any particular nuances of this. And this, It makes it very difficult for me to recommend this report for anyone else because it essentially is going against how this is intended to be used. And the firm that was working with Amazon, they are very involved inside the Green Software Foundation. This really needs to be a thing that we can't do if we want to see this to be adopted and respected because this essentially, in my view, undermines a huge amount of work that's gone into developing a standard here because this makes me trust the Software Carbon Intensity less after reading this report and seeing people cite it, because it's being used incorrectly. So that's one of the things I would actually raise and something that does need to be addressed. Like, there are mechanisms that the GSF has to say, please do not use it in this way. It's misleading and it undermines some of the work we have. And I think that's something that will need to happen because, yeah, I cannot recommend anyone looking at this report or even recommend using or referring to this standard like this because it's an incorrect use of the standard. So yeah, that's my take on it.

I'll move on from this because that was a bit of a downer, but it's really important if you want people to trust this in my view.

Gaël Duez: And I think also that there is a way to protect the SCI and the Green Software Foundation tools, which is using the Impact Framework manifest,

Chris Adams: Yeah, I'm glad you mentioned this, Yeah.

So there is a mechanism. The whole thing around the Impact Framework was specifically set up to say, "hi, you're going to make a claim? Make this transparent. Show you're working inside this." And that's like, there's a huge amount of work that's gone into providing this, and if you're not going to share any of the numbers or share the basis, and there are now lots and lots of really helpful case studies demonstrating how to do this, like we'll share links to this to show this is, these are the correct ways to use this. When you have it being used in a way which is so unhelpful, it's, really problematic, and you can see why people are going to struggle, and why, you can see why people end up essentially dismissing so much of these, efforts as greenwash, when people aren't sharing the underlying numbers for this stuff.

So yeah, that's like the framing I would take, and I would really like to see this addressed, because it's going to be, it's going to be a real challenge going forward, in my view.

Gaël Duez: Transparency, transparency, that's all that matters with this kind of claims.

Chris Adams: So, this probably takes us to the last story I think we have time for. This is one actually, this isn't so much a story, but more of a kind of discussion about some of this. So we've been talking about how it's real, really difficult to actually get some numbers from this, and how the way people report this is also a real challenge.

The thing I kind of want to share with you, and I realize I won't have time to talk about this while I, this is partly what I'll be talking about at some events in September, is the fact that we have, we Some regulation, which is forcing some of this. So in Europe, all across Europe, there is a law called the energy efficiency directive, and basically any data center that uses more than 500 kilowatts of power, which is, that's not a small data.

It's not a tiny data center, but pretty much every single hyperscale you imagine would have to do this. There is now a law, which basically says, every data center and any organization operating a data center has to make publicly available, Information like the name of the data center, who runs it, how large it is, how much power is used. It talks about the amount of energy used, the water used, all this stuff. So we do actually have laws which are kind of forcing some of this now. The, there is one caveat in that where companies consider this information to be a trade secret, they don't necessarily need to publish this information into the public domain, but where companies are not saying this is a trade secret, we now, as technology professionals, can ask and say, this information should be in the public domain if you're in, if you're in Europe. And the thing that I might share as a follow on from this is that for companies that are not sharing this information, they are now mandated to report to a centralized database with the idea that some of this information will be shared in an aggregated format.

So for the first time, we can actually get some meaningful numbers that come out of this. So, companies that are prepared to be transparent, you can ask for this stuff. Companies that are then saying, "we're not going to make this transparent because it's a trade secret." There is still a mechanism by which they will need to report so that we can finally have some data informed policy around this. Because one thing that's come up again and again in this discussion has been that we don't have access to this information. And there is so much pressure or there's so much, there's so many incentives to construct a message which makes you look good that it becomes very difficult to trust a lot of the statements around green software that come from lots and lots of large firms right now.

So yeah, this is, I'll share a link to the issue where this has been discussed inside the real time cloud working group inside the Green Software Foundation. But Gaël, I wanted to just check, as someone who's not in Europe, what's your take on this? Is there anything that kind of caught your eye when you were looking at this?

Gaël Duez: Well, the first thing is that it is required to disclose numbers in both relative, but also absolute numbers. And that's very important. It's not only PUE. It's also how much energy did you consume overall? And that really connects well with what we've discussed before. I also believe that this is something that is

pivotal for country with weakest electricity grid to consider. It's always claimed that for instance, Kenya, my neighboring country of La Reunion island, has a very strong policy of attracting data centers. They want to become a computing power.

Chris Adams: Iceland of Africa, because have more geothermal than

Gaël Duez: Absolutely. And I reckon that this kind of disclosure will also have them a lot anticipate what is needed for them to prepare the electricity grid to this kind of increase in electricity consumption caused by data centers.

And also making sure that what has been dealt and agreed when they do this big hyperscale deal are actually what is provided, that the energy is there, that the water is there, and I believe that local populations, which are often caught in between, like, "oh, it will create a lot of jobs, but when you do the mass, not that much," so it's not that an obvious investment to say, okay, we will welcome a lot of data centers in our country.

It might be, but it's not like a big investment. A clear win or the case, they will have the ability to scrutinize, how, what are the impacts and environmental impacts. And I must admit that, if you look a bit at the history, in 1982 in Europe, a European directive created the Seveso listing, and the Seveso made it compulsory for every state in Europe to list what are the facilities, industrial, agricultural, mostly industrial, which can create significant environmental risk.

And we were talking about chemical industry, et cetera, et cetera. And to some extent, data centers, they impact a lot of the environment. It's just that they will not blow away like a chemical industry, but on the long run, they've got a lot of impact on their environment and it makes a lot of sense to, at least for the bigger now, the biggest data centers, to be able to provide

environmental information, in a comprehensive way, a comparable way, and to make sure that we monitor the environmental impacts of these big facilities. we're talking about facilities that are built on hectares of land. There's not like the small, tiny warehouse that we might still think of.

They're like massive industrial facilities. So having open and transparent reporting seems to be quite straightforward.

Chris Adams: So maybe we might see some of these ideas adopted in other parts of the world, especially because on the underlying data for this. We'll share a link to this. We've been doing some research ourselves in the Green Web Foundation. A lot of these data points are based on the EU code of conduct, which is a public document for people. So it may be the case that you might see some of these data points being reported in other parts of the world as well to set a precedent. So they actually have the data to make data informed decisions about how, about the role digitalization plays in society and

how the impacts are actually shared around this.

Thank you for the link about Seveso as well. I didn't know about the Seveso directive. That's totally new to me. What I might share is a link to some of the work that the Green Web Foundation has been doing. We have a fellowship and one of our fellows, Samantha Nidwalana, she's based in South Africa and the Netherlands, and she spent a bunch of time looking through, trying to get some numbers in South Africa for, to basically explore okay, what's the environmental impact of data centers inside this?

And we'll share some links to her challenges in this because she's been trying to find these numbers and it's been a real, it's been a real challenge in many cases actually. And it does give you some idea about like where some of this might go, but also hopefully stories like this and seeing some of these laws being passed might help set a precedent so that we can have more transparency in other parts of the world as well. Okay, I realize we're coming up to time. Let's do a quick just run through. We've got some events coming up. I know that I'll be catching a train in a few weeks time to go to London, and I think I'll see you in person for the first time for quite some time actually. This is an event called Green IO Conference. Maybe you could just briefly touch on that before we move on to the next set of events and then close out for the day.

Gaël Duez: Yeah. Well, absolutely. I will be pleased to see you again for the second time. The first time was in Berlin, if I recall, and I think it was for being interviewed on the GreenEye And what. I launched with my partners RPI Days last year, was a series of global conferences called Green IO, not very original, sorry about this.

And the idea was to have also on site events. We can see a lot of hybrid and a lot of online events when it comes to digital sustainability and they're great. We can give kudos to the Green Web Foundation, the Green Software Foundation, CNCF as well. They're doing a lot of these events. Now, what I also realized is that if you look at other specialties in our IT industry, let's take cybersecurity, for instance, accessibility, design, or you name it.

When you work in a city with a significant enough workforce in cybersecurity, for instance, let's say Barcelona, Berlin, Paris, New York, Singapore, Beijing, you have at least 2, 3, 4, sometimes 5 different on site conferences when you know that you will meet your peers. Today, if you are an IT sustainability specialist or green IT folks or whatever, like the dude who anyone reached out to because, "oh, it's about green, et cetera.

He's a person, she's a person we'd like to talk to." You've got basically nowhere to go except for one conference in Paris and one in Belgium now in Brussels this year, where you know that the topic will be a hundred percent your specialty. So don't get me wrong. We can give kudos to a lot of tech conferences like QCon, like even Reinvent AWS, you've got to sustainably track, that's fine, but having a 100 percent green IT focus or IT sustainably focus conference, where you know that basically this is the place to be to meet all your peers, most of the cities around, they don't have it. So that was really the idea of creating this Green IO.

Even since Singapore, London, and Paris this year, we are like 90, 90 percent sure that we will add New York and Munich next year also. And the idea is really, it's just It's a place that has been created for the local communities to do what they want with it. And so you, this year in London, it's a bit like go back to the basics and let's talk step by step.

What about low carbon infrastructure? What about design and eco design? What about beyond, understanding the organizational challenges and HR challenges that when you want to rule out more sustainable approach, but that's a one day conference. It's two days in Paris this year, but in London, it will be one day.

And we expect to have like several hundreds of people joining. And I know also that we will have a great keynote speaker that some of the listeners might known named Chris Adams. So I'm really delighted that you agreed to join Chris. Thanks a lot for this.

Chris Adams: Cool, thanks, so that's the event. It's the 19th of September, taking

place in Bishopsgate in London. And thank you, I am indeed keynoting in the morning, so I hope my trains are on time. But there's a number of people from the Green Software Foundation, for example. I can see Sara Hsu, who is one of the people leading the Green Software patterns project in the Green Software Foundation. There's some people from the W3C on working on web sustainability guidelines. There's also, I'll, share a link to Therese Gale who is working at Salesforce. She'll be talking a little bit about some of the experience, some of her experiences as well. So there's a number of people who

Gaël Duez: Mark Butcher will

Chris Adams: and Mark, yes, the, yes, Mark Butcher of Positive Cloud.

He's been one of the people who's been really instrumental in some of the most recent work inside the UK government, put together a kind of Digital Sustainability Alliance. There's a bunch of things there. So I'm actually looking forward to this Gaël, and I want to just give people a heads up that it's taking place. Gaël, thanks so much for coming in for this and telling us the stories about Wales, And we're watching and all that sharing all your insights elsewhere. Gaël, if people do want to follow up and see what you're up to, what's the best way to find you for future work?

Gaël Duez: Well I would say on LinkedIn and I'm pretty easy to find Gaël Duez. There is not that many. And more generally, if you are interested in what we do in Green IO, it's greenio.tech. That's the website. You've got access to the podcast, the conferences you've got link to my own websites. But I think greenio.tech is the best place to start.

Chris Adams: Brilliant. Well, thank you for that. We'll share some links to all of those websites and to this event coming up. And, for people who aren't able to go to Green IO, the Cloud Native Computing Foundation, the TAG ENV essentially the green part of the Cloud Native Computing Foundation.

They have a series of remote events taking place in October. We'll show a link to that so that if you still want some, to get an events fixed, that's where to look. Alright, Gaël, thank you once again for making the time and I hope you have a lovely week. Okay. Take care of yourself, mate.

Gaël Duez: Thank you, that was great being there. Bye, have a nice week as well.

Chris Adams: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundationon. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode!

View Details

Host Chris Adams and guest Romain Jacob delve into the often-overlooked energy demands of networking infrastructure to discover A Greener Internet that Sleeps More. While AI and data centers usually dominate the conversation, networking still consumes significant power, comparable to the energy usage of entire countries. They discuss innovative practices to make the internet greener, such as putting networks to sleep during low usage periods and extending the life of hardware. Romain talks about his recent Hypnos paper, which won Best Paper at HotCarbon 2024. He shares his team’s award-winning research on how energy demand for networking kit powering the internet can be reduced by simply by powering down links when not in use.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Romain Jacob: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

Resources:* SCION Architecture [11:30] * Environmental Impacts of Internet Technology (eimpact) [17:15] * Why we should be intentional about the mental models we use for thinking when we think about digital sustainability | Chris Adams [18:30] * A Sleep Study for ISP Networks: Evaluating Link Sleeping on Real World Data | Romain Jacob, Lukas Röllin and Laurent Vanbever [18:59] * Network energy use not directly proportional to data volume: The power model approach for more reliable network energy consumption calculations | David Mytton [38:55] * Co2.js - The Issue | The Green Web Foundation [42:57] * Rethinking Allocation in High-Baseload Systems: A Demand-Proportional Network Electricity Intensity Metric — University of Bristol | Daniel Schien [43:53] * Introducing Web Sustainability Guidelines | 2023 | Blog | W3C [49:31] * Greening of Streaming [52:16] * Network Power Zoo | ETH Zurich [54:46]

Other source material: * A Primer on Optimistic UI | Imhoff * Response Time Limits: Article by Jakob Nielsen | NN Group * Optimistic UI Patterns for Improved Perceived Performance | Simon Hearne * Reducing the Energy Footprint of Cellular Networks with Delay-Tolerant Users | IEEE Journals & Magazine

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
Romain Jacob: We used to consider that energy is cheap. Energy is there. We don't need to worry too much about it. So it's just simpler to plug the thing in, assume energy is there. You can draw power as much as you want, whenever you want, for as much as you want. And it's time to get away from that.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello, and welcome to another edition of Environment Variables, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. Back in episode 10 of this podcast in September 2022, we did a deep dive into the subject of green networking, because while a lot of the time people talk about the energy demands of AI and data centers, in 2024, in absolute terms, the amount of power consumed by networking was still larger.

Back then in 2022, the best figures, when we looked at this, came from the AI, which put the energy usage of data networks at around 250 terawatt hours per year. So that's about the same as all of Spain's energy usage in 2023, so that's not nothing. Now, it's a few years later, 2024, and the best figures from the same agency, the IEA, now give us a range of between 260 and 360 terawatt hours, which could be anything up to a jump of 50 percent in three years now.

Now because of much of this power is coming from fossil fuels, this is a real problem, climate wise. So what can we do about this? With me to explore this once again, is my friend Romain Jacob, who helped guide us through the subject in 2022, along with Dr. Yves Schouler at Intel at the time.

His team's recent research won the Best Paper Award at HotCarbon, the conference that has fast become a fixture on the green IT and digital sustainability circuit. So he seemed a good person to ask about this. Romain, thank you so much for joining me for this podcast. Can I give you the floor to introduce yourself before we revisit the world of green networks?

Romain Jacob: Chris, welcome. I'm very happy to be back on the podcast to talk a little bit more about this. Hello, I'm Romain, I'm a postdoctoral researcher at ETH Zurich in Switzerland. I've been working in sustainability for two to three years now, more or less full time, as much as full time research happens in academia. And yeah, I was, I had the pleasure to present some of our technical work at HotCarbon and I'm sure we're going to deep dive into a bit more in the podcast.

Chris Adams: Okay. Thank you, Romain. And for people who are new to this podcast, my name is Chris Adams. I am the executive director of the Green Web Foundation. We're a Dutch nonprofit focused on reaching a fossil free internet by 2030. I also work as one of the policy chairs inside the larger Green Software Foundation, which is why I'm on this podcast.

Alright, if you're also new to this podcast, every single project and paper that we mention today we'll be posting a link to in the show notes. So for people who are on a quest to learn more about reducing the environmental impact of software engineering, you can use these for your own practices and your own research.

Okay, Romain, are you sitting comfortably?

Romain Jacob: I am.

Chris Adams: Okay, great. Then I'll begin. Okay, Romain, when we last spoke, we covered a range of approaches that people are using right now to rein in the environmental impact of networking. And but before we spend too much time, I wanted to kind of see if you could help set the scene to help folks develop a mental model for thinking about, say, networking versus data centers, because I touched on this a little bit, but it might not be obvious to most people.

So maybe if you could just provide the high level, then we can touch on some of these Differences between the two and why you might care, or how you might think about these differently. So yeah, let's go from there.

Romain Jacob: Yes. Sounds good. It's true, you mentioned in your introduction that we sometimes get numbers that oppose or compare data center corporate footprint or usage and the ones from networks. But now, what does network really mean? It's not really clear what we mean by that. Because there is networking in data centers and, you know, the rest of networks are not completely detached from it.

But at a high level, you have a set of networks that are meant to provide internet access to individuals and to other networks. What this means is that you have companies that are specialized to just make your laptop, your phone, or other appliances you have, being able to talk through the internet. And typically when we refer to networks, without further details, this is the type of network you're talking about.

And data centers, on the other hand, are something that is in the scale of IT fairly recent, where we have this idea of if we centralize in, in one physical location, a lot of powerful resource machines that have a lot of compute, that have a lot of storage available, then we can use that as a remote computer.

And just offload tasks to those data centers and just only get the results back. In today's ecosystem, data centers are a very core element of the internet. The internet today would not really work without data centers. Or at least a lot of the applications we use over the internet only work thanks to data centers.

So from a networking perspective, in a data center, you also have, you need to exchange information and bits and packets between those different machines that live inside the data center, but the way the network looks like is very different from the cellular network that is providing mobile connectivity to your smartphone.

Chris Adams: Ah, I see.

Romain Jacob: So those are very different type of networks, and they have different, very different type of way they are designed, way they are operated, and how they are used. Typically, in a data center, you tend to have a quite high usage of the data center network because you have a lot of exchange and interaction between the different machines that live inside the data center, whereas in the networks that provide internet access, so the networks that are managed by entities we call ISP, for Internet Service Providers.

Chris Adams: Mm hmm.

Romain Jacob: Tends to be much less utilized. There is a lot more capacity. in those network that what is really demanded by the end user.

Chris Adams: Okay.

Romain Jacob: That's a fundamental difference between, between the two networks and something that we try to leverage in our research.

Chris Adams: Okay, so if I just check if I understand this, so you said that you might have networks which might be like, say the ISPs and things, they are individually not that high themselves, but because there's so many of them and because they're so diffuse, in aggregate, this can work out to be a very large figure, for example, and, and, that also speaks a little bit about, I guess, how you might power some of these.

So, like, when we think about a large hyperscale data center, that's something in the region of maybe, if you're looking at a large one, which is maybe the high tens to maybe low hundreds of megawatts, that's maybe thousands of homes. That's a lot of power in one place, whereas with a network, you don't have quite so much, but it's because it's distributed, you might have to have different approaches to managing that.

So, for example, you might and, you might have to take different strategies to either decarbonize that or deal with some of that, some of that load that you actually have. Okay, and I guess one of the questions I might have to ask you about this is then, when you have this, split between the maybe it's just worth talking a little bit about the different kinds of networks that you have here.

So for example, as I understand it, there's maybe an ISP I connect to, maybe my ISP, but then they need to connect to some other cable. And if I'm going across, maybe if I'm connecting to a server across in the Atlantic, then I'm going through some like backbone or something like that, maybe you could talk a little bit about the different layers there, and what some of the, and what the kind of, how much they might make, or if there's any differences in how those ones need to be powered, for example, how they're used?

Romain Jacob: Yeah, totally. So the, the name internet stands for an interconnection of networks. So the internet by name and in private space is a network of networks. Right? So when you connect to the internet. What it means is that you connect to another machine somewhere on the planet that has also access to the same global network.

But these global networks, the connection between those two endpoints has to go through, most of the time, several different networks. And so, typically, if we look at the internet infrastructure, there are several ways of representing this, but one division that we usually use is You have Core, IAP, so the one that kind of sit more in the middle and they provide transit for many, many different interconnections.

Then you have networks that are qualified to be more belonging to the metro area. So this is where it's getting closer to the user, but it's not yet the network that provides direct connectivity to, let's say, your phone or your laptop. And then you have the edge network. And the edge network is really there to provide what is called the last mile connectivity key to the end user.

And those categories exist and were proposed to Helsinki because this share of the network has different characteristics. The core tends to look a bit more like the data center. Like, it's more dense mesh, so there are more interconnections between the different points in that network. And the utilization tends to be higher and kind of constant because it's a global network.

Whereas, the closer you go to the end user, the more you're going to see filtration, because, for example, while users are awake during certain hours during the day, and this is where they tend to use their machine. You will see peak of usage during, you know, TV show primetimes in the evening, but much less at 5 a.m., where most people are deep and not using their phone or their laptops. And so, those networks look differently in terms of What they are used for and how they are built and designed, because we try to adapt the design for the particular use case.

Chris Adams: Okay, thank you for that. So it's a little bit, if you squint, it's a little bit like how you might have motorways and then A roads and B roads and maybe smaller roads, for example.

Romain Jacob: Very like that. It's very much like that.

Chris Adams: All right. Okay. So that's actually quite helpful. And when I think about other kind of systems, I think a little bit about say, like electricity networks, which have, you know, big fat transmission ones which send lots of things, but then you have like the smaller distribution networks which are, so it's somewhat comparable. Okay.

Romain Jacob: It very similar in principle.

Chris Adams: Okay, so this is helpful for developing a mental model about some of this. Alright, okay, so last episode when we spoke about the different techniques people spoke about, you, we spoke about things like carbon away networking, different protocol designs like I think SCION, which was one of the, projects proposed.

And you kind of coined this phrase that an internet of the future needs to grow old and sleep more. And I really, I found this kind of quite entertaining and it stuck with me. But for people who are new to this, maybe you could just unpack what you meant by that because not everyone has read the paper or seen the talk. And I think it's quite helpful for thinking about this subject in general, actually.

Romain Jacob: Yeah, sure. So, so two years ago in the first edition of the HotCarbon Workshop, we, we outlined this vision of what could be relevant to work on in sustainable networking area. And the two ideas that emerged were essentially captured by this growing old and fleeting more aspect. So what do we mean by that?

Growing old is essentially the idea that we tend to be using the hardware we buy not long enough. So if we take an end user perspective, we tend to change phones every couple years. Numbers are changing about this, but we can debate whether this is a good thing or a bad thing. In the networking area, so for the hardware that operators buy to make up the network, so devices that we call routers and switches, it tends to be a bit of the same thing.

Devices were changed, the standard used to be every three years. So in three years, the entire infrastructure would be renewed. So you would buy new hardware to get higher speed or better energy and so on. And there are various reasons for doing that. We can detail it if you're interested afterwards. But it has a very significant cost, financial cost, but also in terms of carbon cost.

Because one people need to understand is that every time you manufacture a product. Not just for networking, but for any product, there is a carbon footprint associated to it. This is where we typically refer to the embodied carbon footprint. And so this embodied carbon is a one time pay, but if you buy more often, well, you pay this price more often.

Now, there's a bit of a tricky thing, which is that you, you can argue that If I buy a new device, a new phone or a new router that is 10 times more energy efficient, then over time, I will then do more saving that would compensate for the embodied cost. The problem is that you, it's very hard to estimate how much you would save and how much is the embodied footprint.

It's a very firmware, a break even point where you're doing this upgrade, buying this new hardware, start paying off from a carbon perspective, but it's not necessarily clear ahead of time when that happened. Generally speaking though, what was pretty clear to us is that we could and we probably should be using the hardware longer.

And this is what we meant by the grow old idea.

Chris Adams: Ah, okay. Thanks for that.

Romain Jacob: Now, to describe more, this is kind of simpler. This is the idea that is very common in other fields like what we know as embedded systems or the Internet of Things. Think about devices that run on battery, to make things simple, that are more or less small but run on battery. And because they need to run on battery, for decades, engineers have been trying to optimize the energy efficiency of those devices.

And the most efficient way of doing this is essentially turning off everything you don't need when you don't need it. So if you think about your phone, your, the screen of your phone is off, I don't know, maybe 90 percent of the time. And this is to save the power drawn by your screen, which is by far the most expensive or power hungry element in a smartphone.

And we do this in order to save on power, on the average power and so on energy at the end of the day. And we are arguing that in the networking world, this is not done too much. And it should probably be done more. So now I need to be quite precise here when I talk about the networking world, I'm talking about the wired networking domain.

In the mobile domain, so in cellular communication that connect to your phone, or also in Wi Fi and so on, the idea of sleeping is already used quite a lot. But in the wired domain, it did not transfer too much. And so the reason why it did not transfer is because we used to come to the idea that energy is cheap. Energy is there. We don't need to worry too much about it. So, it's just simpler to plug the thing in, assume energy is there. You can draw power as much as you want, whenever you want, for as much as you want. And it's time to get away from that.

Chris Adams: Okay, alright, so if I just play that back to you to make sure I understand it correctly. So, the growing old part is essentially a reference to the embodied energy that goes into making various kinds of hardware. So, like, when we're looking at a laptop, around 80 percent of the carbon footprint, it comes from the manufacturing, compared to the running of this.

And, if I keep that laptop for a short period of time, It's a great proportion of the life cycle, lifetime emissions, for example. And we see the same thing in data centers as well. So, for example, Facebook and company, you know, some companies and hyperscalers, they might have had this three year period that you spoke about before, but in the 2010s, we saw figures anecdotally, but not published ever.

It was like 20 years ago. But sometimes these would go down to as much as as little as 18 months for some service because they wanted to get the maximum usage of kind of compute for the power they're using for example. So they had incentives to change like that. So that's what that part is a reference to.

And I think on the eImpact mailing list, where I've seen a lot of the discussion. I will share a link to this in the show notes of this really cool 3D chart showing how, where the break even points are that you mentioned about that. And the sleeping part seems to be this reference that, in many ways, networks are often designed for kind of maximum amount of usage, not necessarily what the average usage might be, similar to how, say, the electricity grid in America, for example, is designed currently designed for everyone to be using aircon at the same time, when normally it's maybe 40 percent utilization.

So there's all this kind of headroom, which doesn't need to be accounted for. And we, and it's a bit like service, you know, we have, as software engineers, we're taught generally to size for the maximum output because the loss of business is supposed to be worse than the cost of having that extra capacity.

But in 2024, there are new approaches that could be taken. And we do things like serverless and scaling things down. And these ideas are - they've been slower to be adopted in the networking field essentially, right?

Romain Jacob: Yeah, that's kind of the, that's kind of the idea.

Chris Adams: Brilliant! Okay, that is good. We'll share a link to the paper because it's quite a fun read and I really helped, it stuck with me ever since I saw you speaking about that.

Okay, so we've kind of set some of the scene so far. We've got some nice mental models for thinking about this. We referred to the energy and the embodied part and I guess the thing we didn't mention too much was that the growing old thing is going to be, you know, more of an issue over time because while we're getting better at decarbonising the electricity of the internet, we're not doing such a good job of decarbonising the extremely energy intensive process of making electronics right now. So we're only, this is only going to become more acute over time.

So, maybe I can allow you to just talk a little bit about this Hypnos paper, because as I understand it, it was an extension of some of this vision going forward, and I know that it wasn't, you weren't presenting yourself, but I know it was your team who were presenting it at HotCarbon, so maybe you can talk a little bit about that, and maybe say who was presenting, or some of those things there, because, yeah, I enjoyed reading this, it was quite fun, it, similar way, I enjoyed it as well, basically.

Romain Jacob: So Hypnos is a, a recent proposal that we've made to essentially try to quantify this sleeping principle. So in two and a half years ago, we said, okay, we could look at the embedded aspect, we could look at the operational aspect and how to improve them. And we thought back then that the one way was to just try to apply those principles of heaping to wired networks.

And so together with some math students from ETH, we started looking into this and say, okay, in theory, we know how to do this. Let's try. You know, let's try for real, let's take some hardware, let's design a prototype, protocol that would just put some things to sleep and see what happens. What was surprising to us was that the, the theory of how you would do the sleeping in a wired network and how much you would expect to save by doing that was old.

It was the first papers go back 2008 or so, so there's been a while and back then, people were saying, okay, assuming we have hardware that, that allows us to do everything we want, then we could implement seeding in this way and then we would save so much. So they knew that the proposals that were made, they were making back then were not readily applicable.

And so we felt like 15 years later, it's kind of interesting to see where are we today? Like how can we do things? And the key element, key there, was how quickly you can turn on something. You turn it off, you can always turn off something, you take some time, you save some power, okay? But then, eventually, if you need it back on, you want it to react quickly.

You know, I talked about the screen of your phone before. It's always off, and it's fine, because as soon as you press the button, and you touch with your finger, the screen lights up, right? It feels instant, right? So it needs to happen quickly to be usable. Except that in networks, it's not like that, it's, I mean, not, not, at least not today.

So if, if you think about a link that connects two routers, this was the first, the first thing that we started considering. Okay, let's put that to sleep. It's essentially the smallest unit in a network that you could put to sleep.

Right.

Chris Adams: A bit like a lane in a, like a multi-lane in a multi-lane car road.

Romain Jacob: Yeah. I would think about the road network, like, turning off a port or turning off a link in a network would be like. Cutting one road in your network. You know, like here in the city, you have many different ways to go to different end points and you would just say, okay, this street is closed. So you can't use it.

Chris Adams: Ah, I see. Okay.

Romain Jacob: That's kind of like the simplest thing one can do from an networking perspective, except that to turn the thing back on, to reopen the street would take multiple seconds.

Chris Adams: Mm.

Romain Jacob: And it doesn't sound like much, but in the networking area, multiple seconds is a lot of time because a lot of traffic can be sent during this time.

And. If you make things short and not too technical, it's way too long.

Chris Adams: So we're looking, you want milliseconds, which are like thousandth of a second, and if something, it takes two or three, it's two or 3000 times slower than you'd like it to be basically.

Romain Jacob: Exactly. So, without getting too nerdy and too technical, the problem is, we can't do what we're suggesting in the literature because we cannot sleep at short timescales as we were planned. And so we're like, okay, so is it over or can we still do something? And so what we were thinking is maybe we cannot sleep, you know, at millisecond time scales, but we can still leverage the fact that networks, some networks, are a lot more used during the day than during the night.

So we, we have a lot of patterns that are daily or hourly that we can leverage to say, okay, well, we have a predictable variation in the average use of the network. And so when we reach the value to declare night time. Then maybe there are some things we can share. And so we, we try to implement a protocol that we do do.

We say, okay, let's do the simplest thing possible and see how well it works. And Hypnos is essentially the outcome of that. So in essence, it's a very simple tentacle that looks at all of the roads, so all of the links in the network and how much they are used. And then we start turning off the, the unused one.

Until we reach some kind of like stopping condition that we say, okay, now it's enough. Like the rest we really need to keep it. At a high level, this is what we do. So one, one challenge was to get actual data to test it.

Chris Adams: Mm-Hmm.

Romain Jacob: Because if you stimulate a network and you stimulate the utilization of your network, you can make things as pretty or as, as ugly as you want, you know, depending on how you look at things.

And so it was, what was really missing from the literature was precise case study that says, okay, here is the data from a given ISP. Here's what the network looks like, and here's what the utilization looks like. In this network, what can we do? So, there has been a long, very long effort to actually get this data.

And then, the Hypnos paper is essentially say, okay, we have the protocol, we have the theory, now we have the data. Let's match the two things together and see where that takes us. And, we looked at two internet service providers that, that belong to the access part. So, those are, networks that are very close to the end user, where you would expect more of D&I fluctuation.

And we do see that. What we were a bit surprised to confirm is that those networks are effectively underutilized. You want to dare a guess what's the average utilization in those networks?

Chris Adams: I literally couldn't, I have no idea what the number might actually be to be honest.

Romain Jacob: Guess!

Chris Adams: Okay is it like Okay, so I said the national grid was about 40%. Is it like 40, 50%? Like, that's, like, not-

Romain Jacob: Four, four zero?

Chris Adams: Yeah, four zero is like what I, is what national, electricity grid is. So maybe it's like, something like that, maybe?

That's my guess.

Romain Jacob: Now you're an order of magnitude too high. So we are talking a couple of percent.

Chris Adams: Oh, wow! Okay, and the whole point about the internet is that if you don't have one route, you can still route other ways. So you've got all these under, you've got all these things which people are currently on that almost no one is using ever, basically, at like 2%. Okay, alright.

Romain Jacob: I need to modulate this, right? Okay. For the couple of networks that we got, we managed to get access to the data, right? So I'm not claiming this is the general number. I would love to know, if you have data, please let us know.

Chris Adams: Mm

Romain Jacob: But for the networks we could get access to, this is the type of numbers you would see. An average utilization of a couple of percent. And again, going back to what we were saying before, in a data center, things would be different.

Chris Adams: Mm hmm.

Romain Jacob: I actually don't know because I was there a little in data center networking, but I would expect things to be more in the 40 50 percent kind of like what you were mentioning before.

But in an end to end service provider network, the underutilization is extreme. There are various reasons for that, but it tends to be the case.

Chris Adams: That's really interesting, because when you look at data centers, so like, I can tell you about the service that I run, or that our organization runs, the Green Web Foundation, so we run a checking service that gets around between 5 and 10 million, like, checks every day, right? So that's maybe In the order of like 400 million per month, for example, something like that.

It's, a relatively high number, for example, and even when we have that, we've got around 50 percent, we, we did, we started working out the environmental impact of our own systems recently, and that's with us with utilization around 50 percent for our systems and in cloud typically you'll see cloud providers saying oh we're really good we're 30 or 40 percent like the highest I've seen is Facebook's most recent stuff about XFaaS and they say oh yeah we can achieve utilization of as high as 60 odd percent right but for lots of data centers the kind of old Data centers would have been in the low digits.

And you've had this whole wave of people saying, well, let's move to the cloud by making much better use of a smaller number one. So it sounds like the same kind of ideas of massive underutilization and therefore huge amounts of essentially hardware, you know, it seems like it's somewhat similar in the networking field as well.

And there's maybe scope for reductions in that field as well. Okay.

Romain Jacob: Exactly. And so, I want to make it clear, like, it's not happening this way because operators are idiots, right? It's just, there are a number of reasons why you have such underutilization. One what I would say is probably the main one from a decision point of view is that you want to provide high performance for number of connections in your network.

So to reach from point A to point B, you want to make sure that you want to have the lowest delay typically. And that requires to have a direct line. Do you have other concerns that are that things do fail in networks. Link failures happen and they can be quite drastic. You operate like a physical infrastructure in a country where people leave and work, you have incidents, fibers get cut, and those are things that take a long time to fix and so on.

So you want to have some resiliency in your network. So that if some part of the network goes down, you can still reroute the traffic the other way around and still have enough capacity to serve that traffic. So you have some names that are not used by default intentionally. So you get to a 2 percent or a couple of percent average.

But you don't want to be at 50 percent because if you are at 50 percent and something really goes down, then you may run into a situation where you don't have enough capacity left to run your business. So the point is, we have such a high underutilization and something that I don't think we explained so far is in network equipment, so routers and switches, you have very little proportionality.

What I mean by that is that the amount of power that is drawn by a router. It's essentially, from at a height, it's not exactly true, but at a high level.

Chris Adams: Hmm.

Romain Jacob: The amount of power drawn is almost independent or varies very little if you send no traffic at all or if you send at 100%.

Chris Adams: Okay.

Romain Jacob: So, what it means is that if you have a router that you use at 1 percent of its total capacity, you pay almost 100 percent of the power.

Chris Adams: It's almost like one person in that plane going back and forwards, for example. Like, if I'm going to fly, there's, you know, if I'm going to fly somewhere and I'm the only person, it's going to be the same footprint as if that plane was entirely full, for example.

Romain Jacob: Kind of, yes. It was the same kind of idea. And this is why for us, investigating this clipping was kind of interesting because we know we have such method underutilization, although I probably would not have guessed it was that low, and it wastes a lot. Third, we are essentially operating most of those links at the worst efficiency point possible. And so we try to remedy this and it goes one step in that direction.

Chris Adams: I see. And I think one thing that you mentioned before was this idea, you can power these things down and you know there's very, because there are alternative routes through the network at any time, it may be the case that even if you do have these things powered off in response to upticks in demand, just like with, say, national grids, people might. You know, switch on batteries to, or feed power into the grid from a battery or possibly a peak of gas plant.

You have, you still have the option of switching these route, these links back on when there is mass a, a, a big peak in power, for example.

Romain Jacob: Exactly. And it's the same with the kitting protocol we proposed, right? So, it still makes sense to have those redundant links deployed, you know, those fibers laid out. And then you may say, yeah, but we've paid all this effort to actually install this and it's there. Why should I not turn it on? Well, because it consumes energy whether you use it or not. That's for one. And second, It's good to have it in case you need it. But you can turn it off so that you save energy. If you can turn it up quickly, right, then it goes back to what I was saying before. The turning of quickly part is still problematic today.

Chris Adams: Hmm.

Romain Jacob: So orders of magnitude that the time it takes to actually do this would be in 10, 10 seconds, roughly a few seconds, let's say, up to more, a minute or so.

So then what, what do you have to wait? Yeah. The benefit you gain by turning links off in terms of energy versus the time you may have to wait until you go back to a good state in your network in case you have some failures in your network. And of course you need to multiply that risk by the likelihood of getting such link failures.

So if, let's say, if you have a doomsday event that, you know, will just kill the network error, but that happens one every hundred year. Maybe you can be fine having a day to day management policy that says, okay, to manage this doomsday event, we will need an hour long, but in all the rest of the time, it will be fine and we'll save energy every single day.

You know, you, you have weighed the pros and cons of a strategy in terms of performance and in terms of energy usage.

Chris Adams: And presumably, one thing that you've entioned is because you mentioned that you often have these regular, kind of, predictable cycles, like, most people don't, you know, fewer people use the internet when they're asleep than when they're awake, for example. Like, it sounds really silly, but like, yeah, you're going to see these predictable patterns.

Some of the work with the Hypnos paper was basically, essentially taking some of these things into account. So you can say, well, you need to have this buffer, but we don't have to have the buffer massive you don't need to have every single car in the world engine on idling just in case you need to use it you can turn off some of these car engines for it so that was the kind of idea behind this.

Okay neat so I've used this car model a few times but it suggests that actually think about how, the amount of energy usage and how it scales with how we use the Internet. It might not be the correct mental model. And I just want to kind of run this by you, because this is one thing that I've been thinking about recently is that a lot of us tend to instinctively reached to a kind of car and driving and burning fuel model, because that's how a lot of expo experience costs of energy a lot of the time, right?

But it feels almost like if you've got this thing, it may be a different model might be like, I don't know, like bike lanes where there's a matter of time that you need to build something. You might need to light, make sure a bike lane is well lit, for example, if you do use, but the amount of people using the bike lane that isn't the big driver of emissions in this, for example, maybe something like that.

Romain Jacob: Yeah, I was about to say, I think the analogy is not wrong per se, it's just a matter of the trade off between the, the infrastructure cost and the driving cost, let's say. So let's assume you, you're using a, a mean of transport, whatever that may be. That has a cost X per kilometer, but then you need light and you need, I don't know, cooling or if you're using something that works on under like, I don't know, superconductive environment, then you need extreme cooling. And so the cost for the environment gets very high. I think the superconducting thing is actually a, a, a pretty, a, a much, very much closer analogy to how the way network works.

And you need to spend a lot of power, or to draw a lot of power, just to get the infrastructure on. But once the infrastructure is on, once you get your superconductive environment, then traversing this environment is very cheap.

Chris Adams: Ah, okay.

Romain Jacob: And networks are a bit like that today, right? So turning the wires on costs a lot, but when it's on, sending the bits through the wire, it's pretty cheap.

Chris Adams: Ah, I see, and if I understand it, when I've spoke to other people who know more about networking than me, they've basically told me that at some levels, even when you're not sending any data, there is a signal being sent that basically says, I'm not sending data, I'm not sending data, I'm not sending data, just to make sure so that you've got that connection so that when you do send some data, there's a fast response time.

So, just because we aren't perceiving something doesn't mean there isn't energy use taking place for example. So there's maybe some leakiness in the models that we might instinctively just use or intuitively try applying when we're trying to figure out, okay, how do I make something more sustainable for example?

Romain Jacob: Yeah, this is very true. And it also, it gets a bit more detailed than that. It also depends on the type of physical layer you use for sending your information. In networks today, you have, I think, I guess we could differentiate between three main types of physical layer. One is the electrical communication, so you send an electrical signal through a power rail.

You have optical communication, so essentially using light that you modulate in some way. And then there's everything that is kind of wireless and radio wave communication. So I'll leave the wireless part out because I know less about it and it's a very complicated bee. But if you compare electrical to optical, things work kind of differently.

In the electrical environment, you, you can, you have essentially a physical connection between the two points that try to talk to each other. And so, when the physical connection is there, you may send messages as you were saying before, like, I'm not sending, I'm not sending, I'm not sending, but you can do this, for example, once it be, I don't know, 30 seconds or so.

It will be enough to, yeah, keep the connection alive. Whereas if you use optical, it's different. Because if you use optical communication, the line does not exist. The line between the two exists only because you have a laser that is sending some photons from one end to the other. So, where it's different is that a laser is an access component.

You need to, to, to send energy to create this link between the two ends.

Chris Adams: Mm.

Romain Jacob: And so, now, it's not that every 30 seconds you need to say, I'm not sending anything. It's like, all the time, you need to have this laser on so that the two endpoints know they are connected to, to each other.

Chris Adams: Ah, okay.

Romain Jacob: And it's actually one of the reasons why the early ideas about tweaking are not so much in use today is because they don't work nicely with optical communication.

And optical communications are the de facto standard in networks today, in the, in the core of the internet and in data centers as well. For reasons that we don't have time to detail, optical is the primary means of communication. And it is by design the laser needs to be on for the link for the communication to exist.

Whether you send data or not.

Chris Adams: Alright, okay, thank you for elucidating this part here. So it sounds like the models we might use a lot of the time, as lots of, when you're working with digital sustainability, it's very common to look at a kind of figure per gigabyte sent, for example, and like in some cases It's better than having nothing, for example, but there is a lot of extra nuance here.

And, there is, we have seen some new papers, I think there was one paper by David Mytton, who, that we'll share a link to, he's been speaking, he's, he shared one recently about the fact that, there are other approaches you might take, for example, for this. There, if you could, just brief, it'd be really nice to just touch on some of that, if we could, and then just, and then to add some extra nuance, realize that, like, It's not that there is no proportion, because there is something you need to do.

Maybe we could just talk a little bit about some of the things that David Mytton's been proposing as an alternative way to figure out a number here, because I'm mainly sharing this for developers who get access to these numbers, and they want to make a number go up or down, and it's useful to understand what goes into these models so that you are incentivizing the correct interventions essentially.

Romain Jacob: Yeah, of course. So that's actually a very important point, I think. You will often find if you look in the, on the web or anywhere. Figures are in energy per bit, or energy per X, or energy per web search, or energy per email sort of thing. Whatever we can think about whether computing such numbers make sense, what, what is very important to understand is that those numbers were derived in an attributional way.

That means that you take the total power cost of a system. And then you divide by the number of bits that were transmitted. If you take a network, you take the sum of the energy consumption of all the routers and all the links and all the calling and all of everything. And then you look at the total amount of traffic you've sent over your reporting interval, like a year.

And you take one, you divide by the other and ta da, you get energy per bit. That is interesting. That is interesting to get an idea of how much, how much energy you spend for the useful work you've done in that network. But it should not be interpreted as, this is the cost for a single bit, because if you do this, then, and that would be a different type of reasoning that we call consequential reasoning.

If you do this, you would then draw the conclusion, the wrong conclusion, that if I have a network that has, I don't know, a hundred kilowatt hour, if I send a hundred gigabit more, I will use ten kilowatt hour of-

Chris Adams: It increases entire system by that rather than my share of this, for example.

Romain Jacob: Exactly. Except that it's not true. It's not true because the total number in watt, in energy per bit accounts encapsulate all the infrastructure costs. And those infrastructure costs are constant, they are independent of the amount of traffic. And so this summary statistics is useful in order to track the evolution of how, how much is used, how much is your network used over time.

But it's not good to predict the effect of sending more or less traffic. And it's a subtle thing that if you overlook this, you can make the very wrong statement and make bad decisions. And so this is what kind of like these papers you refer to try to highlight and explain. And say that you need to have a finer view on the, the energy per unit that you're interested in.

It's a bit more subtle than that. People should read the paper. It's a great paper. It's very accessible. It's not too technical, I think. And it's great for people that are interested in this area to get a good primer on the challenge of computing the energy efficiency of a network. I think it's really a great piece.

Chris Adams: Okay, cool. So basically the, I think one of the implications of that is that let's say I'm designing a website, for example, if I make the website maybe half the size, it doesn't necessarily mean I have half the carbon footprint of it because some of the models we use and they're popular, they are an improvement on having nothing, but there's extra nuance that we might actually have.

I say this as someone who works in an organization where we have a library, we have one, we have a software library called CO2.js. We have a transfer based model for this because this is one of the ones that's most common that is just like one of the defaults. We also have like an issue open specifically about this paper because there is, when you're starting out, you will often reach for some of these things for this.

And while there's benefit and there's some value in actually having some of these models to help you work out, it's also worth understanding that there is extra nuance to this. And they can end up with slightly different incentives for this. This is something we'll talk about carbon aware as well because again, different ways you measure the carbon intensity of electricity can create different incentives as well. So, like, this is one thing we'll be, I guess, we'll be developing over time, but the thing that I just, if we may, I'm just going to touch on this other thing before we move on to kind of wrap up on this.

This can give the impression that there is no proportionality between using digital tools, and, like roll out of extra infrastructure and if you said there's no link that would be an oversimplification as well and I think we're gonna one of the previous guests Daniel Schien he came on he spoke about some of this and maybe you might paraphrase some of this because I think his this perspective is also very helpful and kind of illustrates why we need to be doing coming up with better models to represent this stuff.

Romain Jacob: Yes, exactly. Thanks for bringing that up. That is also extremely important. So I've said before, power is kind of constant. It doesn't depend so much on how much you send. Two, two things to keep in mind. First, there is some correlation. So if you do send more traffic, there will be an increase in power and so you will consume more energy. That is true. And the work that I'm doing and fuel make that even more so in the future. So what we are trying to do is essentially say. We tried to find ways of reducing the power draw when you're under low utilization. And if we were successful in doing that, by sleeping and by other methods, then it will create a stronger correlation between traffic and power.

Right? So, and this is actually good, right? For energy efficient theories, the closer you are to proportionality, the better. So if we are successful, then the correlation will increase. And then sending more bits or, or having smaller website will have a stronger impact, in energy consumption in carbon footprint.

So that's one aspect.

Chris Adams: Mhmm.

Romain Jacob: The second aspect was also extremely important. You mentioned already the, the work of Daniel Schien that is great about this is to think about the internet in, in, in a different timescale. If you look at one point in time right now, the network is the static element. There's so many nodes in the network.

There's so many networks and therefore today, if I send more traffic; be low impact. However, if you put a longer timescale and you look at a one year, six month, or ten year horizon, what happens is that when people spend more traffic, you see the utilization of the links going up, and that will have a future consequence of incentivizing people to deploy new links, to increase the capacity of the network.

Chris Adams: Hmm.

Romain Jacob: Which means that over a year, so over time, as you send more traffic, you create more demand. As you create more demand, you will create more offer. That means scaling up your network, and every time you scale up, almost away, you will increase the energy consumption of the network, right? So, you will further increase the infrastructure costs.

So, as you send more traffic, as you watch more Netflix today, It does not consume more energy, not so much, but it will incentivize the network to be scaled up, and that will consume more energy. So, there is a good reason to advocate for what is known as digital sobriety, to be, to try to use less of the network or to make a more sensible use of the network, because if we use it more, It will incentivize future increase of the digital network size and therefore future increase of the energy consumption.

Chris Adams: I see. Okay. So basically, if you like set these norms of all this extra use, even though you're not making these changes in the meantime, on a kind of large, on a multiple, multi year timescale that people make investments, like infrastructure investments on, they would then respond to make sure that they've got that kind of headroom available over time.

And I think that's actually some of the work that Daniel has been doing to model, because there is no way that we can do that. We're going to deploy new infrastructure where there being zero carbon footprint, even if everything is green. So there is a, there's an impact there that we need to be mindful of.

That's some of the work that he's referring to there. We'll share a link to that paper as well, because I'm not quite sure how Okay, I know that we can't model that in co2.js, for example, in our library, but he's, this is literally the cutting edge work that I think he's been doing. And he's, last time he was on, he was hiring for some researchers to find out, okay, how do you represent this stuff?

Because when we think about large organizations of the scale of Amazon or Microsoft who are spending literally tens of billions of dollars each year, then you do need to think about these kind of multi year, decade style infrastructure kind of investment scale. Okay. All right. So, we've gone really into the details, then we've spoken at the kind of macroeconomic level now.

I wonder if I can just bring this back to the kind of frame for developers who are like, oh, this sounds really cool. How do I use some of this? Or what would I do? Like, if you wanted to have an internet that was able to kind of sleep more and could grow old, are there any ideas you might use? Like how might it change how you build, for example?

Are there any kind of sensibilities you might take into account? Because as I understand it, some of the things with Hypnos were primarily designed to say, this is how you can do this without forcing people to make too many changes at the end user level. But there may be things that as a practitioner you might make things more conducive to or something like that, for example.

Romain Jacob: Yes, definitely. So I think it goes back to the question we had just before about Daniel's work, about looking at the longer time scale perspective. I think as an end user, as a software designer, I think thinking about sobriety is something that everybody should be doing. It's not just for sustainability.

I think one very recent Environment Variables podcast was about the alignment between the sustainable practices and the financial operations, and in many cases, those two things align. In a similar mindset, if you think about web design, this, if you look at the system, the WebW3C sustainability guideline, they align pretty much almost perfectly with the accessibility guideline and with the performance optimization guideline. Why? Because a smaller website will also load faster and, you know, get people faster to what they want. This is the content they really want to consume. So, there's general value into being as, modest in your demand from the system or from the network as, as possible and for the compute as well.

It's the same thing. Today, it does not yet translate into net benefits. At the network level, but it might in the future. And, you know, somebody has to stop. So you need to, I need the efforts of all sides in order to, you know, make that work. In the networking domain, I know there have been some people studying this from a theoretical point of view where you would say, the end user could be able to say, I want to, I want to place a phone call.

But I'm willing to wait for, I don't know, 20 seconds or 30 seconds before my call is being played. And if you have an ecosystem of users of that network, where the sufficiently large share of users are so called delay tolerant, then you can optimize your network in order to save in resources. So saving energy and ultimately in reducing your carbon footprint.

In the more traditional networking domain, one could envision something like that. There is no work in this area, as far as I know. One way you can think about this would be, the incentive would be pricing. That you, you, you could say, okay, I'm, I'm winning. So not so much to wait the most, most likely to cap the bandwidth I can get out of the network.

But you would, if you were to say, I'm winning to get at most, I don't know, 100 megabits per second in high utilization times, then you would get a discount on your internet deal. I think that's sizable, that's possible. One quick working thing that could happen. But that would be more like a global effect, like it's between the user and the internet service provider.

If you're a software developer, If you think about how your application could be built in such a way, I honestly don't know. I think it's extremely easy today, technically speaking, to have any sort of flagging where your application can say, I'm data intolerant, I can wait, I will not use more than an egg.

One can do that, that's easy. Your network can get that information. The tricky bit is, how would the network then use that information to route traffic in a way that would save energy? That is much trickier.

Chris Adams: Ah, okay, so that sounds like a possible route that people might choose to go. Because I think, I, I know, for example, there is some work in the world of streaming, where there was a notion of a, I think it was the gold button, that was put together by the Greening of Streaming group. They were basically saying, look, most of the time, I, if I'm looking at television from across the room, I can't really tell if it's 8K or 4K.

So, allow me to, you know, have a default which lets me kind of, reduce the resolution or the quality so that when there's lots of people trying to use something, we can see the amount of data reduce somewhat. And that reduces the amount of kind of extra peak capacity people might need, for example. These are some ways to kind of make use of the existing capacity that lives inside the entire network to kind of smooth off that peak as it were, for example.

That's some of the stuff that we might be looking at. So it's very, in some ways, it might be, kind of providing hints to when you send things over the network. And I think there's actually some work that we've seen from some existing tools. I know that Facebook's serverless platform does precisely this.

And there is also some work in Intel, we'll share some links to this, where when you have a computing workload, you can basically say, well, I'm not worried about when this gets delivered, for example, or I have a degree of, as long as it happens before this time, it's okay. And this does provide the information for people running these systems to essentially, like, move things around to avoid having to increase the total capacity, for example.

So you make better use of the existing capacity you have before you have to buy new capacity or deploy new wires or anything like that. That seems to be what you're kind of suggesting.

Romain Jacob: In the cloud computing world, that does exist for real. Yeah, for sure.

Chris Adams: Okay, so there's a possible path for future, future research. And maybe this is the thing I, this is what we can kind of wrap up on. So we've spoke and we've done a dive into sleeping and getting old. Right. But that's not the only tool available to us. Are there any kind of papers or projects or things that you would direct people's attention to that you think is really exciting but may not necessarily be in your field that you think is worth, that you're excited about?

For example, because you spend a lot more time thinking about networks than I do, and I'm pretty sure there's some things you might say that that, that other people listening here might, might enjoy following, for example.

Romain Jacob: Yeah. Yeah. So I think two things come to mind. The first is that today I talked about protocol adaptation, about, you know, we, we would put things to sleep and save energy and so on. But one, one key problem we have, we as practitioners in this field and researchers and operators is the lack of visibility in the power data.

It's actually really hard to get a good understanding about how much power is going to be drawn by a given router, depending on the amount of traffic and depending on how this thing is configured and so on. So, this became very clear at the beginning where we started working on this. And so, a big part of my research has been to try to, to develop tools for building datasets to aggregate such power information in a way that people can contribute to and then use in their own research, do their own analysis.

And try to do some predictions about, okay, now, if I were to buy this device, for example, it will cost me so much in embodied carbon footprint that this is how much I could hope to save. Because I know how this device typically operates and how much it consumes. And so, this led to a dataset on a platform project we call now the Network Power Zoo.

Which is actually a reference to another very well known networking data set that was the Network Topology Zoo. It's kind of like a historical reference to that. But it is really a zoo in a sense that it's very broad. From devices that look the same can consume from, I don't know, two, three times more magnitude power.

Whereas it seems there's the same number of ports, the same part of the number of connections, but it can change drastically. So, it's still a work in progress. I mean, the database is in building and we're starting pouring data in. And very soon we'll do an open call for anyone to contribute their own data sources into this database.

So that people can have access to richer power related data.

Chris Adams: For a data informed discussion. Yeah.

Romain Jacob: So that's one thing that is very active for us. It's still very much related to networking, but that's one thing that is not related to protocols so much. More generally, what I think has become clear and clear to me is that if we want to address the sustainability problems in networking, what we need are not really networking researchers, because a lot has to do with the hardware design, and the hardware architecture, and writing good software for optimizing the hell out of the hardware we get.

And those are just not the typical expertise that you find in networking people. So, networking people are a bit at a protocol, but, you know, they don't know as much how the hardware is built and designed. Maybe I should not make such generalities, but it's definitely true for myself. So, we've been poking more and more people from the computer architecture area, from the hardware design to collaborate with us and say, okay, look, we have those sorts of needs.

This is mainstream in embedded systems for 20 years. We still don't have it yet in routers, it's hightime, we need it now. If anyone is working in this area and is interested, please reach out to me, I'll be happy to chat.

Chris Adams: Brilliant, thank you for that. Okay, and I suspect there's some, I'm just looking through our notes. We actually have been in touch on the E Impact mailing list, which is one project, but I think it's by the IETF. That's one of the things that we can share a link to where there's often quite a lot of, if you want to go into the networking, that's probably one of the deeper ones I've found.

Okay, great. I think, is there anything else? I should, we're just coming to time, so I just want to check. This has been really fascinating, and I've learned a huge amount from this. So, if people are interested in the work that you're doing or they want to learn more about this, where should people look to find more about this?

Like, we'll share a link to the paper that you worked on, for example. But beyond that though, where do we find out what's going on with Romain Jacob and his team of research, researchers?

Romain Jacob: So, nowadays the best place to find me would be on LinkedIn. So, we'll add a link to my profile, but my name is not that common, usually I'm findable on LinkedIn at least. Yeah, that's the best place for you to reach out, I'm quite reactive there.

Chris Adams: Okay, cool. So I'll share the link there. I'll also share the link to HotCarbon, which had the paper that you had. If there's a, and if there's a link with ETH, the research institution you're part of, I'll add a link to that as well. Brilliant! Well, this has been really enlightening for me and hopefully other people who've been listening along with this.

Thanks once again for being so generous with your time, Romain, and, yeah, have a lovely holiday over the summer, okay? Take care of yourself.

Romain Jacob: Thanks, bye bye.

Chris Adams: bye! Hey everyone, thanks for listening! Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts.

And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser.

Thanks again and see you in the next episode!

View Details

Producer Chris Skipper is joined by guests Marjolein Pordon of ladylowcode.com fame and Andri Johnston from Cambridge University Press & Assessment to discuss the sustainability challenges associated with AI's increasing energy demands and the role of data centers in addressing these challenges. Marjolein emphasizes the need for sustainable infrastructure and the potential synergy between low-code platforms and AI. Andri shares insights from CUP&A's efforts to understand and mitigate digital carbon emissions, highlighting the importance of transparency and accurate reporting from cloud service providers like AWS.

Learn more about our people:* Andri Johnston: LinkedIn * Marjolein Pordon: LinkedIn | Website * Chris Skipper: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* AI energy demand is ruining Google's environmental goals [06:06] * How AWS helps reduce carbon footprint of AI workloads [12:58] * Roundtable: Data Center Sustainability Plays for the AI Era [23:33] * AI is starving for more power. Can quantum computing help? – Computerworld [34:28]

Events:* Metatalent.ai on LinkedIn: "Thought Leadership Webinar For AI: Your Replacement, or Your Advantage?" [40:10] * Climate-Conscious Websites for a More Sustainable Net [40:38]

Resources:* AI water footprint suggests that large language models are thirsty [24:15] * Underwater data center voyage hits the doldrums - Verdict [26:16] * How data centers at public pools can keep swimmers warm - The Verge [26:36]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

View Details

In this episode we preview the first episode of CXO Bytes. Join host Sanjay Podder as he talks to leaders in technology, sustainability, and AI in their pursuit of a sustainable future through green software. Joined by Dr. Ong Chen Hui, Assistant CEO of Singapore's Infocomm Media Development Authority (IMDA), the discussion focuses on Singapore's comprehensive approach to digital sustainability. Dr. Ong highlights IMDA's efforts to drive green software adoption across various sectors, emphasizing the importance of efficiency in data centers and the broader ICT ecosystem. Listen to the full episode via the links below.

Listen to CXO Bytes:* Spotify * Apple * YouTube

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

**TRANSCRIPT BELOW:

Chris Skipper:** Hello, and welcome to Environment Variables. This is Chris Skipper, the podcast producer, bringing you a very special episode of Environment Variables. Today, I'm excited to share with you a preview from our new podcast series, CXO Bytes. Hosted by Sanjay Poddar, Chairperson of the Green Software Foundation.

CXObytes dives deep into the intersection of innovation and sustainability within the tech industry. In each episode, Sanjay will be joined by industry leaders from the C Suite to explore practical strategies for greening software while driving enterprise growth. So without further ado, let's get started.

Let's listen in on a sneak peek of the first episode.

Sanjay Podder: Hello and welcome to CXO Bytes, a podcast brought to you by the Green Software Foundation and dedicated to supporting chiefs of information, technology, sustainability, and AI as they aim to shape a sustainable future through green software. We will uncover the strategies and a big green move that's helped drive results for business and for the planet.

I am your host, Sanjay Podder.

Hello everyone. Welcome to CXO Bytes. This is our inaugural podcast on how do you use green software for building a sustainable future. This is a new podcast series and the whole idea behind it is, you know, embracing a culture of green software, it needs to come from the top. And we therefore want to talk with decision makers, with business leaders, with leaders who are running nation states like Singapore, for example, at C level.

You know, how are they driving this culture change when it comes to digital sustainability and green software, for example?

Today I am super excited to invite Dr. Ong. She is the Assistant CEO of IMDA, which is the Infocomm Media Development Authority of Singapore. And we are going to chat on how IMDA is championing digital sustainability as well as green software. Welcome, Dr. Ong.

Dr. Ong Chen Hui: Thank you for having me on your inaugural podcast on green software.

Sanjay Podder: And you know, I had my own selfish reason for inviting you because while the Green Software Foundation has been interacting with many, many large businesses across the world, IMDA and Singapore GovTech, these are two members of Green Software Foundation who represent the government, right?

And we all know the very important role that government will play in sustainability in general. So I wanted to understand from you, you know, how are you looking into this space? So we will talk a lot about that. The other aspect is probably to begin with, for our audience, a perspective on what is IMDA.

You know, what is your specific remit, what you are trying to do in Singapore, if you can give us, you know, a few insights into that.

Dr. Ong Chen Hui: Okay, so here in Singapore, of course, climate change is actually something that is a bit of a existential thing for us, us being a small nation state and we're also an island, to us, climate change and the associated rising sea level is a matter of concern. Right? So, as a result, we have put in a green plan that states our, sustainability goals by the time we reach 2050. And this is actually a whole government effort. So, I don't think it is a case where it's one ministry or one agency that's responsible for the whole world. It is about the whole of government working together in order to make sure that we meet the goals of our Green Plan.

Now, what are some of the things that we are doing? Many things, for example, the National Environment Agency is actually rolling out some of the regulations. We have things like e-waste management, for example. Just now you mentioned GovTech, which is our sister agency. GovTech is also rolling out green procurement when they're actually procuring software solutions. Within IMDA, we are responsible for some of the industry development. We're also what we call a sectoral lead of the ICT sector. So, our own green strategy, comprised broadly of three different strokes. The first is about greening ourselves as an organization.

The second is really about greening the sector that we are responsible for, that we are leading. So, in that case, there will be things like the telecommunications sector, the media sector. And the third thing we want to do is to enable our ICT solution providers to provide green solutions to the broader economy so that we can scale the adoption, we can ease the friction out there in the ecosystem.

So essentially, that's greening ourselves, greening the sector, as the lead. And the third is really to kind of provide solutions through the ecosystem so that the wider community can actually benefit.

Sanjay Podder: Now this is really a full 360 degree kind of approach and it is phenomenal. And, I was, I was wondering, you know, and you mentioned briefly on Singapore being an island state. I was thinking, why digital sustainability? What will happen if Singapore decides not to do it, for example, right? Do you have a point of view, say, because, you know, there are many different levers of, sustainability, you know, I can understand the larger sustainability, but what is the importance of digital sustainability?

Do you think it's an important enough lever or maybe you can look at nature biodiversity or something else, right? So specifically for digital sustainability. What is it that triggers IMDA that this is a important initiative? And I'm, I'm seeing this is my second year in Asia Tech that, you know, this is something you give a lot of importance to.

Bringing in leaders from various organizations. Doing deep deliberation. I also remember last year, you brought out your new data center standards, I think increasing the temperature by one degree that has an implication. If you could throw a little bit more light on digital sustainability in particular,

Dr. Ong Chen Hui: Mm hmm.

Sanjay Podder: why do you feel that's a very important lever for a country like Singapore and maybe for many other countries around the world?

Dr. Ong Chen Hui: Yeah. Well, I think you're actually exactly right that when we are trying to drive sustainability, actually there are many different strokes. Some of it includes looking at energy sources and all that, which actually is also very important for Singapore because we are small. We do, have to look at, different kinds of energy sources and how we can potentially actually import some of them, right?

Now, when it comes to digital sustainability, actually our journey, I would say started many years ago. Maybe more than a decade ago, when we started looking at, some of the research work within the research community about, making sure that our data centers, can operate more efficiently in the tropical climate.

Now, data centers, comprise of almost a fifth, of the ICT carbon emissions. And because they are such a huge component of the carbon emissions, of course, their efficiency has always been top of the mind. Now in the tropical climate like ours, a large part of the energy sometimes is attributed to the cooling systems, right?

The air conditioning that's actually needed to bring the temperatures down. So as you rightly pointed out, what we found out is that actually if you were to increase the temperature by one degree, that can lead to a savings of between two to five percent off. Carbon emissions. So, and that as a result, we have been investing in research within our academia, funding some of the innovation projects with our ITC players, in order to look at what actually works and what doesn't.

Because I think in Singapore, regulations always need to be balanced with innovation. So that have kind of, led to what happened last year, which was that we released the first, standards for tropical data sensors. But we wanted to go a lot more, right, because some of those standards, around cooling and all that, that's kind of like looking at how efficient the radiators are in a car.

But we also need to look at how efficient the engines are. And the reality is that, if you look at the trends of ICT usage of software applications. I mean, so much of our lives, whether it is watching videos, watching TikTok, right, our education, around all that, most of this have moved to become, to be enabled by digital technologies.

And when we look at the consumption of, data centers and the kind of workload in it, it is increasing year by year. Now, with the explosion of AI, we know that the trend is probably that there will be more consumption of digital technologies. And those are the engines that sits withinssb the data centers.

And we need to make them efficient. And as a result of that, we have decided that we need to also get onto this journey of greening the software stack. And greening the software stack means a few things. The first is, of course, I think this is still a fairly nascent area. How do we make software more measurable, so that there's a basis of comparison, so that we can identify hot spots that I think is important.

The second part that I think is important is also, given all the trends today, GPUs, CPUs all needing to work together, how do you make them work efficiently? How do you process data efficiently? How do you make sure that the networks and the interconnects within the data centers are efficient.

I think all of these are worthy problems, to look at. Some of it will rightfully stay, still in the research stage. So we'll be funding, research programs, called the Green Computing Funding Initiative around it. But at the same time, we also think that there are some practices that may be a bit more mature already, and we should encourage companies to actually innovate on top of it.

So we're also conducting green software trials.

Chris Skipper: Hey, everyone. I hope you enjoyed that preview from CXO Bytes. If you want to listen to the rest of the episode, please go over to the CXO Bytes page on wherever you find your podcasts. Just search for CXO Bytes and enjoy the rest of this insightful conversation between Sanjay and Dr. Ong Chen Hui of the IMDA.

And to listen to more episodes of Environment Variables, Please visit podcast. greensoftware. foundation. Bye for now!

View Details

In this episode of Environment Variables, host Chris Adams is joined by Asim Hussain to dive into the complexities of AI's growing energy demands and its environmental impact. They discuss innovative approaches to sustainability, such as using fungi to manage building waste in data centers and the potential for greener materials and practices. The conversation also covers software optimizations to reduce AI's carbon footprint, emphasizing that energy inefficiency cannot be outsourced. They highlight the importance of integrated sustainable practices in tech development, particularly in the face of increasing AI power consumption projections.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Asim Hussain: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Mushrooms eat building waste at Meta's Gallatin data center - DCD [03:35] * Building with Mushrooms to Reduce Drywall Waste — or Cooking Up a New Future for Data Center Construction - Meta Sustainability [06:59] * Solutions for AI's Energy Inefficiency Can't Be Outsourced - Bloomberg [15:42] * BitNet: Scaling 1-bit Transformers for Large Language Models - Microsoft Research [16:34] * Balance effects of AI with profits tax and green levy, says IMF | International Monetary Fund (IMF) | The Guardian [31:09] * Fiscal Policy Can Help Broaden the Gains of AI to Humanity [31:24] * [2406.09645] Carbon accounting in the Cloud: a methodology for allocating emissions across data center users [37:52]

Events:* HotCarbon - Workshop on Sustainable Computer Systems - July 9, 2024 [48:33] * IEEE CLOUD 2024 International Conference on Cloud Computing - July 7 to 13 [48:53] * Masterclass: Become a Sustainable UX Designer - July 8 [49:44] * The Software Measurement Landscape - Workshop 2 - July 9 [50:12]

Resources:* Software Carbon Intensity (SCI) Specification [10:58] * Episode 56 - Mushroom recycling with Joanne Rodriguez, Mycocycle - DCD * Mushrooms eat building waste at Meta's Gallatin data center - DCD * Options to make software greener without changing the code, and how to remember them | Chris Adams [30:17]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Asim Hussain: And now there's a big hoorah in our space because like AI's now gone and

our automation has now gotten the point where even our jobs are now we're all really like nervous and upset and but you know this has been the pressure that we've been applying to the rest of the world with all the industry for decades and decades and it's just now coming to us and affecting us so you know we don't really have a leg to stand on I'd say.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello, and welcome to Environment Variables; This Week in Green Software, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. Today, in our news roundup, we're diving into some of the pressing issues at the intersection of AI and sustainability.

So, with AI rapidly advancing, the energy demands of training and running these models are also seen to be skyrocketing. Posing significant challenges for the environment. We'll also be touching on some legislation for promoting sustainable business practices amongst AI companies and the potential for a green levy to drive investment for greener eco-friendly technologies.

We'll also be talking about some of the latest papers that have been published for people trying to understand and get grips on cloud carbon emissions. And finally, we'll touch on some of the exciting events in the green software community, including conferences, workshops, and masterclasses aimed at fostering sustainable development practices.

Joining me today for today's news roundup is my longtime friend, Asim Hussain of the Green Software Foundation. Asim, for people who've never listened to the podcast before, can I give you the floor to introduce yourself and some of your background?

Asim Hussain: Yeah, sure. So my name's Asim Hussain. I am the executive director of the Green Software Foundation. And yeah, I've been at the intersection of sustainability and software. I've been very lucky to be thinking about the same question about the intersection of sustainability and software for quite a few years now. And yeah, I've been well, mate. I've been, I've just come back from a vacation, which has been long time coming. I do have a little bit of a, cold, so that's what would explain the slightly nasally, annoying nasally sound the audience members are going to have to experience for this podcast.

Chris Adams: So this is with your hot beverage and Nurofen chaser

Asim Hussain: hot beverage. Yeah, that's what I like to do. That's how I like to start every podcast episode is a coffee and a Nurofen, every conversation with Chris Adams has to have a, both a coffee and a Nurofen.

Chris Adams: Wow, that's, one thing to take away with me. All right, folks, I should just briefly introduce myself before we dive in. I am the executive director of the Green Web Foundation. It's a small Dutch nonprofit based, well, in the Netherlands, where we are working towards an entirely fossil-free internet by 2030.

I also am one of the hosts of this podcast here. As well as one of the organizers of ClimateAction.tech, which is an online community, where actually me and Asim first met online before he basically headed off to set up the GSF in its current state. Alright, Asim, are you sitting comfortably?

Asim Hussain: I'm standing uncomfortably.

Chris Adams: uncomfortably at your swanky standing desk.

That's good enough for me. Should we start with news then?

Asim Hussain: Yeah, let's go for

Chris Adams: Alright, okay, so Asim, I was thinking of you when I saw this paper, this story. The first one is a story about mushrooms eating building waste in data centers. So this is a link to the Data Center Dynamics website talking about specifically the use of these, of essentially building-waste-eating mushrooms at the Meta data center and other ones.

And the general spiel of this is that there are now a number of companies which are, essentially deploying fungi, various kinds of fungi, to deal with all the building waste that ends up being created when you might kind of read, when you're essentially demolishing a building or creating a new one.

And, it essentially takes all this waste, and the fungi are able to Essentially, deal with the toxins, and then create something like, kind of, fungi-style bricks that can then be used as a kind of circular building material going forward. And Asim, given that you're our kind of resident mushroom fan, I wanted to just like, see what you thought about this, or if you had any particular immediate like, hot takes or things when you saw this one?

Asim Hussain: No, that's all. it's a great application. In fact, it's not an uncommon application of, you know, what people are applying, you know, fungi in this technology for. It's actually one of the, one of the, one of the, one of the very exciting kind of broader sustainability solutions in this space that there is.

I mean, there's a couple of different types of fungi. You're going to have to pause me at some point. There's a couple of different types of fungi, but there's one particular type was kind of saprophytic, which is effectively what Fungi, the purpose it has in kind this life that we lead is it basically, it's the thing that destroys things that have died. And if it didn't exist, then we'd be basically living on top of this massive mountain of logs that aren't decomposing. So that's one of the things that they're really, really good at. And it's been, it's, there's been a lot in many different spaces, been a lot of active research, a lot of startups, a lot of organizations exploring how to use Fungi to decompose things that they don't normally decompose. And it's actually quite an interesting technique. Because even people, what's so fascinating about the the fungi space is it's, driven in large part by citizen scientists, which is one of the things I love about it. And there's a lot of citizen scientists out there who are doing things like trying to find a strain of fungi, which can decompose certain types of plastics and you would literally do this. You would literally grab a selection of these plastics. You put them in a, you know, you can go online. It's as simple as this. You put it in a blender, you blend up a plastic in your home blender. And then you just have like, as you can probably see behind me, I have lots of jars out there, which have like different strains of fungi, and you would just put that with other material in the jars.

And then you'd collect lots of different strains. Like. Every single kind of mycelium is like of a different strain of it of the same one. So you can have like millions and millions of different types of strains. You go into the forest and you see a type of mushroom you've never seen before. And you're like, ah, maybe that will absorb this plastic. And so there's a lot of interest in this trying to like find those strains of fungi that can kind of absorb and transform, you know, different materials. Obviously certain fungi only in the forest, they only work on certain types of trees. They have like a relationship with them, but you can actually find strains of fungi, which do different things. And kind of the interesting thing about it is about turning them into, bricks like that as well. There's actually organizations out there trying to replace packing material for boxes. But what you do is you basically, you create like, so you take some time. It's not like a foam that you stick in and like 30 seconds later, there's a thing you basically have to Have the thing you want to pack in a box Inside the box you put like a substrate which can be the thing that mycelium grows on you then like almost like impress inside this substrate the shape of

Chris Adams: like the

Asim Hussain: book or something the mold and then you inject it with the mycelium and you put it in basically an oven for like a month. And it comes back out and then you basically spray it off and like the actual mycelium has grown into the shape of the thing. And then you've got something which you can put in the packing crate. And then at the end of the day, you just, it's a mycelium. You just break up and put it into your garden and you, and it decomposes.

There's lots of like wonderful stuff. There's a, great guy called Paul Stamets, who's quite a character. But he's done a lot of, he's done some great TED talks in the use of like fungi and mycelium in, kind of waste and getting rid of waste even getting rid of oil and there's a lot of kind of very active stuff in this space.

Chris Adams: Can I stop you one second there, mate? Cause, cause there's, so you just said Stamets, right? So Stamets hit, so in real life, there's someone called Stamets and in the whole, and that's, so the whole, when they had this whole Star Trek discovery thing, where there was this guy called Stamets who was using like the mycelial internet space thing, that's a direct reference to this dude, basically.

Asim Hussain: That's a direct reference to Stamets, which is kind of, which joins two of my biggest nerd bubbles together in the most beautiful way, but yeah, there's the engineer, and in Star Trek Discovery, how they, instantly, there's a new type of drive, and they instantly can, move to one part of the universe to another, and it's called a spore drive, and you need to kind of enter this kind of psychedelic realm to connect transmission, so yeah.

Chris Adams: My word, Asim, I was not expecting us to dive down that myco rabbit hole for that, but that was a lot of fun. Thank you very much. So you basically said. By doing this, so in this case of packaging, this basically removes the need for like, say, fossil-based expanded polystyrene in packaging, and in the case of materials here for buildings, you would use that instead of having to get a bunch of virgin materials, for example.

This would be like a circular, that's the approach that they'd be using here, right?

Asim Hussain: So what, so the specific approach they're using in this particular article is, I believe it's more about, it looks like they're using, basically trying to get rid of the drywall that they have inside the data centers. So I don't know if it's a particularly from a decommissioning a data perspective or renovating a data center perspective, but they're ending up with a lot of material, which typically you would just dump in a waste fill, but now they've basically got a form of mycelium, which can eat drywall and generate something that's, decomposable, maybe edible.

Yeah

Chris Adams: All right, cool. And so we, this is, mentioning, referencing the metadata center in, I think, Tennessee. But we've also seen Microsoft, as far as I'm aware, Microsoft has also been a bit of, it's been dipping their toes into this field as well. And one of the reasons why you might care about this is that, well, last year, Microsoft's reported emissions, when they released their sustainability report, it was like, up 30 percent and a significant chunk of that came from buildout of data centers.

So we are now starting to think a lot more about the embodied energy in the facilities that are created so that we can actually have data centers, so we can actually use compute, a lot of the kind of compute power available to us, or even some of the AI power, or the kind of sources of AI and stuff like that, because you need, they need to be in a building somewhere to get this stuff built.

And like, this kind of made me wonder actually, Asim, surely I imagine some of this might show up in an SCI score, a Software Carbon Intensity score, if you're purchasing cloud from a certain place. If you've seen a massive buildup of data centers, surely that might have an impact on the embodied carbon for the compute you might be using, right?

Asim Hussain: It could do, it depends on what your, cause in the SCI, there's kind of two components. One is the software boundary, which is "what are you going to include and not include in that score?" I remember us having quite a few conversations in the early days of the SCIs, which "should you include the, like the concrete that was used to pour the floor of the data center?" And I'm not too sure we really, I don't, think anything particularly made its way into the specification, but it has to be, if you're measuring something, it has to be something which drives a choice or a behavior. So, you know, I suppose what I'm going to with this is, if there was a data center, which was particularly built like a zero carbon, maybe built with mycelium or something.

I don't know, but like, if there was a data center, it was particularly built with that choice, then maybe it is something you want to include in the score, because then that can drive an action of choosing one option over another. But if every single data center is effectively built exactly the same way, the discussions we were having was, well, that's just overhead of adding a sec, effectively a coefficient, which wouldn't really drive a decision-making factor. So, I suppose as what I'm going to this is excitingly, if there are data centers that are being built, which are going to have

vastly different embodied carbon profiles, and then you, and then if that was included in an SCI score... and I think as we move forward with SCI, because one of the things that's happening... SCI on its most, we, launched kind of the version one and now 1,1 of the SCI and it's, and it was, it's very bare, very basic. It's designed to be built upon. And so now what the teams are having conversations around is like, if you were to apply SCI to AI, specifically, what does that include? And one of those questions

they want to answer is what,

Chris Adams: building,

Asim Hussain: yeah, like what you include so, so when someone reports an AI score, we can actually start getting to like some apples to apples comparisons. So that's, a conversation that, you know, it's interesting. Maybe we should bring that, bring it up again is do you include the embodied of the data center? But then you also get into the headache of "my God, it's hard enough trying to figure out what the embodied of a chip is."

Chris Adams: Yeah.

Asim Hussain: And now going to ask to figure out like what the embodied, so there's has to be some practicality aspect to this as well.

You know, you know, we have to, there should at least be some models. I don't know.

Chris Adams: So there are models that, as I understand it, there are models for working out the, essentially like the carbon emissions for a kilo of concrete, for example, or stuff like that. Some of these exist. And,

Asim Hussain: exists from a

LCA,

Chris Adams: and there are companies, and we know there's like, in Europe at least, I know there's a company called LeafCloud.

That are explicitly using, are doing, making reused, or, they're reusing heat, but also a very specific kind of data center, which isn't like a very large outta town thing. They have like essentially shipping containers put into places like say greenhouses, where the heat is being reused, for example, and where they're not having to build a whole bunch new buildings. There's also, I think in Switzerland, there's one company, because we maintain, where I work, we maintain a directory of green data centers. And one of them is a, they basically reused a old factory building with a waterwheel that used to be kind of like a clothing factory, and now it's a data center.

So they've essentially reused the whole building shell. They haven't built a load of stuff as a result. So this is one place where this might show up, but in order to do this, you need to have access to the numbers for this. And that's still a bit of a challenge because, yeah, we don't have the, we don't have easy access to these numbers, and like you do say, it's a challenge just thinking about chips, let alone expanding the boundary to the actual buildings instead.

Asim Hussain: Yeah. I mean, at least you have some information when you're running software, like what, you know, you can, now that we've done, a lot of that workings out so you can figure out, you know, perhaps it's this chip, but I think given the secrecy around data centers, I don't know, I think there's going to be,

I don't know.

Chris Adams: It's gonna be a challenge, because while we have this practice of, essentially, water usage and electricity use, so many things being under NDA, it'll be very hard to come up with some numbers without using, like, a basic number. Okay, alright. We have totally gone past talking about mushrooms and data centers into all these other things, but I guess this is part of the whole thing about sustainability and technology.

It's all interconnected.

Asim Hussain: It's all interconnected.

Chris Adams: Shall we go to the next story?

Asim Hussain: Yeah. Let's go for it.

Chris Adams: So this is a piece from Bloomberg, actually, so this is the topic of this is Solutions for AI's Energy Inefficiency Can't Be Outsourced, and this is an opinion column from Bloomberg talking about this projected demand some of the figures which are pretty, pretty impressive, they basically say, in the US at least, it's, there's a projection saying that AI, the growing demands of energy are like, is projected to make up around 8% of the US' power consumption, electricity consumption up from 3% in 2022.

Now these numbers seem a little bit high and they are citing a kind of this arms race of different kinds of organizations, essentially building out these massive data centers but also buying loads and loads of chips, but it does talk about some of the approaches that we're seeing now to kind of rein in some of this growth.

So one of the things was this idea of one-bit architecture, which is essentially, I'm not going to pretend to understand it. And I'm not sure if you are similarly informed in this one, but

Asim Hussain: I'm going to definitely pretend to understand it.

Chris Adams: In that case, I'll hand over for you to confidently bluff it around, just like a ChatGPT would actually, Asim, the floor is yours.

Asim Hussain: I'm going to, I'm asking GPT. No, I'm guessing, and this is, I haven't really, I've, seen it, but because it's one bit and a bit can only be one or zero, I'm guessing what this is, that, you know, instead of like pumping in a number between one and 256 as one of the inputs to a node in a model. Maybe you could just try one or zero. And then output one or zero and then see if that actually still gives you some pretty reasonable results and from what it looks like it might do and you know for those of us I kind of it's like there are extreme inefficiencies you can do when you're working at the bit level in terms of programming and computation and instructions on the chip and things like that because it's so much lower level than the architecture.

I presume that's what it is, which actually to me is. It's really exciting from a, from the level of, this is a software architectural solution, which is effectively, I think what we've been advocating for, a large part of the time, which is, you know, we do need to I hate to use the word code because I don't want people to dive down the, you know, building more. I, well, AI is one of the, one of the few areas I would say where actual code efficiency is extremely important. But yeah, this is kind of, it's interesting. Now that there has been a pressure applied to optimize, the optimization has happened.

Chris Adams: Yeah, that's, so basically, Asim, I think you're about right. Now, when I, remember when I skimmed over this paper before, one of the key ideas was, the one bit approach was, essentially, when you, would be able to, you would use this to encode the difference between different parts of, like a dataset rather than showing absolute numbers.

And one of the things that this allowed you to do was allowed you to just use addition rather than multiplication in some cases. Now, I'm not an AI specialist and I'm not a hardware specialist, but the general idea was by representing things in a more somewhat simple fashion here, you avoided having to make some of the expensive calculations that you would otherwise need to do.

And this basically reduced the energy that you might need to run some of these calculations. So this was like one example. I was quite impressed to see this inside Blumberg because it was a very quite new research, but also really, technical and actually quite promising. So yeah.

Asim Hussain: It's, it, the title is interesting though, isn't it? Cause it's not like, it's not like software making, it's kind of talking about energy inefficiency can't be outsourced.

Chris Adams: Yeah,

Asim Hussain: I just thought it was an interesting, it's like no one really knows or cares or thinks about the software side of the, this whole equation.

To me, this is just like a software optimization. So you would just say like software can be optimized to reduce any AI's energy footprint. It's not, not expressed in that way. It's interesting. Kind of expressed

Chris Adams: there's a couple of things that I think are also really interesting about this piece, in my view, was that it talks about the kind of economics around some of this, and basically the idea of outsourcing this is essentially how we have a bit of a tendency in the technology industry to say, "well, we're just going to have, like, We realize that data centers use loads and loads of power, so what we're going to have to do is just somehow get loads more power."

And so you basically have people talking about, oh, obviously the solution is to deploy loads and loads of nuclear, for example, right? Never mind that these take between minimum 10 years to get built, right? So, what are we going to do in the meantime? A lot of the time it's likely to be coming from things like gas, if you're going to be using something like that.

So that's an issue there. But it's also worth thinking a little bit about these figures that were mentioned in this story. We've seen numbers like 8 percent of the USA's energy consumption by 2030. It's worth bearing in mind that these numbers are often coming from the utility providers in various states, all right?

So like, say, in, say, Virginia, I think it might be, I forget the name of the actual monopoly provider, but there's only one provider over there. And basically I think that's Pacific General. I think that's actually on the, other coast, basically.

Asim Hussain: We've played this game before where you can name all

Chris Adams: was Caiso last time, which was, which is, that's the Independent Systems Operator, which is not the energy company.

The energy companies are somewhat different because it's a, because in many, because they have very specific, if you're in a state where you've got a single provider, they are allowed The only, the reason you only have a single provider is that you have basically had that state agree to have a, what's referred to as a natural monopoly.

So, they basically, the agreement is, we will give you a guaranteed 10 percent net profit plus for your organization, alright? But you need to basically, yeah, as long as you agree to share your plans, For the new infrastructure you're going to build over the next few years, but also you need to justify this in each of these cases.

And when you think about this, if you're going to get a 10 percent net profit from that for any of the energy you, get. Now, what you, if you want to increase your profits, what you need to do is you need to say, "well, I have loads more demand coming. I need to like double my expected demand to double my profits inside this."

Asim Hussain: Oh, I see.

Chris Adams: is one of the things, because this is a lot of the existing providers, they're used to saying, "well, we've got all this extra demand. What we need to do, we need to build a bunch of new gas, fired power stations. And 'cause we know we're gonna make a 10% guaranteed profit on all the infrastructure we, build.

That's basically, you know, we are incentivized to say it's gonna be really, high" basically. So. You, it's, really worth looking at a paper by one, one gentleman, John Kumi, who's actually, who's spoken a lot about this, because 20 years ago, we had the similar thing when you had people in the coal industry saying, "well, coal was what powers the internet, so you need to have more coal fired power plants if you want more internet."

We have a very similar thing happening. In this case as well actually. So it's worth bearing in mind that yes, we do see these kind of apocalyptic forecasts for energy, but you also see that when you do have constraints on this because it's so difficult to build, then we do end up with a renewed interest in energy efficiency.

And even at the kind of like energy level, right, there are different ways that you can basically meet demand. You can meet demand by adding new supply, but you can also meet demand by investing in energy efficiency. And that's, and this is very much what it looks like, so a lot of the ideas you might see at the energy sector, I think, are at least applicable, or at least relevant in what we talk about with cloud, because essentially you're looking at a kind of commodity that you pay for on an hourly basis, or something like that.

Asim Hussain: Well, that's kind of one of the... All I see is there's, a significant amount. There's not a significant, there's a fixed amount of investment and focus that organizations can put into something. And if you present them with an option, either put all this engineering effort to make something more efficient, which costs 10 or buy renewable energy, which costs five and then, well, I'll choose the five one. So I think that's kind of, that's. That's why kind of investment goes in one way or the other. Whereas I suppose what's happening now is that energy is now, we're reaching the point where energy is, and I'm just throwing out numbers here for energy is now costing 12, but the development still costs 10.

So like, well, maybe we'll put some money into development

Chris Adams: Yeah.

Asim Hussain: So that's kind of, and that's interesting that's why you want things like we were talking about levies and money last time. That's kind of why you want to change that balance of it a little bit. And that's also significantly why in the SCI specification, the decision was made not to include any energy offsets or anything like that.

Just because if you gave somebody the option of spending 1 instead of spending 10, they would spend 1. And we want people to spend the 10 to actually make things more

Chris Adams: Yeah, to address the consumption issue, rather than just think about the intensity.

Asim Hussain: Exactly, yeah. But this is exa I'm really excited. And the other thing I was thinking about as you were talking was I was just remembering about my time at Intel. I think this maybe links a little bit to the Nvidia's statement as well. So, I think I might have, I always love telling people this story because I just think it's such a cool word and it's such, it tickles my sci-fi bone so much. But there's a statement they used a lot, which was dark silicon. Have I told you this? I

Chris Adams: No, you haven't.

Asim Hussain: people. There's a dark silicon. And I was like, "Oh, that sounds good. What's the, what's dark silicon?" And what dark silicon is when they're kind of looking at a chip and they put load on it.

And the key thing with a chip is how much can it expel heat and still function at that level. So looking at heat on a chip. And so when they're running a certain software on a chip, they'll put like a, what you call the heat detecting camera on. And you know how they look like this. It's very red, it's very red on the bits that are hot.

And it kind of looks

Chris Adams: Ah, okay, yeah, look at a thermal house,

Asim Hussain: Thermal imaging. yeah. Yeah. Even though the black might not be like ice

cold, quite hot, but like relatively it's cold. And so the things that they would be really like thinking through is like, how come this software, how come half the chip is black?

Like, why aren't you using the rest of the chip? Like you've maxed out the chip, but half the chip is black. And really what it kind of, you know, what it goes back down to is that, you know, we called it, I think I might call it the silicon gap, which is the gap between what engineers are building and what silicon manufacturers are enabling on their chips. And there's this disconnect between, you know, they're, all building, "why aren't you using this, these more advanced chip sets that are more efficient? Why are you using this stuff on this side of the chip?" And so I think that's something that we need to get down and tighten that gap to use this infrastructure more efficiently, I think over the years, from a developer's perspective, it's always been about time to market.

How do we beat our competition? It's never around, how do we use this chip more efficiently? And so I think that one bit architecture is, it sounds like an example of that. It sounds like an example of, we want to leverage the instruction set on this chip to be as efficient as possible. We need to change. Fundamentally how we're architecting and even thinking through algorithmically this code to take advantage of that. And that's, I think it's also like this, other area, which is completely, we're just ignoring, you know, there is this dark silicon and honestly, the silicon manufacturers are like, why are developers not, I don't understand, we put so much energy and time into like

building

Chris Adams: we're only using a of it, right?

Asim Hussain: a The percentage of it, and there's that also, and I'm going to, I'm rambling on for a second, but just one more, one more point. I thought it was really interesting. One of our organization's Entity Data, they did a really great report. It was kind of two years ago now, I think. I don't think we really circulated.

I don't think we circulated that well. And it was, they just, they just looked at Java, you know, Java, like still, there's still a lot of very antiquated Java applications running out there in the world. And they just said, what is the energy difference if we just upgraded, not the code, but the JVM, the underlying JVM.

And that's all they did was I think they upgraded, I cannot remember. I'll find a link to the article and the paper. It was like several steps up. But they were like, "look, most apps are still running on whatever the JVM was they were built with like 10 years ago. And it was a seven, it was a 60 or 70% energy efficiency improvement.

It was unbelievable. The energy efficiency improvement just from grading the JVM. And that was

Chris Adams: Ah, okay.

Asim Hussain: That, and if you think about what that means, what happens was the chips evolve to have different instruction sets. The JVMs, only the modern JVMs are built to the new one. And so if you're running on the old ones, it's just using the old instructions.

So you're not really leveraging the infrastructure the same way, which is why like recompiling software with like, you know, the latest version of the compiler against the latest version of the chip. It's really important. And it again, that was Intel's, when I was at the time, that was their big push.

They were like, "use the latest bits, use stuff that's compiled now using the latest optimizations." 'Cause they saw a lot of people were still just kind of compiling, leaving that binary, letting it run for like four or five years. And then, that's it. And yeah, I'm going to stop ranting now.

Chris Adams: No, that's actually, I didn't realize, I was somewhat aware of things like the JVM, there's like hotspot or different kinds of flavors of the Java Virtual Machine to run this code, and it's somewhat similar to like in PHP land, like when a new version of PHP came out, because it made much better use of the underlying code, the underlying hardware, you saw a massive increase in performance.

And like, you kind of see something a bit like that with Python as well, with the whole global interpreter lock. Like, I can have a piece of Python that'll be running, and it won't be able to use all the other cores in my machine, in my computer, right? So, rather than lighting up the rest of the silicon, it's got just, it's, most of my computer is dark, basically, in that same kind of approach.

All right, yeah. Cool, alright, so that's like one of the approaches that we have, and this is one thing that you could plausibly do. I've shared a link to a blog post that I've, I was trying to explore this to find a way to explain it, to basically explain the fact that you can reduce the emissions associated with code without actually changing the code, by thinking about what options you might have in terms of, like you said here, like you change the VM or something like that, or change when you run it, or anything like this.

And I'll share a link to that, because I've kind of framed it in terms of If, there are three, three things you can change, basically. You can change the time of running something, which is kind of speaks to carbon awareness. You can change the speed, the amount of compute, computation you might be using, the number of cores you might be using something, or you might change the place, like where in the world you choose to run this for the carbon intensity of the underlying energy.

So I'll add that to the show notes because it might be another nice helpful addition to this. Alright, okay, that was quite, that was fun. Shall we look at the next story?

Asim Hussain: Go on. Yeah.

Chris Adams: Okay, the next story is, this is actually from The Guardian, and this is talking about the balancing some of the incentives of the kind of profits that are projected to come from deploying AI with something like a green levy on these profits, basically.

And this is actually, came from that, Left leaning organization, the International Monetary Fund,

Asim Hussain: Oh, wonderful. Great. Great to see them in this space.

Chris Adams: And basically what they are, the argument from the IMF is basically saying, well, you've got all these very profitable AI firms, and they, and we know there's both the social and environmental impact that's taking place here. So what you should actually have is some kind of green AI win for tax, essentially, that will be used to fund some of the, sustainability initiatives.

And like, to be honest, I have a lot of sympathy for this because what we've seen from the largest providers in the last like year is that given the choice between investing in efficiency or investing in more capacity and building loads more data centers, we've seen all the big providers go for building more capacity and like emphasize profits rather than the environmental impact here.

So it looks like we're not the only people thinking about this. The IMF is thinking about this as well. And they're saying, about this. You need something a levee to do this. Do you have any kind of particular thoughts on this? First of all, Asim, because I was really surprised to see this come up from the IMF of all organizations.

Asim Hussain: Yes, I thought it was a very important point. I love the fact because the use of the word levy, and I remember us having the conversation last podcast about like use of the term levy rather than

tax instead of, explaining it, but then in the article actually uses the word tax, like all over the place. Yeah, I think it's really important. Like one of the things I'd say is that like, why is everybody so excited about AI in the first place? In my most cynical moments as as a software engineer, I would say, Our purpose in life is to either find solutions that help people waste more of their time or get rid of jobs and automation.

If you think about kind of why we have been like one of the most highly paid sectors for quite a significant amount of time, it's because building automations, yes, you could argue and helps you deliver kind of projects faster, but it also helps you to do more with fewer employees. It decreases the.

You know, the earnings potential, the, a lot of this stuff from that perspective, and now there's a big hoorah in our space. Cause like AI is now gone and

our automation has now gone the point where even our jobs are now we're all really like nervous and upset. And, but, you know, this has been the pressure that we've been applying to the rest of the world with all the industry for decades and decades.

And it's just now coming, to us and affecting us. So, you know, we, don't really have a leg to stand on, I'd say. We also. There's nothing we can do. It's happening is the only other thing I'd say. There's no, you know, we have to just accept it and move forward. But yeah, I really liked the idea of that because like, let me put it another way.

Like there's this huge kind of bro down AI tech bro showdown with like, well, I think Sam Altman posted something a year ago now, which deeply disturbed me. And he said he wouldn't be surprised, I think within the next couple of years, if there's a one person unicorn startup, which is a single, like, billion dollar organization run by one human being. And I was thinking to myself, like, that might actually be true. And I would, you know, I do, there is a chance that would be true. might happen in the future, but how do I feel about that? What is the human impact to that? I mean, what is the green impact to that? So I'm now going beyond green because I think that there's like this AI is going to make a few people and organizations immense amounts of power and wealth. How do we have ways to, redistribute all of that and to kind of add a level of fairness to, the rest of society? Is it okay? And so from a green level, absolutely. But I'd also argue from a societal level as well, like, like, you know, like when we talked, you know, how about this? When we spoke about the green transition, it was impossible for us to have like a proper conversation about the green transition without having a real conversation and talking about how we're going to transition the people who are employed in the fossil fuel industry over to other areas. I don't see having, I don't see us having that conversation here as well.

Like it's just ignored. And so I think that's something that we need to have is like, is if you're, if you want to have. The opportunity to get this much power and money and wealth, I think it should come with a certain amount of social responsibility to, you know, be a green levy in terms of the green ones, but I think it actually should be broader than that. It should be, you know,

Chris Adams: So address some of the. Some of the inevitable costs that might be incurred upon society to provide to, like, ease that transition. Okay,

Asim Hussain: yeah.

Chris Adams: I was not expecting you to go there, Asim, but

Asim Hussain: Well, I feeling it.

Chris Adams: Bang yeah, that's usually me kind of jumping up and down, actually. All right, okay, that

Asim Hussain: How do you feel about it?

Chris Adams: I think, so you said this idea, like, I feel uncomfortable about a billion dollar startup with a single person.

And I, okay, how many, we're not that far from it, I think, because if, actually, no, we've been, so if you think, how many people work for WhatsApp?

Asim Hussain: WhatsApp! I was WhatsApp, I think it 11

Chris Adams: was purchased for $12.6 billion by Facebook a few years back, right? So that's not that far away on a kind of per person basis, but that's not a single person.

But you've got to realize that like, you know, if that was probably a lot better for the people who own shares in that than the people who are working for this. And we have seen multiple cases. We've seen cases like when a company has to choose between keeping on staff to work on something and getting rid of them, and then spending multiples of the staff's wages on buying their own shares to kind of in increase the cost, increase the share price. We've seen the decision that people have been taking, and there is the, I think that this is a thing that needs to be addressed. 'Cause the current, if we're going to assume that, if we're gonna accept that digital is gonna be the, this thing which is just as important to our lives as access to water or you to or energy or anything like that then you probably want to have a discussion about okay well how are the dividends shared well how is the upside shared in an equitable fashion so that we don't end up with people rushing outside with guillotines or in the very least right like it's not good for social cohesion basically so that's my the view that i might actually have on some of this

Asim Hussain: No, that's a, really, I think that's something that people, I've been, I don't know, should I say this?

Chris Adams: I'm going to stop you because it's coming up to 40 we've got one story, so we can, talk about societal accounting, all to carbon accounting, this new paper, which I think is really interesting and we both were nerding out about it before this call. So this is a new paper from Google, Carbon Accounting in the Cloud, a methodology for allocating emissions across data center users.

So, We can totally talk about the societal aspects of cloud computing here. But this one here is really interesting because this looks like one of the most interesting papers about how you apportion responsibility for your use of cloud services when, using these things. And for the longest time, we've had a real struggle because we haven't had access to any of these numbers.

And this paper really. Lays out a bunch of really interesting ideas with lots of really helpful diagrams, and it dies into how inside Google, people allocate carbon emissions for both internal use, but also for cloud customers. It's a really, fun paper, but it is also quite a significant piece of work.

Read. Like, me and Asim were quite excited about it, but we realized this is almost like a kind of book club kind of paper to read through, basically.

Asim Hussain: Yeah. Yeah. Yeah.

Chris Adams: So, Asim, I'll hand over to you because, there's a couple of things I'd like to draw attention to, but I suspect there's some things that caught your eye as well, or at least maybe you might have some context about why the two of us might be so excited about this.

Asim Hussain: Well, I just think, I think it's really exciting. Well, I get really excited when any organization does such a deep, thorough analysis of their emissions. The thing I'm kind of like going through as I go through this is like, part of me is like, I'm going to try and like represent some of this stuff as an impact framework manifest File because I can read an impact framework manifest file and I can compare it and I can look at it and I can know what's going on. Like one of the first things that the paper outlines, the approach that Google developed to quantify location based emissions of its individual products. And now I'm now like, I now need to dive into this paper to understand, well, yes, I'm understanding the, my definition of location based. However, I'm also seeing references to CFE, which to me doesn't factor as

Chris Adams: CFE being carbon-free energy

Asim Hussain: carbon-free energy So like, there's like a lot of nuance to this stuff. and yeah, I I would probably, as an experiment for me to try and understand the paper, I might try and represent some of this stuff as a manifest file. 'cause for me that's quite useful as a way of, learning something in, in a way, in such a way where I can compare and contrast it to other methods and methodologies as well.

But it looks very, interesting, very exciting. And when Google first worked on its carbon dashboard as well. They were the only organization to have done it the slightly different way, which is kind of like bottom up, like from products and services up towards the top, and now IBM has actually done actually to give IBM some credit as well. And they've got great white paper as well. If you're not ready, I'll send it over to you, Chris. they've done another approach is kind of bottom up as well. And so they're the only two organizations that have gone bottom up. The other ones have gone top down and I'm always excited when people go bottom up, because then you get the data with the granularity, the level of products and services that people actually use, which they drives.

Which is what you need to drive emissions reductions. So that's it. I haven't read, I haven't read almost any of this So I'm interested to get Chris's, if you've got any time, I don't know. What are your hot

Chris Adams: So, the thing that really caught my eye from this is that it talks about some of the ideas that Google has been doing that other organizations aren't so open about. So, for example, you have like a given amount of capacity that might be available inside this. Now, what Google have done previously is they've kind of said, well, We know that we've got a certain amount of, kind of, energy that's coming from green sources and we've said that we want to have a percentage of our energy that is always running at, say, 100 percent carbon free, for example, right, and they, Google have an approach where they say we count something as carbon free if it's matched at the time of use and if it's I think it's on the same grid.

So it's not literally a solar power, but a set of panels on the data center. It might be a wind farm that's where you could plausibly deliver the power to that place. And they use this to kind of represent the amount of clean capacity as something which they call a virtual capacity curve, because it changes over the time of day, basically.

So they talk about in this paper, there's some production, there's some production loads, like that always have to run and always have to respond very, quickly. And there's things where they've got a Bit of freedom in how they move it around and I think this is actually quite interesting because they talk about where they have some flexibility inside this and they talk about how they account for a bunch of that because it's the first time I've seen a paper, A, talk about this, but also talk about the fact that there's like, a set amount of kind of idle power then there's amount of power that will kind of ramp up and down based on the amount of use you're introducing they do they speak about a bunch of really interesting things inside this and the thing that i think there's like there's a couple of figures which i really find like really quite fascinating actually and the fact that there's like one thing like If you are at all interested in, like, Sankey diagrams, they've got this really cool Sankey diagram of saying, well, this is all the kind of power that goes into running machines, running the overhead.

This is how it gets proportioned across all the different services. And this is how these end up being allocated to both our internal use, but also cloud customers and stuff like that. It's a really, fun read. And I'm probably going to spend like, I think, an afternoon or maybe the weekend making some more notes on this.

'cause there is a bunch of stuff which is beyond my can, like some of the equations are. I, don't have the, I don't have the ability to kind of make sense of those. I am looking forward to reading this nonetheless, because it's really nice to see something like this, not least because by putting this into the public domain, it's now raised the bar for some of the other providers to be more transparent about this.

Because if you're looking at, say, Amazon, you're looking at Amazon's calculator, you don't have scope 3 emissions, so that could be up to 99 percent of your emissions not accounted for in the numbers. So if they look suspiciously good on the Amazon dashboard, maybe they are suspiciously good. But also you look at the resolution.

This is something where they providing information at both the location and a product line value. So let's say I'm using Cloud Run or one particular kind of storage. I can see it at that kind of resolution. And that's that kind of location. In some other providers, you might see Europe and then compute.

So, there is nowhere near that kind of resolution. So, people talking about this is how we do it. This is how it's possible. This is what you should be expecting from other providers. I think it's really, good. And they also do mention the fact that they're using high time resolution. So, they say, "We're using data from electricity maps to help us work out these hourly curves, so that we know at what times of day, what the kind of carbon intensity for the power might be, so that we know that we've got this much kind of green compute that we can plausibly use," and in a defensible and transparent way, say, "yes, this really is running on renewable energy, according to the way that we talk about this."

And like, they do refer to like, they, you don't need to agree with the approach that they use in order to at least understand where they're coming from, because there's plus points and minus points with using the approach here versus having something totally location based like we've spoke about before.

So, yeah, that's kind of my initial thoughts when I see this, actually.

Asim Hussain: We need to get this to the point where it's kind of easily absorbable and understandable by folks in such a way that they can actually, because you know, otherwise it's just, oh, right. There's a great paper we'll use, you know, but I think you need to understand the nuance of a lot of this stuff.

I don't

Chris Adams: Well, there's two things, but what I think, so... you know, there's a, the real time cloud working group that Adrian Corkcroft is

Asim Hussain: Oh yeah. Yeah.

Chris Adams: He's been really pushing on a bunch of this stuff. This feels like one of the abs, absolutely worth sharing to that group because they've been doing a really good job of actually collating this data so it can be used.

And like, a scene like that was the thing that kind of fed into the impact framework stuff, right? So there is a path for this. And like, There's a job to decode some of this and make it easier for lay people because, yeah, like, Asim, we've been talking about this for literally five, six, five years to get to, for us to understand why it was exciting.

But yeah, you do need a job to actually make this easier for people new to the field because there's lots of developers who are kind of coming into this kind of sustainable software field.

Asim Hussain: you know, we should also have and this, we're now talking about GSF work. I know I've actually got to drop like very soon, but this is interesting because as I just asked you that question, I think an answer came to my head as well, which is like standardization. So, you know, as we like to, even as a real time cloud project is kind of evolving, like one of the things it's trying to figure out and work through is like, like you mentioned CFE and your definition of CFE.

And I can tell you right now, I've heard different definitions of CFE from other organizations, which don't. Count the, it to be, it doesn't have to be the grid. It could be anywhere. So I think some of this stuff, it might be interesting to have conversation with Google, like other ways to standardize some of the terminology, the methodology, the equations to this, as soon as you can create a standard, maybe something we can push into ISO or something like that. That kind of also in a way also forces the, not only simplifies everything for everybody, cause they're like, "well I don't really understand what the standard is, but I can see that it's got wide adoption and it's a standard and competitors have got together and agreed on this standard." So I don't really, you know, and there seems to be a wide body of people who support it. I don't need to look at this. This equation is so thick. I'm staring at this equ

Woo!

Chris Adams: it's quite a man,

Asim Hussain: It's a quite, a yeah, it's quite a lot. Selecting it has like 43 components in the selection.

But...

Chris Adams: the thing that we can maybe talk about is that there are standards. We don't need to be doing all this work ourselves. Like energy TAG is one standard that is essentially written into European law and American laws around hydrogen now, like hydrogen production. So there's things that, you know, we wouldn't be starting from zero.

We could be using some of that stuff, but you're right.

Asim Hussain: We how we push

Chris Adams: Yeah. I need to also. Thank you. Trying to rush us through for the last few bits, because there's a few things inside this that, as hosts, I need to be doing, and I sadly can't talk about the marginal carbon intensity of baked bread, because we had a really lovely follow from Dr Daniel Schien, who responded about the low carbon bread and high carbon bread thing. So maybe we'll, actually, we should commit right now to do an article about the, about how green the energy is, and how you talk about that, because this is what we just spoke about. Right now, Dr schien raised a number of really good points and linked it and shared some really helpful resources with us.

Okay.

Asim Hussain: we should get a proper conversation together with, if we can, like with maybe EM and some

Chris Adams: Yeah, we have some people inside the organization who've been doing that. Alright, let's look at events. So, stuff that's coming up. HotCarbon is a workshop on sustainable computer systems. This is happening on July the 9th. It's free to attend virtually. You can turn up in person if you're in California.

It's really, good. And I, there's, they have videos online and really fascinating papers. It's really worth reading. It's like absolute cutting edge stuff. There's also a, the IEEE. They have a cloud conference on the 7th through to the 13th. This is in Shenzhen, China. And for the first time I've seen, there appears to be something like a sustainable AI track, or sustainable computing. You are? Oh,

Asim Hussain: to be there. Yeah. I'm going to be there. Yeah. Yeah. I'm going to be there. I was invited by, well, the, anyway. So yeah, I'm going to be, I'm going to be, I'm going to be over there. I'm going to talk about sustainable AI in the cloud. There's going to be a whole track, several panels, discussion topics.

And

Chris Adams: Oh, wow! Cool!

Asim Hussain: You know, I don't think we particularly speak too much to, I'm a big believer in that this is a global challenge and a global issue. And yeah, most of our conversations happen in the Western world. So one of the things I'm personally trying to do is to try and

Chris Adams: Bring the other 1,5 1 point something billion people into that. Okay, great. Okay, so other two things we had. There is a, so outside of programming, this was shared with us. The masterclass on becoming a sustainable UX designer. This is one thing that's been led, I believe, by Thorsten. Oh, Thorsten, I'm afraid I forgot your name.

Thorsten Jonas. He's been helping organizing Sustainable UX as a community, which has the unfortunate short name of SUX, S U X, but it's, this is a virtual masterclass you can join. We'll share a link to that inside the show notes that's taking place, and he has a number of these coming up. And there's also Asim, I think this is yours, right?

The Software Measurement Landscape Workshop on the 9th of July? That's something that you've got, you're looking at?

Asim Hussain: That's not, well, no, not, it's yeah, it's not something I'm particularly involved with myself, but the green, the, we have a meetup group in Brighton in the UK, organized by an organization called Root & Branch, which do a lot of green software, the kind of green software startup, and they're doing a workshop on software measurement.

Chris Adams: Folks, ah, so Cardamon were the people behind, sorry, Root & Branch were behind the Rust based software tool called Cardamon? I think Cardamon, it's monitor for some of this carbon related things. Okay, that makes sense now, putting two and two together. Okay. And we have one last wrap up before I need to go, actually.

So, this is the, this week in Green Tech, where it's basically you and me, and occasional guests talking about the news. We have a, there's a new podcast, or a new podcast related to the Green Software stuff called CXO Bytes, and this is, I believe, Sanjay Poddar, the chair of the Green Software Foundation.

He'll be talking a little bit about some of this and speaking at the, I guess, CIO level, something like that. That's what we have. So, there's a first episode coming out in July, for this and, yeah, I figure we should tell people about that because it's something that's coming up too. Alright.

Asim Hussain: That will be, that's a separate, just everybody knows that's a separate podcast, so you'll have to find it and put it in the show, no late. We have to find it and subscribe to it separately. And as Chris mentions, like Sanjay, I'll be speaking more to the c-suite level of an organization and like one of his personal beliefs, and I do subscribe to this as well, if you want change in an organization, it needs to come from both directions or it will just stall in the middle. So he's very keen

Chris Adams: Getting by on it at the management level, at the very top, yeah? The big cheeses,

Asim Hussain: do is big cheeses and we do the witherbread whatever. That's

Chris Adams: Or the mushrooms, if you prefer, the

Asim Hussain: right. There you go. Wither, wither, yeah.

Chris Adams: breaking down barriers to adoption, like you break down dying logs, right? Okay. But Asim, really, enjoyed this, mate, I'd really love to see you again, and get well soon. I hope the Nurofen and coffee thing doesn't have to be a daily thing, and that you get better over the weekend, alright?

Take care of yourself, mate.

Asim Hussain: Wonderful. You too.

Chris Adams: Okay, ta ra!

Asim Hussain: Catch you there.

Chris Adams: Hey everyone, thanks for listening! Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode.

View Details

On this episode of TWiGS, host Anne Currie is joined by Navveen Balani of Accenture and fellow GSF member. This conversation navigates the landscapes of, and intersections between GreenOps, DevOps, and FinOps, as well as the vital role of Infrastructure as Code in marrying financial and ecological efficiencies in cloud operations. Lastly, they tackle the intersection of cybersecurity and AI development, emphasizing the need for green software principles to fortify AI systems while minimizing energy use.

Learn more about our people:* Anne Currie: LinkedIn | GitHub | Website * Navveen Balani: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Green coding - CloudBolt: Cloud efficiency... beyond dollars, pounds & pennies [03:17] * Why you should switch to green coding for a net-zero future [16:08] * The role of cybersecurity in AI system development [31:28] * Mexico elects Claudia Sheinbaum as its first female president [40:00]

Resources:* Cloud Native Computing Foundation [14:36]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Navveen Balani: Definitely, I would say there is some synergy between security and green software and certain, I would say, features of green software principles can also be applied to security domain, right, to make it more energy-efficient.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Anne Currie: Welcome to another edition of the Week in Green Software, where we bring you the latest news and updates from the world of sustainable software development. Today, I'm your host, Anne Currie. So you're not quite hearing the usual dulcet tones of Chris Adams. You will have to do with me instead. But as usual, we'll be talking about the world of green software and what's, what's going on at the moment.

And today we're going to talk a little bit about how being green matches with FinOps, which I think is very true. And I think that's a really important part of the story. So we'll be talking a little bit about that. We'll also be talking a little bit about code and code efficiency, which I'm much more...

You have to be very careful about code efficiency. So that's, that's the part that we need to be really careful about. What's the context there when we talk about code efficiency. And finally, we'll talk about the intersection of cybersecurity and AI developments, and we'll be talking a little bit about GreenOps.

And there is a new Green Software Foundation project, GreenOps project, which is aimed to look about how we can embrace AI and use AI without totally throwing all our green principles out of the window. And I think that is absolutely doable, but we need to think about it. We need to go in, in a very knowing way.

So as I said, I am your host today, Anne Currie. But first I'm going to introduce our guest, Navveen. Navveen, do you want to, do you want to introduce yourself?

Navveen Balani: Thank you Anne. Hi everyone. I'm Navveen Balani. I'm the Managing Director and Chief Technologist for the Techno and Sustainability Innovation Group at Accenture, working at the intersection of technology and sustainability. I'm also the co chair of the Standards Working Group and the Impact Engine Framework at the Green Software Foundation.

I'm a Google Cloud Certified Fellow, a LinkedIn Top Voice, and author of several reading books. Very glad to be part of this podcast.

Anne Currie: Thank you very much, Navveen. It's very good to have you. So just a bit of context for me. My name is Anne Currie. I am one of the co-chairs of the community group of the Green Software Foundation. And I am also one of the authors of the new O'Reilly book, Building Green Software. So that's, fills you in a little bit on my background.

So before we dive in to the articles this week that we're going to be talking about, it's just a reminder that everything we talk about will be linked in the show notes at the bottom of the episode. So you can, you can read the articles that we're talking about. You don't just have to rely on us telling you what was in the article.

So, well, let's, let's move first to the first article from today, which was in Computer Weekly. And it was called Green Coding. It was, it was a, basically a puff piece by a company called CloudBolt who do a look at code efficiency, cloud frequency. So taking it beyond FinOps, beyond dollars, pounds, and pennies.

So actually, but it was a very good article, I thought. I was very pleased to see it in Computer Weekly. So it was fundamentally, it was about how GreenOps and FinOps are very aligned. They're very combined. And, and I can, I'm in complete agreement on that. It's a good article. It doesn't say, tell you anything that you probably, that you won't know alreby knowingwing that FinOps and GreenOps are quite aligned and they're all aligned through the fact that in the end, being green, a lot of being green, not all of being green, but a lot of being green is about cutting down on how many machines you, and how much electricity you are using to run your systems, which, which generally speaking cuts down on the cost.

So cost is somewhat of a proxy measure. It's not a perfect proxy measure, but it's somewhat of a proxy measure. So the question that Chris Skipper, our excellent editor has left me and Navveen to discuss is about considering the role of infrastructure as code in enhancing cloud efficiency. How can developers ensure that their infrastructure as code implementations are aligned with sustainability practices to reduce both costs and environmental impact?

So Navveen. What are your thoughts on that subject?

There's,

Navveen Balani: I think that's a great question. Yeah, agreed. Developers need to embed sustainability as part of the infrastructure as co implementation. And the frameworks that I suggest developers apply is based on our Software Carbon Intensity specification from our Green Software Foundation which also recently received the ISO standard recognition.

So, for those who does not know what SCI is, SCI is a specification to measure the carbon emission of any software application and it promotes three key levers. Writing energy-efficient code, using less hardware for same amount of work, and making applications carbon-aware. And if you apply this strategy to infrastructure and the code, first you start with writing energy-efficient code.

So developers can focus on optimizing resource utilization by right sizing resources and implementing auto scaling. This means allocating only what's necessary for each workload, and also adjusting dynamically based on the demand. Second strategy is around using less hardware for same amount of work.

This basically involves automating resource management like automating the shutdown of non-essential resources during off hours and starting them during peak times. Even conserve energy and cut cost. Also, tagging and monitoring resources usage helps identifying optimization opportunities and eliminates waste.

You can also go with serverless architectures in your ISE code, particularly, it's quite effective as they scale with demand and eliminate, let's say, any provisional requirements. And finally, the third strategy is how do you make applications more carbon-aware. And that's where, as part of your infrastructure code, you can say that I want to deploy a particular workload in a clean free region so you can basically take, apply strategies like region shifting and time shifting and selecting cloud regions which are running on renewables and also maybe deploying workloads or scheduling jobs when the carbon intensity is low.

So all of these strategies can be definitely applied and designed as part of your infrastructure code.

Anne Currie: That's a, that's a very thorough answer and there's loads to unpick in there. Lots of different things. And some things I think at the moment are very aligned with FinOps and cutting your costs. And some things are not aligned yet, but are almost certainly going to become aligned in the future. So for example, you talked about operational efficiency and automation, which is interesting.

Operational efficiency, if you use for your machines. And if you use less electricity, your bill goes down. So that's all good. So in that respect, your FinOps and GreenOps are really well aligned. You know, fewer machines, less stuff, less carbon goes into the atmosphere and it's all fantastically good. And in that respect, I would say that That, that FinOps, that, that, that, you know, your, your hosting bill is a really good proxy metric for your carbon emission.

But of course it's, it's, it's almost stupid, it's so obvious to say it, but it can't just use your cloud bill totally blindly as a, as a guide. Just, you know, what I, when I used to do start, startups in my youth, quite often Azure or, AWS would give you loads of free credits. And then of course, but that doesn't mean that it's carbon free.

So, so there are times when, you know, you just, but you just need to use your head, don't you? Sometimes, obviously, you've been given a discount, but it's not green. It's just a discount.

Navveen Balani: Yeah, yeah, I think that that's, that's a good point. Because if you look at cloud, right? Cloud has infinite resources, right? So, it doesn't mean that, so you have to use it responsibly, right? So, you can bake in energy efficiency and sustainability, right? So, definitely, you have to look at how can you lower the carbon emissions.

And now, and there are also dashboards available from cloud vendors, right? Which at least gives you, some approximation, right? How, what, what is your carbon footprint of your application?

Anne Currie: Yeah, yeah, yeah. I mean, yes, they do provide really good tools and, and, and it's, it's a cut cost off really is the best possible metric you could potentially use, but it's where you've got the tools, it's where you've got the data. So, you know, it's, it's quite good from that perspective. Sometimes you just have to take what's good enough.

And, but so something else you mentioned is automation and obviously the, the really good operations is all automated these days. It's auto scaling and it's using the you know, not just in the cloud, but on prem as well, but actually I, in the. You can just do a lot of stuff manually, you don't have to leap straight, if you, if automation is too scary and you know, it's too much of a leap, just going through and turning off machines at the weekends, even manually, identifying machines that are over, that are over provisioned can actually, bizarrely, I think, I suspect in, well, and in fact, I've seen It might be the biggest carbon reduction you ever do, it's the simplest thing and the least techie thing.

So what do you think about, even for automation?

Navveen Balani: Yeah, totally agree. I would say even just turning off machines. Yeah. I mean, that's just manually, right? Would definitely save also the cost also, as well as the carbon emission also, right? Man, especially if you've turned on GPUs, that would affect. So, yeah, But actually, I think, also, I think if you look at the infrastructure, right, it's, it's, if you, if you break down the infrastructure in two parts, right, production and non-production environment, you can definitely have a lot of savings on non-production environment, right, because it doesn't need to be on always.

Production definitely needs to be on 24 by 7, but you are definitely have a lot of improvements that you can done on your non-production environment, dev environments, people, right, and I've seen customers having more non-production environments, right, than production ones.

Anne Currie: Indeed. And it's so ungreen. It's there's, there was another interesting thing that you talked about in your when you were talking about the SCI, which is carbon-awareness, which of course we know is the most, it's actually the most, it That's the code efficiency and operational efficiency are all good for kind of short term mitigating the harms, but in, but to actually take full advantage of that, you know, the soaring production of cheap energy for renewables, we need to demand shift to when the sun is shining or the wind's blowing.

But the interesting thing about that is that although that's by far the most interesting thing in being green, I would say, it's the bit that at the moment doesn't really save you any money because most countries don't yet have dynamic pricing. So dynamic pricing, so, so what's your thoughts? What are your thoughts on dynamic pricing and when it's coming?

So dynamic pricing is basically when the price of electricity changes through the day, depending on how expensive it was to produce, which usually means, you know, at times when the sun's shining and the wind's blowing, the power is cheaper than others. And that's, that's now very common in certain countries like Spain, but very uncommon in other countries.

Navveen Balani: I think definitely that's a good concept that will promote more sustainability. Typically, if you look at cloud providers, like let's be, to give you an example of Google cloud, it at least gives you now, if you're deploying something on a region, it tells you that it's, it's a low carbon region and hopefully in future you will have the dynamic parsing also, right? It will also give you the time when you should run the workloads. And there are a lot of workloads we doesn't need to run 24 by 7, like batch jobs. We get a lot of emails, right? Of all those millions of emails, right? You'll be sending, right? For promotions. All those can be run on time where, where there is least intensity.

And definitely if you have, if you have a cost, if the cloud provider gives you a cost that this is a good time window, and this is less costly and then all, all, all the activity which doesn't are not critical enough can definitely take care of the dynamic pricing. So I assume in future, I mean, we can see the trend, right?

Maybe where you have, I mean, it's all about data. If you have the data from the grids available to the providers in future, then we can definitely definitely tap on it.

Anne Currie: Yeah. Yeah. I agree. It's, it's a bit of a shame. It's, it's where there's the hole in the, in the alignment of green ops and fin ops at the moment. That's, that is incredibly green to demand shift, but you don't necessarily get money off for doing that. You know, moving to that green region is incredibly green.

But it doesn't necessarily save you money, but it will do once dynamic pricing comes in.

Navveen Balani: I also, I think if I also feel if regulations also are there, right, with regulations around carbon emissions reporting. Especially, I think, the EUA Act just talked about reporting the carbon emission, but it's a dog bone mitigation. But at some point of time, I would say, when you have a reporting mechanism also, and everybody have to comply for it, I see a lot of these trends coming, right, a new innovative way, right, to lower the carbon emission, right?

So I think regulations at some point of time will also enable, right, a lot of these, I say, innovations, right, to come up.

Anne Currie: Yeah, I agree. Oh, I meant something I meant to mention that, that's aligned with what you were saying earlier about automation. There's the CNCF, the Cloud Native Computing Foundation. So another of our, of the Linux foundations out there. They describe, and it's, GreenOps equals Fin, GreenOps equals FinOps plus GitOps.

So basically they're saying GreenOps is automated FinOps, which is an interesting one because it feels to me like they're really saying there that GreenOps is good FinOps. Uh, and oddly enough, FinOps often say, well, FinOps is just good ops. GreenOps is just good ops. It's, it's which is interesting, which I think that people often don't really appreciate. No, sorry, I'm taking the final word there and I need to, I will leave the final word to you, Navveen, on FinOps and GreenOps.

Navveen Balani: I'd like to end with what you said, right? So it's, we started with DevOps where you decide to automate something, then you, then the FinOps came, right? So we, because cloud resources were getting expensive, right? And now we have GreenOps, right? So all, we have to look at it in holistically, right? Across DevOps, FinOps, GreenOps, right?

And ensure you take care of both the cost and carbon, right? And keep it under control.

Anne Currie: Yes, totally agree. Totally agree. Right. So we're going to move on to the next. So that's the first article we're talking about there, I would say is extremely uncontroversial. Operational efficiency is like a total win all around. The next article, which is about why you should switch to green coding for a net zero feature, which is a LinkedIn article from the CEO of CSM Technologies, I think is vastly more controversial. Not because it's wrong that you should write a more code efficient, more efficient code. But because I think that there's a lot of context around it. So, so he's written a lovely article, links, as I say, links in the show notes, saying we should all be, be coding more efficiently, which is, which is nice.

But, and it ends with the, with the line, we should change, change, save the world one line of code at a time, which I find massively controversial because I think that when it comes to code efficiency, a lot of business, it's just not the right thing for a lot of businesses to do. It's too expensive. What they should be doing is putting pressure on suppliers to write their code efficient, you know, write the scaled code efficiency.

I think that it can really waste time going down, people going down that rabbit hole and their, their bosses were very right to say, "don't, I'm not going to do it" because it would put you out of business if you rewrote all your systems in Rust or C. So I think that is, it's, it's, it's an article that's true, but only true in certain contexts and not in others.

So Navveen, what's your, what's your thinking on it?

Navveen Balani: So I would say we need to look at this holistically, particularly around green software, focusing on, let's say... I would say three dimensions we have to take. First is having developer training and implementation of green software. Second, we need management buy-in. And third, I would say, it's the culture shift that needs to happen.

And if you look at green software, right, when we when we started, when you all started with the foundation, three years back, green software was a very relatively new area. So we need to provide training and certification in this area so that developers are aware of, right, how they embed sustainability in their day to day work.

Apart from, I would say, the training, a developer needs to have accessible tools, right. Now we have the SCI specification, the Impact Framework, Carbon-Aware SDK, right, which, and there are a lot of other open source tools also available now, which can make it more actionable and developers can actually embed them as part of their DevOps process.

And once the measurement is done apart from code, right, it's also the optimization piece we talked about, right in the infrastructure as code earlier also, right, how you take it all together, right, and try to optimize not just the code, right, but also the resources which are running the hardware, the resources which are powering those applications.

And as I would say green software practices gain traction, I would say securing management buy-in also is essential, right, for widespread production. For instance, highlighting the business benefits is crucial. For instance, implementing green coding, right, can lead to also significant cost savings by, let's say, reducing energy consumption and optimizing utilization.

And as you mentioned, right, it's not just Our footprint, but the scope, the footprint of our suppliers to ensure they also follow the same standard methodology. And that's where I think it comes to the culture change, right? That we all need to go through, particularly for, for green software. And we need to look at how we can embed green software, right?

Going forward in all our work, right? Similar to, let's say, similar, we do it for security, right? So when we, when we had security at 10 years back, right? Now we have security by default, right? We don't talk about that application needs to be secure. We assume application is secure by default. Similarly, if we embed green software, not just code, but across all, all the layers, then we can ensure maybe over the next four, five years where all applications, the new applications that we build, right?

Have a green software principles baked in. So I would say, I mean, it's basically a holistic approach that would be required, right, to, right, from enabling the development community, the tech community where the foundation also, like, for foundation, like, Green Software Foundation plays a critical role.

The management needs to buy in, and also the culture change that needs to happen, right? And the culture change also needs to happen, I would say, at the universities and schools, right, where they can start educating green software early on, right? Similar to the way we have learned object oriented programming, right?

That's by default. We have learned over the, I mean, over the last I would say decade, few decades, right? If we have green software, same as object oriented programming concept, then I think whatever application we build in future, right, we'll have green software baked in.

Anne Currie: Yeah, I, I may agree up to a point. I agree with you, but I think we, I, I'm a big believer in separating out two types of developers. Obviously there are loads of different types of developers in the world, but so, but two types of backend developers, so front end developers, this is almost a separate thing.

But backend developers, you've got people who just working in an enterprise and the code that they're producing is not going to ever be deployed. You know, it's, it's the code that they are writing is never going to be run by billions of people in their own data centers. And then you've got people who are writing platforms and the whole purpose of the platform is to try and get some billions of people to, or at least millions of people to write this code, to run this code.

And those people, they absolutely need to write efficient code. When I think everybody needs to, should be, could, should get used to getting out their performance profiler and just making sure there are no egregious performance problems with their code. Because performance problems are your code's slower and you're burning a load of carbon and it's total waste.

So all again, very aligned with the business. You want your systems to run fast. Your customers want your systems to run fast. So, so having a decently performance system is good. But beyond that, you probably don't want to be writing code yourself, which is massively efficient because that takes a long time, but you do want the platforms you're running on to have done, to have made that investment.

So it's, it's kind of like, there's a lot of context here, isn't it? Are you writing code for mass use or are you writing code that is not really for mass use, which is, which is interesting. I think that's a subtlety that we, like, for example, lovely article though this was, did not point out that difference.

Navveen Balani: That's a good point. So, yeah, especially applications, right? Package applications which will be used, let's say, by millions of developers worldwide or users worldwide definitely needs to make that in right to ensure that for instance simply like all the large language models a good example right all all generative applications will be used by millions of applications millions of developers so how can you make the AI more efficient right both on the user side who is creating let's say the prompts right to Create in an efficient way so that the round trip is reduced and secondly on the backend side, right?

How do you have a low cost efficient energy-efficient model? That's why you also seeing a lot of LLM models are now Talking about the small language models more energy-efficient more compact, right? There is a trend where I would say right where Organizations are now looking at energy efficiency also, right, as part of the applications or whatever work they have been doing.

Anne Currie: Yeah. And of course that's all driven by cost. It's taking us back to our previous thing about cost and cost and green are very aligned. And the good thing about, well, the bad thing about AI is very costly. The good thing is it's driving quite a lot of efficiency improvements. So, I mean, I talk about this every time I'm on here, that, that Python has got a lot more efficient because, because of AI, that they've rewritten all of the code, core, core libraries in Rust. And of course that's, that's a perfect example of they are the kind of people you want to be writing super efficient code. They can save the world one line of code at a time because so many people run Python. But you want to be getting that out of your platform and not having to do it yourself as a, as a Python user.

You don't want to have to change to Rust yourself. You want to be able to get the value of Rust whilst still using Python. But yes, yeah. So, so that is all very interesting stuff, but yeah, very nuanced. It's all at every degree of it. It's what my, to my mind is what makes green interesting, is it's not simple.

It's not trivial. You have to step back and you go, "where am I? What am I doing? You know, what's, where, what's, how do I fit into this? Where does mine, where is my effort best applied?" I mean, you're obviously part of the SCI, which covers all of the things, you know, operational efficiency and code efficiency and demand shifting and shaping.

What's your interest? What do you like the most out of those things?

Navveen Balani: I would say from a, I think from a developer standpoint, right, depending on your roles, right, so SCI, I would say is more inclusive in terms of, depending on roles, right, whether you are a developer, architect, data scientist, right. All are various parts to play, right, to reduce the carbon emission and make applications more energy-efficient.

So, depending on your role, for instance, if you are building, or you are a developer writing code, right, then you can really focus on energy efficiency. And it's not, as you mentioned, right, it's not just moving towards a C or C++ language, right, which is more efficient, but it's, so you have to basically look in the context of the work you are doing and trying to optimize it, right.

So you have to do that trade off as a developer and how, what libraries access to make it more efficient. Second, I would say the whole hardware optimization, I think in terms of where all the DevOps, cloud, cloud architects comes in. How there are various custom chipset from various vendors, right? How can you best utilize from an infrastructure point of view?

And third, I would say is more strategic in nature, right, in terms of how do you bake in the whole carbon away computing concept, because that's new. You need to have data providers, you need to tie up with various licenses which are actually costlier, right, if you look at getting the real time data, right, from various providers.

So how do you bake that in in the application to more of a strategy kind of work and thinking? So in that way, I would say it's, I mean, depending on your role and context, right? I mean, whether from developers to architect for data scientists, right? Each can find definitely a value for, in SCI and then try to reduce their scope of work.

Anne Currie: Yeah. It's so, it's interesting. When I first heard about the SCI, I was a bit, I was a bit dubious about its value, but I have completely changed my mind on that as time goes, especially because I teach, I teach people who are green software and, and, and. One of the things that often comes up is people wanting to be able to do like for like measurements.

And I think that I originally thought the SCI was about a standard that you could compare between applications. And that was where the value would lie. And I was a bit dubious that we could realistically do it. And, and now I've realized that, that I like that the SCI has stayed fairly woolly and loose.

It's more conceptual than it is a specific implementation. And I like that because really it means that companies could choose their SCI score, they can choose how to define their SCI score for their applications and choose what's appropriate. What it's going to, what it's going to, what the denominator is going to be.

So it's per user or per transaction or per, so everything, something that's specific to them, and then it's essentially for like, for like, so you can say, well, last year it was this, and the next year is this, and you can average over time so that you're, you, you know, saying you don't say, well, I'm comparing a sunny day with a non sunny day, or, you know, all those kinds of things.

What I like about the SCI is it's, is it's very kind of conceptual high level nature that forces people to think, "well, actually, how do these things apply to my system?" You've got to use your head. You can't just, you know, you can't just follow it. You can't follow it blindly because it doesn't make any sense if you do that.

You have to say, how does this apply? Forces you to think, which I like.

Navveen Balani: Yeah, I think that's a good concept. Particularly if you look at SCI, right? It's for an application, so you have better control rather than giving you the carbon emission of all the applications. Right. Which typically is given by various cloud providers given an application, then you have a better control, as you mentioned, right?

You can define your own boundary and architecture and calculate the SCS core, right? And the intent is to. Basically, as you deploy new versions, right, the intent is the SCI, you should look at how you can reduce the SCI score, right? We can't achieve zero, but definitely across releases, right? How can you make it have a lower SCI score?

And the point you made about the comparison also, right? So you're comparing your application versus your previous application that you have deployed. It's not about creating two applications from two different organizations, right? We're not there yet. It's about currently using this methodology, right, for your own application and trying ways to reduce it.

Anne Currie: Yeah, which makes all the sense to me. So many years ago in my, when I was more youthful, I used to work in retail and in retail, like for like comparisons are very important. You want to be able to say, well, this year we've made more money than last year, but you can't just say this year we made more money than last year.

You can, but it's not all that useful. What they actually want to do is say, it's per thing. So in retail it's often the kind of per square foot of retail space, balanced for kind of like, well, how expensive was that retail space? You know, so you're not comparing it and say, well, this year we made more money on the same on, on the same amount of floor space, but, you know, it was in London versus it was in the middle of, you know, of the desert. It's, it's kind of like you, you've got to, you've gotta come up with your own, like, for like measure so that you can say, well, is our business improving or is our business getting worse? And the SCI is exactly the same. It's, it's the concept of like, for, like, it's for you to check Ron North's for you to check against other people.

So yeah, it's yeah, I, I, I, I've been completely won over to the SCI. I was highly dubious to start with. Right.

Navveen Balani: Good example. Yeah, that's a very good example of a retail. I'll also use that.

Anne Currie: Right. So now we'll go to the final, the final thing we're going to talk about today, which is, we just touched it from a slightly, again, a slightly more holistic perspective. So this was an article in a Silicon Republic and it was a Q&A with the chief security officer of a, an AI company. It was talking about.

Basically, her premise, and I totally agree with it, is that security, cyber security is very aligned with being green. It wasn't, it's not, it's a bit thin as an article, it doesn't give you an awful lot of information, but I think basically, yeah, that there's the, the idea that, that I think we should be discussing is, is security and, and green aligned?

And you, you, Navveen, you've talked a little bit about that, about in terms building security in is, is like, it is, we've, we've learned to do that and we should learn to do green things, build green things in, in, in the same way. But separately to that, are there security benefits to being green? What do you think?

Navveen Balani: I would say, yeah, definitely there's synergies between security and green principles. So I like to again give that example of SCI, right, if you want to break down the methodology into three parts, right, making applications more energy-efficient, right. So, if you look at the security algorithms, right, how can you use, how can you basically optimize the security algorithms to, let's say, use fewer computation resources.

Particularly, if you look at the security stack, right, they also have evolved from various encryption and cryptography software, right, and now I think you have various key ciphers available across different dimensions. So, they're already following this, I would say, backtest, right, of making encryption security, right, more performance and more easier to adapt. So in that case, I would say it's more aligned towards the algorithms that they're using are more efficient, right? As compared to what it might be, let's say five years, 10 years down the line for, for security protocols. And similarly, I would also say new strategies can also be applied for security scanning.

For instance, vulnerability scanning is one commonly used, right, to identify any threats, maybe in cloud or maybe in desktops and other systems, right, that can actually run, take the advantage of running it on a time, right, where the carbon intensity is low. So in that way, it can apply certain green software principles.

To run all those scans where the carbon intensity is low and also save on the carbon emissions. So, definitely I would say there is some synergy between security and green software. And certain, I would say, features of green software principles can also be applied to secure the domain, right, to make it more energy-efficient.

Yeah,

Anne Currie: And so, so something that actually I'm, I, well, you did mention a little bit earlier is, is security is the perfect example of where hardware, using the right hardware for the job massively cuts your emissions. So dedicate the right kind of chips that are designed for for encryption are just so much more efficient than using general purpose or CPUs for, for that, for that.

So, yeah, we wouldn't be able to do what we do these days if it wasn't for dedicated chips. Oh, and so, and oddly enough, this does also map to some of the stuff that we said at the beginning about manual ops and manual FinOps, that's, it's amazing how many systems are through machines that are kind of like, nobody's, everyone's kind of forgotten about them.

They're not keeping them patched. They don't really do anything useful anymore. Those are your backdoor. Those are the ways that people break in and they're just wasting electricity. So even in building green software one of my co-authors, she, she brought up the fact that, that it's interesting that security, well, that are very much an example of a waste of electricity.

They, they're, they're wasting. So, so something like a denial of service attack, the whole purpose is to burn your electricity in your systems and burn your system so that your systems don't have anything, any time to do the thing that they're designed to do. You know, the thing that has value for you, instead, it's just burning your systems up burning electricity, running up all your bills to do something which is bad for you.

So having a secure system that, and things like applying the latest patches so that you're less, less exposed to denial of service attacks is green because denial of service attacks are very ungreen, they are very dirty. Same, it's, it is quite interesting, isn't it, from that?

Navveen Balani: Yeah, that's why I think the provisioning the right hardware, virtual machines, especially, right, provide various cloud providers. Right. They all, they now provide a managed services, right, to detect various denial attacks. And I assume, right, the underlying hardware that they are using, which is, which should be used by millions of applications, right,

would be definitely more sustainable, more energy-efficient, right. And, and more scalable.

Anne Currie: Yeah. Yeah. Securities are really interesting in that, that's it. So FinOps is just really a, a, a pretty much, except with, for, you know, your free Azure credits or whatever, is pretty much a group, the direct proxy measurement for carbon emissions. And, and likely to become more so in the future when we get dynamic pricing.

But security is not a direct proxy measurement is just, it's just that there are a lot of, you know, best practice in ops is also best practice in secure ops is also best practice in green ops. You know, they're, they're, they're kind of like, you can't use the number of hacks you have, then the number of attacks you, you fall foul to as a proxy measure, you, well, maybe you could, I think that would be a bit complicated.

Proxy measures for carbon is how many times your data gets stolen, aligned rather than proxy. It's interesting. I mean, so we just, we've talked about those, those three things, but have you run across anything interesting at the moment that's, that you think that our listeners should, should hear about? And

Navveen Balani: So, yeah, I would say for the, on the Green Software Foundations, specifically, right, we are working on green AI and so we are trying to look at how we can extend SCI to take I mean, how we can do SCI measurements for large language models generative AI models. So this is something we are actively, I would say, working towards from the foundation perspective.

And if you look at from an SCI perspective, right, we want to have various extensions to SCI, for instance. How do you do SCI for web applications, backend applications? And make it more easy to measure, right, different parts of the code and make it easily available to developers so that developers can measure their, their part of the overall carbon footprint, right so we can make it more accessible.

So that's, that's one thing I think we had from a foundation perspective, looking at how we can make it SCMO extensible to various other use cases.

Anne Currie: That's, that's very interesting. That is the, yeah. 'cause obviously Ai, AI is the, is the workload of the, it's on everybody's lips at the moment. It is... and so I, I saw very interesting charts from all the, the Economist, I think the, the other week that, that said, you know, that's, that showed the enormous amounts of power that was currently being used on ai, but still less than the amounts of power being used on Bitcoin.

So it is just worth reminding. And of course, bitcoin is very aligned with our last conversation about security and what people wanting and people who are attacking you wanting to run up your energy bills, because quite often what they want to do is mine Bitcoin on your, on your machines that you're not properly watching.

So security sweeps are a pretty good way of identifying machines that are burning power totally unnecessarily. From political... I, I quite liked to keep my eyes not just on the Al news, but the really good news news last week from a political rather than a technical perspective was the world's just got its first climate science trained president in the new female president of Mexico is a, is a climate scientist by, by trade and training.

So, I, I, I would be very interested to see what affects that out on the country. Any other interesting political news that's good news, do you think?

Navveen Balani: No, I think I've yet to catch up on,

Anne Currie: Well, I'm quite nosy, so I keep my, I keep my eyes open on all things. I would say there's, there's loads, actually, there's, there's a lot of good news going on at the moment. Texas is now a massive solar producing state. It's, so, yeah, there, there is, it's, The world is changing in a positive way. I, I like to, to, to keep reminding everybody that we are not doomers at the Green Software Foundation.

We, we are doing this because we believe it will have an effect.

Navveen Balani: I totally, I would say, especially with the foundation, right? It's all our collective journey that we've gone through. I mean, we started three years back, we didn't have, we didn't have any specification tools, right? Three years down the line, we have the first specification tool. Software carbon intensity specification, which is now an ISO standard.

We have various tools now, carbon SDK, impact engine framework. And I, I know that 1230 projects already in the pipeline on the foundation, right, which will make the world, I would say, a better place, right. In terms of sustainability, right. For all the work that we do. So, yeah, it's basically a shared responsibility, right.

Climate change is basically a shared responsibility, right. And from our perspective, developers, all we can do is contribute, right, by using the three SCI principles, which I talked about, right? Which I again repeat is either write better energy-efficient code, use hardware wisely, and make applications carbon-aware.

Anne Currie: And of course, actually, not just write it, cause you might not be the one who's writing, it's more important that you use it. So as I'll, I'll constantly, cause Python is such a good, good example of the moment, at the moment, because of their big, big revising stuff. If you people who upgrade the latest versions of Python that are much more, more efficient will be saving a lot compared to people who don't upgrade.

And that's, those kinds of things are the kind of things that will immediately be unearthed by running the SCI like for like. I mean, a really big change might be on your like for like is that you upgraded to more recent versions of a particular library or a particular set of tools that you're using that are more, more efficient.

SCI isn't just about what code you write, it's about what code you use. And that is almost certainly going to be where you get the biggest, biggest value, the biggest return. Anyway, sorry, now I'm doing my, I'm trying to take the last word again, and I'm going to leave the last word to you, Navveen.

Navveen Balani: So yeah, very happy to be part of this podcast. Enjoyed this conversation talking about, I think, three different aspects. I would, I would say. And to all the viewers is, yeah, thank you for listening in and have a good day.

Anne Currie: Navveen, awesome. Thank you very much for coming on this podcast. And a final reminder that all the resources are in the show description below, and you can visit podcast.greensoftware.foundation to listen to more episodes of Environment Variables. And see you all soon at some point, if they ever let me back in again as a guest host.

Good bye.

Navveen Balani: Goodbye. Thank you, everyone.

Chris Adams: Hey everyone, thanks for listening! Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundationon. That's greensoftware.foundation in any browser. Thanks again and see you in the next episode.

View Details

TWiGS host Chris Adams is joined by Asim Hussain the executive director of the GSF to talk about the recent hackathon hosted by the GSF : Carbon Hack 24. Asim goes through some of his favourite projects that featured work with the Impact Framework including some surprising choices! They also cover some interesting news from the world of cloud service providers and the new CSDDD developments. Asim also talks about how mushrooms are out and bread is in!

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Tom Greenwood: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News & Topics:* GreenOps, FinOps, and the Sustainable Cloud | Forrester [6:03] * EU: New CSDDD compromise finally accepted by Member States | Linklaters [30:02] * Carbon Hack 24 Recap: Asim’s Favourites: [50:12] + Facebook Open Sourcing the code behind its Power and Water Efficiency Dashboards [51:40] + Grasp [52:22] + Amazon Packages for Delivery [56:08] + Kubernetes Focused Project [56:40] + GreenerMeet: Assessing Energy Usage & Carbon Emissions in Zoom Conferences [57:04]

Resources:* The Baking Forecast | ShouldIbake.com [2:57] * Hetzner [17:09] * DigitalOcean [17:32] * BackMarket [18:04] * Sesame Open Hardware [20:32] * DjangoCon [23:18] * Green Metrics Tool [23:57] * How does AI and ML Impact Climate Change? | Environment Variables Ep 4 [36:49] * Green Digital Coalition [44:15] * In-depth Q&A: How does climate change drive human migration? [54:32] * All the winners of Carbon Hack 24

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
Asim Hussain: And I'm just sitting there thinking, we are old. These are the kids of the future, you know, maybe gave me so much hope, like these are 16 year old kids, and they were doing some incredibly advanced green software measurement, reporting, zoom, understanding curtailment, understanding like how to measure this stuff.

And I was like, ooh, we've got a, we've got a good future ahead of us.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams. Hello, and welcome to Environment Variables, the podcast where we talk about sustainable software development. I'm your host, Chris Adams. This week, our format is This Week in Green Software, where rather than doing a deep dive into some of the specifics of green software, we're going to look at some of the news stories that have been making the rounds and provide a bit of commentary and analysis on this. And joining me today is my good friend Asim Hussain, the executive director of the Green Software Foundation. Asim, I'll hand over to you to introduce yourself a bit more than what I've just shared so far, if that's okay with you.

Asim Hussain: Yeah, of course. Yeah. Thanks. I really love these, having these podcast episodes with you and talking through this material. Asim Hussain, Executive Director of the Green Software Foundation and been, you know, lucky enough to be at the intersection of sustainability and software for quite a few years. So based in the UK and excited to be on the podcast again.

Chris Adams: Thank you, Asim. And when I last spoke to you on the podcast, the recurring thing is your history of growing all kinds of delicious mushrooms. How are the myco friends doing?

Asim Hussain: Not good, not good. I've lost, my green thumb or my blue thumb. Maybe if that's how you would, talk about it. But yeah, no, I've lost my, I've lost the thumb. I now bake bread is, the thing that I do, which is equally disappointing, to be honest with you. I just love doing stuff, which is like very, the people, you put a lot of effort in and then you get kind of like middling results is kind of my, seems to be my hobbies of, the day, hobbies du jour.

Yeah.

Chris Adams: Okay, so you've been culturing um, what's it, butter, sourdough and things like that?

Asim Hussain: Yeah, sourdough right now, yeah. I do have a sourdough starter that I, was gonna say keep refreshed, but I probably should say like, keep on the verge of starvation all the time. But yeah, no, it's actually quite fun. I make, I bake bread every weekend and I give it a go. Yeah.

Chris Adams: you for sharing that. Presumably, this is going to be carbon aware bread that you're using, that you're baking when the energy is green, because in the UK, you have the baking forecast. Are you familiar with the baking forecast?

Asim Hussain: I am not aware of the baking forecast.

Chris Adams: Ah, dude, this is so cool.

Asim Hussain: Now that you've said it, I can't believe I'm not using the baking forecast. Because it is, a lot of, that's the thing my wife questions me on. She's like, does the financials of this work out? And I'm like, I don't know, but there's healthier bread than the stuff you get in the supermarket.

Chris Adams: So for those who are curious, and I promise we will talk about green software, this is a kind of segue towards some of the ideas we might talk about later. In the UK, there is a website called the Baking Forecast, named after the shipping forecast, and the idea behind it is to look at the carbon intensity of the electricity that might be going into the oven when you're doing any kind of heating.

And this means that you can then decide to time your baking to be zero or very low carbon bread by making sure you bake when there's lots of renewable energies on the grid. Or, alternatively, if you are not paying attention, you can end up with very, high carbon bread by baking when there's lots of fossil fuels on the grid.

Now fortunately, sunnier, we've got some more solar and wind coming in, it's not like the depths of winter, so it's probably greener breaking today than it was in November or December. But yeah, this is one thing that we should, that I think is, only the UK has this right now. And we'll have to share a link in the show notes because it's a really, cool project.

Asim Hussain: That's cool. You could also end up with really high carbon bread if you leave it in the oven for too long.

Chris Adams: Oh yeah,

Asim Hussain: wait, wait. Oh my God. Where is it? Where is it? I don't know which one it is. You do it.

Chris Adams: I think I know what you're after.

Asim Hussain: Oh, there we go. Oh no.

Chris Adams: This is what you're after?

Asim Hussain: That was it.

Chris Adams: Yes, it, yeah, as, you, Asim has discovered the sound effects on the, on Riverside, the podcast platform we're using. So-

Asim Hussain: You told me about it.

Chris Adams: Yeah, I do apologize. So if we have, we might be like two children at the front of an aircraft playing with this, flip, flicking all the switches, but we'll try our best to not make listening to this too insufferable.

Okay, so we've, mentioned about the baking forecast as a way to talk about carbon aware use of electricity and things like that. Shall we look at some of the stories together, Asim?

Asim Hussain: Yeah, let's do it.

Chris Adams: Oh, if you're new to this podcast, my name is Chris Adams, or if I'm in trouble, Christopher Adams. I am the executive director of the Green Web Foundation, a small Dutch non profit focused on reaching a fossil free internet by 2030.

I'm also one of the chairs of the policy working group inside the Green Software Foundation. The other thing I'll share is that at the end of this show, we'll be showing a link with all the show notes, and it's usually written in Markdown, and we do accept pull requests, so if there's a thing that we've linked to that you think is incorrect, or if there's things you'd like to add, then it's open source and you can do that.

And I think that's the main thing I'll share. The stuff we talk about will be linked. And I guess we should probably find something to talk about then, shouldn't we?

Asim Hussain: Yeah. Something that's not bread related.

Chris Adams: Alright then, well in that case, shall we move on to, I want to make a joke about biochar, but let's just move on from, yeah, alright, so let's, focus on the first story, which is GreenOps, FinOps, and the Sustainable Cloud.

This is from, uh, I think it's actually originally from Forrester, a big analyst firm, who have now kind of woken up to this idea that If you're tracking cost, in many cases you might be tracking carbon. And this is the main thing they're talking about here. There's a few kind of key takeaways and key points inside this.

And this basically does talk about things like, say, you can reduce emissions through kind of looking at kind of existing cost bills, for example. There's different steps you can take. They talk a little bit about some of this stuff. And they also provide a very, high level idea that Right now, we do have inconsistency across the large cloud providers, so Google and Microsoft, they might report all of the emissions, or all of the emissions according to the kind of GHG protocol, which is like the gold standard of reporting, giving you scope 1, 2, and 3, where the majority of the emissions for what we do is probably in scope 3, and talking about how Amazon is doing this, and they've recently, we now know on the grapevine that they've started to rehire people.

But at present, if you look at the dashboards or the calculators of Amazon, you're only going to look at scope one and two, which on average means that you're missing a significant chunk of the picture. So that basically means if you dashboards, and you think, oh, my numbers are really low, that might not be the full story.

All right, Asim, I trust you had a chance to look over it. So are there any particular takeaways or hot takes you had on this one that you might share with us?

Asim Hussain: Well, I don't know if I had any particular hot takes is stuff I've heard before and kind of stuff I've heard mentioned kind of in quite a few times over the past few years. And what I was actually interested in is perhaps just having a more. I'd actually love to hear your thoughts and maybe we can like walk through some of the ideas and some of the question marks I have are just about the whole premise of this link to cost and carbon and like, there's a few things I think of when I think about that.

One of the things I think of is, well, isn't, the cost of things the reason why we're in this problem in the first place? You know, how can costs, how can money both be the cause of the problem and the solution to the problem at the same time? And then, like, you know, you know, yes, there is this argument that kind of reducing cost reduces carbon, there's this kind of correlation.

I've spoken about it extensively, in my past, but kind of I'm trying to refine my thinking in this space. We know that there's somewhat of a correlation there. But we also know there's things you can do which can dramatically reduce carbon, which don't affect your bottom, the cost at all in the slightest.

So what is the, how big of an opportunity is that and is therefore focusing on cost kind of distracting us from things that we can do, which can dramatically reduce our carbon that they've got nothing to do with the cost. And another thing just kind of pops up in my mind as well, which is I remember I was speaking to just the energy purchasing department at Microsoft years and years ago. And I actually asked them, can I quote, quote you on this.

Chris Adams: And this is because you worked at Microsoft.

Asim Hussain: I used to work at Microsoft. Yeah. Yeah. And a rule of thumb that they gave me was, which was the, this is pre AI, was that the cost of running a data center is only 10 percent energy. The actual dollar cost, 10 percent energy, 50 percent depreciation of assets.

So you bought some chips, and they're gonna be worth zero in five years, so they're depreciating of assets. And everything else was like, you know, people and everything else was number one. And so like, when you think about that, certain parts like that emits carbon into the atmosphere, all of those-

Chris Adams: The creation of, oh, each of these, right?

Asim Hussain: The energy emits carbon, but it's only 10%.

You know, the human beings running around emit carbon, the actual physical infrastructure like emit carbon when it's created. And then what happens in an organization is you normalize that into a dollar value, which you then charge for services that run off there. But does that dollar value, like represent, you know, accurately, you know, like the carbon emissions put it that way like there's probably a lot of nuance here yes. Reducing your cost reduces emissions, but maybe reducing costs In this way has unbelievably emissions reductions and reducing, you know, reducing $10 in another area, eh, probably doesn't have that much impact at all.

So I'm kind of a little concerned with how I don't really think the link is kind of that well understood and I'm worried a little bit that if we focus too much on cost reduction, we might be able to reduce costs in ways that have no impact on carbon emissions reductions. That's kind of like where I'm thinking about.

Chris Adams: Mm.

Asim Hussain: I was just wondering what your thoughts were, actually.

Chris Adams: So, I think there's two things. I'll share a question to that, but you said two things which I think are really interesting there. First of all, the cost of energy as, like, that's a part of what the data center might be, right? And you also said, like, depreciation of assets being one of the big costs.

And that, I'm assuming that basically means, like, I've got a server, it's going to last over, say, three or four years, and because of that I split the cost over four years, and that's how I, that's, you know, it's-

Asim Hussain: Yeah. Accounting wise that let me see exactly how they figure out accounting wise. Yeah.

Chris Adams: All right, so there are two things. Most of these discussions seem to be about energy usage, with the idea being that, I think you're right, there's totally mismatch between these two things, because we are, in many ways, we don't see any of this stuff, we don't have the visibility in a bunch of these things.

And one thing that we've, one thing that I guess we've seen a number of large companies start talking about now is saying, well, we are looking to extend the life of our servers, and we're doing this as a way, as a green measure, right? That sounds great, yeah? But if you extend the life of your servers, you've gone from 50 percent depreciation to maybe 30 percent or 40 percent depreciation, right?

I mean, from a financial point of view, that basically, I mean, Amazon did this. It put like billions onto their, on to their balance sheet because they now look way more profitable than they were before because they don't have to kind of write it off. So, yes, there are some things being shared for this but whether how that actually factors into some of the calculations people use.

I mean, I don't know. There was an announcement there. We haven't seen any changes whatsoever in any of the kind of cloud dashboards, so you would have expected that to make a difference if you did have, if we did see that, and both Amazon has done this, Google has done this, and Microsoft had done this, right?

So, I would argue that looking at calculators, there's a gap here between what we're seeing here and what we are being taught to optimize for. And there's also another question. Yeah.

Asim Hussain: Yeah, no, it, and there's also, I remember just as you were saying that, I remember this, and this is years, this is information is years old, but I was chatting to the, uh, the Xbox team at Microsoft and like one of the things, I mean, I still, no, I don't have an Xbox. I finally got rid of it. That initial estimation

Chris Adams: You sorely miss. Your love to Xbox, that is. Yeah.

Asim Hussain: Yeah, love.

Chris Adams: Oh no, you don't work for them now. You're okay. You can say anything.

Asim Hussain: I'm okay. I can, get rid of it, I think. I think. Yeah, you wouldn't get, you wouldn't get a free Xbox if you went to Microsoft, and I always thought they should give you one. But, it was, like, they assumed that it would only last, like, four, three or four years. I can't, I'm, don't quote, no one quote me on this.

But the actual lifespan of kind of these consoles turned out to be a lot longer. And people, I don't know how old Xbox is now, like, it must be like six, seven years. But it's still, like, pretty, you know, still pretty active. The decision was to kind of still keep, from an accounting perspective, still keep it kind of three, four years, even though the reality was it was being used for longer.

So those decisions are being made as well. But it's interesting that's part of the, yeah, I suppose that's part of the story we don't really, The point I'm coming from is this, is a $1 reduction in your costs, how do you link that to an actual carbon emission? Because coming back to my point of like the energy versus the embodied, like how much of the emissions is linked to the energy versus the embodied and therefore how much of your cost is linked to reducing the energy versus reducing the embodied?

Does that make sense? It's

Chris Adams: This comes to basically disclosure of cost structure, which is a bit of a kind of like jargony term but basically without having visibility into how this stuff is paid for because in many cases we have very proprietary services, it's really hard to basically, be sure, like, is this really happening?

And even when we talk about things like, say, cloud, moving to cloud compute, moving to, say, serverless, all these other tools, which are kind of higher up the stack, right? There is, it's not like the profit margins for cloud at the very bottom, like paying for compute per, on a per hour basis, will be different from things higher up.

And we don't have much in the way of visibility into any of that stuff. I mean, I, as I understand it. The higher up the stack you go, the more value you add. A bit like if you're buying refined, if you're buying oil, and then you're selling, say, refined kerosene or something like that, it's going to be a different price, right?

So you can think of, I think we have maybe some mental models we can apply for some of this. And this is actually possibly one way that you can say, well, if we have If we're running a bunch of companies, and we have a set amount of resources, and we cannot use more resources, like more inputs, there are ways to still continue to increase the amount of kind of value and profits being made by shifting people to kind of go higher up the stack to get them to purchase, maybe say, a serverless thing, or something like, something which allows you to kind of cram more stuff onto the same infrastructure.

But the problem is, In order for you to do that, you need to not build more infrastructure. And what we've just seen is the opposite of that happening right now. And I think this is what, I think you're somewhat right. It's easy to talk about cloud costs because it's, you've already got the numbers there and you don't have to, yeah.

Asim Hussain: It's like one of the most obviously disclosed, like, facts about your cloud usage is how much it's going to cost you.

Chris Adams: Yeah. And like, if you're in an organization, it's probably easier to start optimizing a number that you already have than to pay for someone to, or even pay for a solution for someone to do this stuff. Because I've invested like. We've, uh, okay, I promise we'll get back to the other stories a little bit later on, all right?

But inside the Green Web Foundation, we've been looking to, like, audit all of our own services recently, or just, like, work out our own kind of, look at our own annual emissions. And the thing we found is that, let's say we've, uh, the majority of our impact, because we're a quite small organization, comes from, not necessarily from the services we're paying for on an hourly basis, like, we use Hetzner, and we don't, Which we're spending maybe, I guess, maybe a thousand euros a year on Hetzner in total?

Asim Hussain: What's Hetzner?

Chris Adams: Hetzner is a German cloud computing service. So, about half of all of Mastodon run on Hetzner service because they're so cheap. So much cheaper, and in Europe at least. They've been one of the greener ones to use, because they build all their own software. And if you look at their prices, they're typically, like, you know how DigitalOcean will sometimes be cheaper than, say, the big cloud providers?

They are cheaper than DigitalOcean, once again. So as a result, we're a cash strapped non profit, we're going to go for the cheapest green, option we can find. And the cheapest green option that We can find that has cloud like APIs and is used and works quite well. So we've been using those ones, and as a result, cloud makes a small amount of our kind of digital estate.

What ends up being a larger thing is the infrastructure we use, like the laptops and the monitors we have inside our own houses, inside our own offices. But, even if we buy those from circular providers, so my laptop is from BackMarket, which is like a kind of second hand provider, and likewise, Hannah does the same thing with hers, and all this.

Hannah's my, she's my colleague who's been leading on this work here. We've done this, but under most of the ways there's no guidance on, okay, is it someone else's carbon? Do you know, has someone else banked it so therefore it's free for you because they've depreciated the carbon there? There isn't much in the way of guidance or real stuff that you can adopt.

Like, you can might, you might be able to sight a paper, but that's not the same as there being, say, guidance that you might use for your own reporting to say, this is why we've chosen these numbers here, for example. And like, this is what, these are some of the problems. There isn't this recognized way to account for circular versus buying new stuff, for example, and this does speak to this idea of, well, okay, how do you estimate this stuff and work out what is the most effective thing, which, you know, which levers should you be pulling if you want to reduce the emissions from software or digital services in general?

Asim Hussain: So that would be like an example of, well, yeah, cause I've even had these conversations before we're talking about like, what'd you do? I think with all these like hyperscalers, like once they actually reach end of life, they're not broken.

Chris Adams: Mm

Asim Hussain: the, equation that they're running is like, we've got per square foot of infrastructure, of real estate, what is the profitability? And at a certain point, it becomes more profitable to take out this old server, which is perfectly fine.

Chris Adams: Yeah, usable. Working.

Asim Hussain: But you can just put something else, which is more profitable per square foot for that given situation. So that, I mean, people think these things are breaking and then no, they're not, they're just perfectly fine and working.

They might be more inefficient. Then we've had like conversations in the past with, I've had people going, well, if I was to take that server. End of life server and build my own data center. Could I argue that is zero? Could I argue that it has zero embodied emissions? Is that like a reasonable statement to argue?

And, I don't know. I don't know what the answer to that question is.

Chris Adams: The question, the answer is likely to be about, oh God, this is so nerdy, mate. I'm so sorry. But like, what is the depreciation that we've just spoke about now? You said half of the cost in a data center is a depreciation. What's, how do you split that? How do you kind of, Amortize the carbon over these years and then how do you then share that with someone else?

So there's a company called Open, I think they're called Open Sesame or Sesame. They basically build data centers or like racks and stuff out of all of the, uh, Yeah, decommissioned stuff from Facebook and all these open compute projects, because all the companies, because you know how these servers are designed, and know how they're specced, it's actually quite common to buy these, and these tend to be cheaper than what you might have elsewhere.

And in many cases, it's not like, It's not like they rust, right? They really, they're, kept in kind of quite good con condition and they are working in a lot of cases, but the, they make the argument that, well, this is circular, so this is gonna be greener what you have, what you've been using elsewhere, but whether you are able, but yeah, it's, a number question.

It's an open question about how you account for that stuff inside, if you're purchasing, say, computing from these folks compared to people from somewhere else, because a lot of the time, order for in you to do this, you probably need organizations to be really transparent about where they got their servers from, and that's not always what companies are incentivized to do, basically, right now.

Asim Hussain: but then we get to that same argument of like, at the end of the day, that's going to be sold to somebody as like a dollar cost, like dollar per hour of a CPU. and if we just look at cost as a proxy for carbon, then you could argue there that will, they might have to end up selling that service at a rate that is actually quite comparable to a brand new server.

Chris Adams: Yeah.

Asim Hussain: This is where I think there's this kind of, I don't know if it's a breakdown or there just needs to be a lot more thought put into it. It's almost like there's a, that you pay a dollar value. There's a black box. And then at the other end, we know there's some sort of carbon emissions. And I think there's a lot of nuance there.

And maybe what I'm saying is that actually cost isn't a great proxy for carbon. Because really, maybe that is, I'm kind of refining my thinking as I'm talking to you. Maybe cost isn't a great proxy for carbon. Or maybe you put it this way. Three, four, five years ago I was advocating for it because we had nothing else.

Chris Adams: Mm.

Asim Hussain: There were so few other options, but I'd actually argue now, we have the capacity and capability, even if a cloud provider, somebody themselves don't even know what the carbon emissions are. There are models that now exist where you can estimate from what you can see about. But the infrastructure that you're using and make your own assumptions and make your own judgments as to what the carbon emissions are.

So I think I suppose where I'm thinking now is we can actually move beyond costs. I suppose that's where I'm thinking.

Chris Adams: Well, the thing I might share with you, and if you forgive the plug, so I've just been travelling all around Western Europe by train, and I literally started on the 31st of May, and I arrived at this conference called DjangoCon, which is a conference all around DjangoCon, Django, which is a very popular framework that initially powered, say, Instagram, and like, part of the NHS website, all this stuff here, yeah.

Asim Hussain: I used to be a Django developer. That was like my job. Yeah. My job, my paid for profession for quite a few years was a Django developer.

Chris Adams: Wow, I did not know that. Okay, no, that's a, okay, that's a story I'm going to use then, because I think we can bring this back to the cross thing for a second. Anyway, I did a talk, I, there was very short notice, I was going to deliver a workshop about how to, basically, how to use some of the tools available to kind of green your Django stack.

Right, so we were using a tool called Green Metrics Tool, which as Ana, one of the, like, I guess the founder of this, the guy who, the lead maintainer, he says the name is descriptive more than creative, but you kind of know what it's for, right? I quite like that. Anyway, that does give you figures for energy usage and embodied carbon and it does provide these and even provides like SCI figures. So there's now like a workshop and a deck and I will show a link to it to see how you can take an existing project and come up with SCI figures for various user journeys and things that you do have. Asim, I didn't have time to talk about the Impact Framework, and I, once I know enough about the Impact Framework, I'd be really up for using it.

But one of the key things I had to do was I was doing this workshop and then literally the day before I arrived, we had someone with a visa problem, so they couldn't do their talk. So basically the organizers asked me, said, Chris, are you, do you have a talk ready or are you, would you be up for filling this spot?

We have a 30 minute slot to talk about this. And I basically had 24 hours to take the workshop, turn it into a presentation. And the thing, the reason I'm talking about this is that I presented a kind of taxonomy of ways to think about these tools that you have. And I described things in terms of usage based and cost based specifically for this reason.

So you would use cost based tools to do your first round of disclosure or to work out like a baseline because until you, and until you've been able to demonstrate any value from doing this, it's going to be really hard to argue for like weeks of developer time to come up with some numbers. Right?

Whereas this at least gives you a number that you do have. And then I spoke about how you would use usage based tools to start figuring out, okay, well, what changes can I make to reduce some of this stuff? And yeah, I'll share the link to the deck, because it's, it allows us to create the, you know, we need, like, taxonomies to realize that we're not conflating these ideas too much.

Because a lot of the time, you're doing different jobs, and you're asking, you're being asked by different people. So, like, for example, the whole kind of Software Carbon Intensity thing, initially, it was, as I understand it was created partly because the sustainability, like the head of sustainability asks for some numbers, and if you're going to report along these numbers, you don't really see much in the way of incentives to show how you're changing in future, right?

it doesn't incentivize changes at the engineering level.

Asim Hussain: Yeah, yeah, yeah.

Chris Adams: right? So therefore you need a, you know, one of the thrusts would say, well, let's come up with a metric to show that we are planning forward. And we're taking some steps so that if you're an engineer, you have an idea of what's, what, you can do rather than just outsourcing all to energy procurement, because that-

Asim Hussain: Yeah,

Chris Adams: isn't necessarily the full solution, for example.

Asim Hussain: I mean, the way, I mean, I really love your taxonomy of cost based versus user based. I think that, yeah, I like that actually. And user based being more, perhaps more, more granular and more action. Cause it kind of gives you more, more specific things you can do. Whereas cost is like this really high level thing.

Just to bring it back to what you said about the SCI, the, one of the things, And I really, I didn't coin this, uh, but when it was coined, I loved it, but they described it as measurement for reporting versus measurement for action. And that's, I think, an interesting way of looking at kind of the different measures, uh, in this space.

And, you know, we talk about regulations. We need to talk about regulation. We want regulations a lot, but once you start talking about regulations, the measure that you have is a measurement for reporting and the, behavior it triggers is what, number can I disclose that I can defend? What can I defend? Whereas a measurement for action is kind of what number do I need to drive action change. And that's when we think about the SCI, it's a measurement for action. I don't know whether, where, it will need to land to be something, you know, to be, you know, To be, you know, defensible.

Like, I don't know why I'm gonna go off on a massive tangent right now, but-

Chris Adams: Go with it, let's go with it.

Asim Hussain: Go with it. Let's go with it. We know Krav Maga. You know Krav Maga?

Chris Adams: Wow, yeah, the Israeli martial art you're talking about?

Asim Hussain: The Israeli martial art. Like, I've always, there's actually a place nearby and I've always wanted to learn.

Chris Adams: I did not expect you to go in that direction, let's go with

Asim Hussain: Well, but let's just go with it.

Because here's an interesting thing about it. And one of the things that the founder of Krav Maga said, this is will never be allowed to be done in like a competitive environment. There will never be the world championship of Krav Maga. There will never be like this, you know, global Krav Maga, blah, blah, blah.

Because by, by that's when you start bringing in rules and the actual nature of the sport changes. So it doesn't become good at what it's supposed to do.

Chris Adams: Ah, yeah, so for people who are not familiar, Krav Maga is, it's like, oh, it's like punch him in the love spuds and all the stuff like that. It does all the kinds of things which you wouldn't do in a, kind of formalized mode, because they are, they're basically weapons of war, rather than actually weapons of art, right?

So it's more like, there's more martial than the art part, perhaps.

Asim Hussain: I mean if I'm gonna learn a martial art, it's gonna be there so I can like actually get out of trouble, so I don't mind like poking somebody in the eye or kicking them where they shouldn't be kicked.

But like, but I think that might, that's just one of my thinking and I'm, and I, this is just my thinking and this is a consensus based organization, so I just want to really be clear that I'm just expressing kind of some thoughts have and they might change in the future as well. You know, can you have both things?

Can you have a measure which is good for action and good for reporting? Or does, you know, as soon as you bring a regulation into a measure, does it then transform the nature of it, so it, you know, it doesn't become good as an action driving measure and it can only serve as a , as a measure for reporting.

That's kind of some of the thinking we've gone, I don't know how we got to this.

Chris Adams: No, this is a graceful segue into the next story, Asim, don't worry. All

Asim Hussain: But yeah, that, that's some of the thinking I had.

Chris Adams: I don't have a, I won't try to directly answer that, but what I will do is name check the new story, the next story we have, which is from Linklaters, the law firm, and they talk about, so this is going to be a bit of jargon.

Asim Hussain: Oh, yeah.

Chris Adams: I'm afraid, so this is a, this was a new story from actually a few weeks back, say, the new CSDDD compromise finally accepted by member states.

That is impenetrable to most people who are programmers, but the short version is that there is a piece of law. called, we already have a piece of law called the Corporate Sustainability Reporting Directive, which is a bit like, which essentially compels organizations of a certain size to disclose their carbon emissions on an annual basis, just like they disclose their financial things and their financial figures.

Different parts of the European Union are now, okay, for want subclassing the directive and turning it into their own law, right? So, France has been the first of the countries in Europe to actually do this. And Egalité, CSAD, yeah, like, they have a really hardcore version of the law, where if you are a corporate director, and you don't disclose, and you take steps to block disclosure, You have jail, you know, there are jail time sentences and stuff like that now.

There's some really, hardcore things, right? And that's like the disclosure thing. But the thing that's interesting is that this plays nicely with this new law, which is the Corporate Sustainable, Corporate, I think it's Corporate Supply Chain Due Diligence Directive. And this introduced some new demands.

So you basically need to like, as you'd imagine, Have some due diligence in your supply chain, but they also need to demonstrate how this fits into some of the laws or some of the kind of longer term goals of being a company active in, like Europe, where Europe has set targets of saying, well, you need to reduce emissions by, you know, we aim as a kind of union to reduce emissions by 55 percent and who knows, maybe even 90 percent by 2040.

And as a result, you know, you now have to publish a climate transition plan, which shows what your steps are to actually help get there. And, uh, this I think is interesting because this now means that you have basically a mechanism for accountability each year, I mean, kind of anyway, but you've also got something to show that you're looking forward.

So you've got forward looking and backward looking. And I think this is quite helpful for the conversations around, say, a consequential model like The Software Carbon Intensity thing, plus some of the kind of somewhat backward looking models that you might have with the GHG. And I think the GHG protocol, and this is how I now think about this, you will say that you might use the SCI to plan forward and say, well, am I going to do this versus that?

And that allows me to talk about, it's not just my organization, like, uh, are there places where impact is taking place where I don't have to put it on my books, but I know it's a significant problem, right? Because the current state of the law doesn't actually incentivize you to do that. And, uh, particularly if you're like, say, a media company, for example, where, you know, most of the impact is in a router in someone's home, or in someone's end user device, like their big ass television, you might not try and tell someone.

Hey, can you please stop using your big ass television and use a, tablet, right? Yeah, you might do that, but like, it's, that's going to be a hard thing for you to kind of argue is inside your kind of organizational boundary, for example, for, reporting. So this is why having two ways of looking at this is actually quite helpful.

And this is how I've expressed the difference between an SCI and the GHG protocol. The fact that they are complimentary to each other, but very but different.

Asim Hussain: Yeah, and I think that's, I never meant to throw shade on any kind of measurement for reporting, like it's all, needed. it's just different audiences. It's just different audiences, different needs, different, other things. So would you say the CSDDD is, because I just think the way you just described it, there's, it's, different to how some of the ways I've heard it described, but the, does it go beyond the organizational boundary?

So the climate transition plan that you have to expose, is it how it supports the EU's aggregate goal, or is it just how you, your organization plays, how its emissions has to reduce? Because if, it's an aggregate goal, then the kind of debate that you're just describing, which is like, I'm making my TV more efficient, but who cares? It's not part of my or something. That's not part of my effectively changing Help showing how you're helping the climate transition by things outside of your value chain.

Chris Adams: I need to stress, I'm not a lawyer. All right. Okay. And uh, I think I see, I think you mentioned that there might be someone who is a lawyer who does look at this, that I think it would be really nice to have someone who, with that deeper domain expertise to kind of talk about this 'cause. I'm mindful that because I have an English accent, it sounds like I know what I, that I am confident and, uh, about what I'm talking about when I might not be that well informed.

Asim Hussain: In a lot of you're very well informed in a lot of areas. But anyway, yeah.

Chris Adams: Alright. So yeah, I'm definitely not a lawyer in this con in, this context. Uh, but the, I guess the key, you know, your question is do you use 'em differently and would you be, I mean, is that the question that you had? Like, uh, uh, is that, maybe you could just repeat that to make sure I understand the question.

Asim Hussain: Well, I think it's interesting. I think it's, I think, because a lot of these questions are kind of like insular to an organization. Like what are you doing? What's your organization? How is your organization reducing its own like emissions? And then the conversation is basically coached around, "well, that's not my problem. That's not me. I, even though you could do something materially to reduce those emissions, it's just not part of my value chain. So I'm not going to be focused in on it." Is it, I presume because it's a business reporting directive. It is kind of very much like how, like you've, made, how are you as an organization going to your emissions in line with the EU's target by 2040?

Chris Adams: So, okay. That's, yeah. I think I understand your question now. So, uh, as I'm aware so far. The CSDDD is basically, they're still all focused very much on your own organization, right? So it, I think most of the supply chain due diligence part is about your upstream, right? Not necessarily so much stuff that you have downstream, for example.

So, you know, you might talk about who you purchase things from, but it might not be about to what extent am I incentivizing or am I accelerating the production of fossil fuels, for example, right? So right now, let's say, when we saw this, when we saw, I think Will Alpine, you know, he was a guest before, and so, so, so, so, so he mentioned this a while ago, and I think way, way back in the first or second episode.

He spoke about, okay, we need to be doing, you know, we, need to be using, we need to be responsible for our use of AI. Yes, we need to think about the green part, but we also think about these parts elsewhere. He's been like really, he's been leading on a bunch of this stuff and talking about this. Yeah.

Yeah. So, the yes.

Asim Hussain: Scope 4, he got me onto the idea of scope 4 emissions, which is like Very interesting.

Chris Adams: Yeah, so he, so like, he's been talking about this in quite kind of clear ways for quite some time. So, the scope 4 stuff that you've just mentioned, don't know to what extent that's actually included in this right now. But if you're talking about your plan, it's likely that if you're going to have a transition plan, you probably would have very good reasons to talk about what your transition plan looks like because you're helping transition the entire economy.

So it may be that you might refer to this, but this is where I'm outside of my kind of comfort zone, basically.

Asim Hussain: We can, lobby right now for what we'd want. I mean, what the ideal solution I would say is not lobby. That's the wrong word. We don't, do lobbying, but you know, you know, There is this overall aggregate goal that we need to achieve. And that's it. I love this. It was Henry Richardson that said that.

I remember it so specifically. I know the person that said it. And I know in what meeting they said it. was such a great statement. We were talking about the SCI. And we were talking about this whole idea of double counting. You know, double counting, when it comes to reportings and all this stuff, it's so significant because you're an organization.

You don't want to, you know, You don't want to be responsible for somebody else's emissions. You don't want double counting. But he said, actually. As a humanity, we want double counting because what does double counting mean? Double counting means that there's more than one person incentivized to reduce that emissions, right?

That's, the advantage somewhat of double counting. And actually, if you think of scope 3 in a way is double, counting across the board because somebody's scope 1 and 2 is somebody else's scope 3. But I actually completely forgot where I was gonna go with this.

Chris Adams: I'll try and rescue Asim before we move to the next story. So, we were talking a little bit about, and bring it back to digital services, right? The, so, I can't name the organization that we did some of this work for, but we were talking about a large media company, we were talking with a large media company, and we were helping them understand this, because some of the jargon, I'm afraid, that people use for this is like an attributional approach, which is like, are they my emissions? Versus a consequential approach, which is, do these emissions, you know, is this activity going to increase or reduce emissions? And when you're looking at media, for example, essentially, if you look at the attributional part and the GSG protocol, what you have to report on, right, you are incentivized to care about the data center more than anything else, right?

Because that's kind of inside your boundary at the moment, or what. Most organizations report as their boundary, right? Not every organization. But if you were to look at the consequential approach, you'd be looking at, yeah, all the things mentioned before. And like, the, this is quite a significant thing because for consuming digital media for consumers, the data center's making, Less than 10 percent, right?

It's tiny compared to the, well, the energy use at least of the, yeah, and uh, if you look at the energy use, it's going to be, you know, more than two thirds is coming from all the stuff at the end users, which is outside of your, you know, it's not on your book, so why would you care right now?

Asim Hussain: Well, it's an externality in a way, isn't it? Yeah.

Chris Adams: So this is, this is why I think it's interesting to see these two things have some interplay, and we, I think we need some wording for this right now.

Like, the one I'm trying to popularize is, you have climate disclosure, Which is one of my missions. And then there's climate response. What was my plan to reduce this? Right? Climate disclosure, you want your missions to be small. Your climate response, you want it to be really big. really, like, massive and ambitious and, like, loud and everything like that.

And that's what I think you can get behind.

Asim Hussain: But I think that's what Scope 4, that's why I think Scope 4 is a really interesting concept. It is, I've forgotten how it's defined exactly, but you know, things like your response, like things that you are doing outside of anything to do with making money or products, like that is what's counted in Scope 4.

But also it's like the impact you're having, the impact your, business and the work that you're doing is having on the fundamental problem of climate change. So, i. e. like, if you're enabling something which helps people to find another oil reserve, that's a massive scope for. That would like overshadow anything that you're producing in this world.

But scope for could also be negative, because if you're doing lots of work that actually sucks out carbon from the atmosphere. You can actually have a, like a, scope four, which a note, scope one, two, three, can't be negative, like, unless you're not doing, unless you're just not breathing or just sitting very still, but like, it can't be, but scope four could potentially be positive or negative and it shows your, like, how you, really like impacting the world, like.

Chris Adams: Yeah, so the thing we could possibly link to, I'm going to add to the show notes the episode we did, the podcast episode, which was all about AI and ML impacting climate change way, way, back in the day, I think June 13th. Oh wow, it's literally two years ago.

Asim Hussain: Is it two years?

Chris Adams: Yeah, we're recording on June 12th.

Asim Hussain: About AI?!.

Chris Adams: No, we've spoken about it before, but this is the, this is one I'm really, actually, I really loved this one. This was recorded on June the 13th, and this included, it was Abhishek Gupta, who's now, like, inside CAT, inside Climate Action Tech, which is a community that we're both part of. He's being funded on a micro grant to come up with some sustainable AI principles, but Will, Will Alpine, he, well, Will Buchanan is what he, before he got married, he was called Will Buchanan.

He mentioned a bunch of this stuff. And we also have Lynn Kaack, who was one of the co founders of Climate Change AI, which is another one of the really, in my view, really fantastic organizations who have real authority in talking about that. They mentioned a bunch of this stuff, so if you want to know a bit more about AI, look at these things from two years ago, because a lot of that still stands, and it's very, it's, I, learned so much from that one, basically.

So yes.

Asim Hussain: I get pinged by organizations all the time going, "oh, we want to talk about, or media, we want to talk about AI and, oh, AI and sustainability is suddenly a problem." And I'm like, we've been talking about it for a long time, like well before chat GPT came on the market as AI being a, hot topic of conversation in sustainability circles.

Chris Adams: Well, maybe the thing we should also link to in then Asim is, A, there's, so the GSF has actually started to endorse some existing legislation in America, to make this a bit clearer. But also, in Europe, I think something like a million and a half or a million euros, there was a tender a few years ago, to basically start researching some of this stuff that you might refer to as Scope 4, basically.

Like Scope 4 is, it's an idea, but it's not, there's no standard around it right now. So there was some work there to start looking at. This to see how you might quantify the positive and negative impacts of various steps. Now, because you've got, this was funded by the Green Digital Coalition explicitly to kind of measure the positive impacts, it's not surprising that every single intervention is only positive.

So it's not like there's a methodology for talking, oh, if we use AI to extract oil and gas, does this mean that we've, you know, there is nothing like that. And I would be very happy to see something like that because those climate emergency, see all this stuff here, right?

Asim Hussain: Well, that's one of the reasons I was thinking about this recently is kind of where we're starting to, well, we've somewhat measured our emissions. I'm starting to like, now that we're growing, right.

Chris Adams: This is the GSF you're about?

Asim Hussain: GSF. Yeah. And I suppose the green web is the same, isn't it? Like if you were to employ just one more person, your emissions would jump up significantly.

And so like, how do you meaning, meaningfully have a plan? Or what do you even say when you're like a very small organization that's just growing? Like, I mean, forget if you're

Chris Adams: If you hire five people, you've doubled your

Asim Hussain: have like you've doubled your emissions and you've set yourself a target to reduce that, what does that really mean?

And I think for, especially for organizations like you and me, like Green Web and Green Software, like if there was a scope for, our scope for is significant. Because the activities that we do as an organization, I don't mean scope 4, our negative scope 4's are significant. Because the act, us existing, arguably, hopefully, reduce the overall emissions of the world.

And so in a way you could, you know, it'd be interesting to look at organizations from their scope 4, because then you're investing in kind of a different component. There could be like startups out there who aren't like in the green software space, but have a negative, if you have a negative scope 4.

The more you grow, the more emissions get reduced from the atmosphere. It's interesting.

Chris Adams: I'm I'll be honest, dude, I'm a little bit I'm sceptical of this scope 4 idea because it very much, when I've seen people talk about it, they use it as a way to either say well this is why it's okay for us to deal with these really damaging things elsewhere, right, it's used to basically draw attention away from other things, or I just don't think like It's not, it's never going to balance out.

It's okay for things to be like, orthogonal, in two different, moving along two different axes, right? And I think it, that makes more sense. What you can do instead, is actually be responsible about the impact that you do actually have. And the, there's a, an approach used by the New Climate Institute, who I think, which I think is really interesting.

What they do, they basically say, look, We're a small non profit, our job is to be at, say, COP 28, 29, 26 or something and essentially work with policy makers to set the rules that end up impacting, influencing ginormous organizations that are way, larger than us. And what they do instead, they basically say, well, we have to fly there, we have to do something like this, we're going to impose an internal cost of maybe 100 euros per ton that we put into a kind of, I forget the term they use, Let's just call it a carbon war chest, right?

A climate war chest. And then they use that to fund other systemically effective things. And, like, this feels like a much more sensible way to do it. And this dude, like, dude, like, you know how the GSF, where the GSF came from, right? The funding for the GSF came from the internal carbon levy inside Microsoft.

You told me this before.

Asim Hussain: Well, actually, no,

Chris Adams: Oh,

Asim Hussain: I didn't, get there. No, there is an internal carbon levy in Microsoft, which is then used, to fund green measures but the actual, like, technically the money from this actually came from a different bucket.

Chris Adams: Ah, dude, I, ah, that would have been such a good story.

Asim Hussain: It's unfortunately not a good story, yeah.

Will Alpine, a lot of his work he did at Microsoft was actually funded from that war chest. He knew how to navigate that space and get money from that war chest.

Chris Adams: So this feels like a more sensible way to do it, right? The idea of saying, well, you're not trying to say, you're not trying to get back into eco heaven, you're being an adult about the emissions, and about that there is an impact being caused, and then you're talking about, well, what is the way that I can do it, which doesn't give you my sugar rush of saying, I'm carbon neutral again, but says, well, we have a societal goal to get to, so let's think about it in that sense.

I'm, this was, I mean, Microsoft is using an internal carbon price. It's not the same as a carbon tax, but it does revolve like, it's a discussion about how you allocate time and money to projects, rather.

Asim Hussain: It's a tax because different departments have to pay different amounts depending on how much carbon they've been deemed to have omitted. So it is kind of like a tax.

Chris Adams: Yes, this is something we can-

We don't want to use the word tax? Oh, is this another topic?

It's not so much that, it's, I mean, it's more that, yeah, you might not want to use the word tax in various places, because certain people are in favor of tax, certain people are not in favor of tax, right? And like, there are loads of ways where people allocate funds to various things inside this.

I mean, like, there's a reason inside Microsoft they use it, they called it a levy, right?

Asim Hussain: Oh yeah.

Chris Adams: But like, we, you know, there are loads of places where we allocate a percentage of some funds to funding something else. So this is why I've stayed away from using the term tax inside this, because in the way I see it, governments get to levy taxes, they get to like raise taxes and stuff like that, but organizations don't necessarily, and there are loads of cases where if you're inside an organization, you're going to allocate this much to kind of keeping your staff happy.

Is that a staff happiness tax? Or if I'm paying for cloud, right, and it's a chunk of my, let's say I'm building a digital service and I'm paying Amazon a chunk, or Microsoft, is that a Microsoft tax? I'm not sure it is. It's, I'm paying for something, right? Yeah.

Asim Hussain: Good point. Now that you've said the word tax like five times, every time you said it, I get a-

Chris Adams: You, sir, have said the word tax. I have not used the word tax at all.

Asim Hussain: Have you not? Okay. Well, I think it, I think anyway.

Chris Adams: I talk about internal, I talk about internal carbon pricing, because this is internalizing the costs that are otherwise being shifted onto society, and that seems a kind of economic and kind of grown up way to think about this.

Asim Hussain: Yeah.

Chris Adams: Yeah, uh, yeah, I'm not using that word either for very good reason, because there's another thing. Anyway, we've totally gone off script. This has been fun, though. Let's, should we go back to where we are? So we were going to talk about CarbonHack, some of the aftermath and learning points from that before we wrap up.

So are there any particular projects? So maybe it might be worth you just briefly summarizing what CarbonHack actually was, and then maybe if we talk about one or two projects. So, two projects that really caught your eye, then we can wrap up after that because we've this, has been, this was going to be a short, one and we're running about 50 minutes already, basically.

Asim Hussain: That's okay. People must have some long journeys ahead of them. Summer holidays coming along. Yeah, no, it was really good. So CarbonHack this year, we focused on Impact Framework, but more specifically focused around measuring, like how do we actually measure software, so it's really exciting. So, I'm really excited to be here where we can actually talk about this.

So, really quickly, Impact Framework is a framework that we've been building here to a very low level. You can measure, print, kind of most things with it, but also provide that evidence of the measurement in this impact manifest file. So there's a couple of, we had a couple of prizes. We had the ones I was very excited about.

I was inspired by all of them, to be honest with you. But the one I was really keen to see what people It was we just threw it out there. We were like, well, let's just see how people respond to this one. And it was beyond carbon. Because we've talked about carbon all the way through this episode.

But, you know, as we know, the sustainability challenge we had to have ahead of us is actually far bigger than just carbon. And we just left it fairly open. Kind of anything that kind of measures the environmental impacts beyond carbon was effectively it. And there was some really interesting submissions.

Like the one that won was, as we might guess, like water, like they, they measured the impact of water. And it also triggered some like really interesting conversations around, you know, the, I know there's been some research in this space, but like, at what level are you measuring it? Are you measuring the water impact?

Like at the data center? Kind of like primary. Primary and secondary, primary water and secondary water kind of was like the concept and it was just exciting. But now, what that means now is that there's now a plugin for Impact Framework where you can just, there's actually two, but you can drop it in and just say like, I just want to estimate my water impacts of my workload.

You can just drop it in and do it. Another, team was from a team called Grasp and I loved it because, you know, one of the things that plugin measures. Actually does a couple of different beyond carbon categories, but the three main ones are death.

Chris Adams: Okay.

Asim Hussain: Premature death, social cost of carbon, plus a dollar value on like the carbon emissions and displacement, which is kind of interesting as well.

Like how many people and all this stuff is like one of the, you have to submit like citations and research to prove and evidence kind of where these numbers are coming from. But yeah, you know, like social cost of carbon, we know like what is the cost of carbon as we take it down through the generations and, you know, all this other stuff

Chris Adams: So that's the harm caused by, on society, by the people, right? And like, this is what the, that was 50 under Barack Obama's time in America, went down to 1.

Asim Hussain: No, I think it's two.

Chris Adams: or 2, and then that's gone up to 190 now. No, I think it's actually back to 50. But there, I think the, it's now shifted to a very, a much, Like, fourfold increase, or nearly a fourfold increase in the US, for example.

But this is like, and in Europe it's around 100 right now, that's the figure.

Asim Hussain: I don't, yeah. I don't believe they use what Biden decided and wrote on an exec. It's it was more, more from research.

Chris Adams: Oh, I'm not saying that's like, that's not Biden saying this, that's like, the group who was allocated to do this work, these are the things they've recommended for this. And that's how they've, that's what the number looks like is being mentioned. I'll share a link to that as well, actually, because that's actually This is, really helpful for the internal carbon pricing stuff we discussed before.

If you're going to think about, okay, how do I create a carbon war chest to fund the work like Will Alpine did, or founding an organization, or doing any kind of systemic work. Yes.

Asim Hussain: Yeah, but I think that's kind of like where it's interesting. cause you know, sometimes I do feel that. We sanitize this conversation too much. Like it's too sanitized. Like we talk about carbon, we talk about this, talk about that. But actually, the reason why we're here is this is there's a lot of human suffering that is happening and will increasingly happen because of the work that we're doing and the work. There is, that value in this whole, whole question.

Are you trying to like add a cost to carbon? How many people will likely be displaced because of rising sea levels

Chris Adams: Always like climate migration being informed.

Asim Hussain: Climate migration. Yeah. so like, and of course there's also research which talks about what is the increased death rate, you know, You have to look at kind of, not just carbon emissions, but air quality and things like that.

So there's these, so these are the impacts. I mean, I, and I know it's kind of, it can be hard for some people to swallow, but it is, you know, something I think about a lot. I actually have a big skull next to me. It's like, I'm very stoic.

Chris Adams: You are full of surprises. Wow, you've got kind of Shakespearean kind of Wow.

Asim Hussain: A little

Chris Adams: Alas, poor Yorick. Wow. I did not see that coming at all.

Asim Hussain: Well, you, it's a stoicism thing.

It's like, if you, contemplate death a lot, you, live life more. But those are two, two, two, two really good plugins there. But there's just been, it's hard to like really pick up on the rest. There's some really good work done to using Impact Framework, not as like, not building a plugin for it, but just leveraging it to examine what the emissions of machine learning is.

And the important thing about that is, is the output of it is this kind of very standardized manifest file, which anybody can read. You're

Chris Adams: Like an auditable or repeatable

Asim Hussain: audible, readable, and you're just reading this manifest file. And as soon as you look at this manifest file, if you know now how to read these manifest files, you can go, Okay.

So, straight away, I know you did this, you used that coefficient. I get the kind of measurement that you are. I can, that's an interesting number you generated. So that's one of the things we want to drive from it. And the best, yeah, there's some great work from, I've forgotten the name of the team now.

But the, they did work on the, trying to figure out the, using impact frame in a very In a usual way, which is like in logistics, can you drive, can you create a manifest file which represents the emissions of like a fleet of cars, like delivering Amazon packages all over? Can there be a manifest file for that?

And, uh, I think the winner was they built, it's called green. Oh, no, I want to mention two other teams and they both got the same name, which is very confusing in the hackathon. Find a called green and meet green. Oh, I forgot the actual name of the team. It was green something, but they, uh, they built Kubernetes.

So an interface into Kubernetes and the reason why it won, it was just like Kubernetes is so ubiquitous on the internet. And now if you've got, and it wasn't using, there was a separate one for Kepler, but this is very specifically for Kubernetes, independence of Kepler, taking the observations from there.

And you can compute the, environmental impact of that. And I think, actually, I shouldn't have mentioned it, that my favorite solution was a team called Greener Meet. My absolute, I all, I'm sorry, all of the rest of you, you all weren't my favorite solution. My favorite solution was a team called Greener Meet.

Chris Adams: Green Me, as in, like, Greener You, Greener Me, or Greenami, like Konami?

Asim Hussain: Greener Meet, as in having a meeting.

Chris Adams: Oh, Greener Meet, as in zoom, not like.

Asim Hussain: Zoom. And it was exactly

Chris Adams: Okay.

Asim Hussain: And we had an under 18s prize, which we really spent a long time with lawyers trying to figure out, can we do an under 18s prize? But we managed to get one together. And it was a team of 16 year olds from school in California.

And they created, they used the Impact Framework to actually measure The environmental impact of Zoom. So they literally like they, they got Python libraries. They, ran Zoom calls. They could get the utilization. They compared it to Watttime and they even found they were like, they even switched on and off features of Zoom to show like how that changed the emissions profile of your call.

And even I loved it. They found a curtailment that they were having a meeting and cause they're in CAISO. They

Chris Adams: CAISO being Californian Independent Systems Operator.

Asim Hussain: I knew you'd know that.

Chris Adams: And that's basically the grid operators in California you're talking about.

Asim Hussain: And California has a lot of renewables, as you know, so they had a moment in the meeting where they curtailed, which means that the emissions are effectively zero for the call now because they're factoring that in.

It was really good work, and we tried to give them the prize on the call. They, we were delayed. They had to go to class. So we couldn't give the kids the prize, and if we can, maybe we can bring them on this podcast. I'd love to speak to them. I just, it gave me such, honestly, you watch this, And I'm sorry to the rest of the prize winners, but I think this was the best video.

It was the best presented. And I'm just sitting there thinking, these are the, now we're going to, now we're going to, " the kids of today!" - we are old. These are the kids of the future. You know, maybe it gave me so much hope, like these are 16 year old kids and they were doing some incredibly advanced green software, measurement, reporting, zoom, understanding curtailment, understanding like how to measure this stuff.

And I was like, ooh, we've got a, we've got a good future ahead of us. I think, I don't think, yeah.

Chris Adams: Asim, this sounds really cool, but I have to ask, right, why are we relying on a bunch of literal children to do this work when Zoom is a multi billion dollar publicly traded company that does have to report on its own figures like this, and they are doing, Zoom doesn't expose these numbers themselves, right?

Like they will tell you how much you've saved, but you can't see the figures from this. We're relying on children to do the work of essentially publicly traded companies here, right? Right. This feels like a, we, I think this is really, cool. But this has an open question about what they would do maybe Zoom or they might join an organi organization like the GSF and say, well, this is how we do measure this stuff. And, uh, 'cause if not, I think we might need to refer to the work of children until that happens. Because this is just like, I mean, if, this embarrasses them to actually being more transparent about how this is being used, I think, we should be doing it because it's kind of bonkers that you are relying, like, it's nice to have like youth of today, but one of these groups has literally access to billions of dollars of capital and one of these groups is doing it in their spare time and couldn't even accept the thing because they had to leave for class. Yeah.

Asim Hussain: For class. Yeah. Yeah. I mean, that's a fair point. But at the same time, I mean, I want to counter your point for a second as well. I mean, I'm, you know, I have multiple views. Like, do you really want to be waiting all the time? Like, we're just waiting all the time. We're just sitting and waiting and waiting and waiting, for everybody to be transparent about all of their emissions all the time.

If we can just take that power back into our hands, And we why not wait for people to be transparent, but actually like, look, this is a model that I've created. I think this is the emissions profile of your product. I'm going to publish it. If you feel somewhat different, that's the beauty of open source.

If you feel somewhat different, create a pull request and be, as transparent as me. I think in a way we, it is good. That we're leading the way, it is good that the kids are leading that way in the future because it kind of brings power back into our hands, if that makes sense.

Chris Adams: I think what it sounds like you're suggesting is in the absence of information, it might be worth using the age old internet trick of ask a question on Stack Overflow, answer it with an incorrect answer, then hope that people will actually come up with better answers, because that's the tried and tested way to get a good answer on Stack Overflow.

You answer it incorrectly, then someone goes, no, you're getting it wrong. Now I'm doing it, because they're so incensed that someone is wrong on the internet. So this basically, I think what we can use that, we can harness this natural resource and we can say, we're only going to use the worker of these children, and we're for talking about Zoom calls until someone comes in with actual better figures and ideally the organizations with full access to this, like maybe Zoom themselves, or maybe a competitor of Zoom.

So if you'd like to do this, I'm chris@greenweb.org, no, I'm very happy to have this conversation because this does feel like it's necessary. Anyway, oh, blimey, I've just seen the time. Asim, we've, gone a bit over, but this has been really, fun and,

Asim Hussain: Yeah. It has been!

Chris Adams: I, this is, We've got another one of these in a few weeks time.

So, Asim, really lovely chatting with you, nice to catch up, and sorry to hear about the mushrooms, but I guess the Mushroom Kingdom's loss is the Bread Kingdom's gain. So, I should probably wrap up now. Folks, if you've made it this far, we will be sharing links Pretty much everything we've discussed and which you can find at podcast.greensoftware.foundation. And thanks again for listening. My name is Chris Adams and this is Asim Hussain of the Green Web Foundation and Green Software Foundation respectively. All right. Thanks, Asim, mate. Take care of yourself. Okay. Bye.

Asim Hussain: Cheers. See you later.

Chris Adams: Hey, everyone. Thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts.

And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser.

Thanks again, and see you in the next episode!

View Details

In this episode of the TWiGS, host Chris Adams welcomes back Anne Currie, Sara Bergman, and Sarah Hsu, authors of the book Building Green Software. They dive into the latest updates and hot topics at the intersection of sustainability and software engineering. The discussion highlights the importance of making software and hardware more efficient and explores cutting-edge topics like serverless computing on Kubernetes with WebAssembly, the circular economy for electronics, and the potential for dynamic pricing in cloud services based on renewable energy availability. The episode emphasizes the ongoing energy transition and the need for innovative solutions to reduce the carbon footprint of technology.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Anne Currie: LinkedIn | Website * Sarah Hsu: LinkedIn * Sara Bergman: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Introducing SpinKube [04:11] * Staggering quantities of energy transition metals are winding up in the garbage bin | Grist [10:25] * THE GLOBAL E WASTE MONITOR 2024 [10:50] * Analysis: Fossil fuels fall to record-low 2.4% of British electricity - Carbon Brief [16:27] * https://github.com/open-telemetry/community/issues/2020 [23:03] * Explore Traces | Honeycomb [24:40] * https://www.microsoft.com/en-us/corporate-responsibility/sustainability/report?icid=SustainabilityHomepage01Report2024 [30:20]

Events:* https://ndcoslo.com/ [47:55]

Resources:* Building Green Software * Environment Variables Podcast | Ep 67 Building Green Software * https://links.danielle.fyi/ [05:55] * Working toward a net zero future: Evolving our work with energy companies - The Official Microsoft Blog * https://grist.org/accountability/microsoft-employees-spent-years-fighting-the-tech-giants-oil-ties-now-theyre-speaking-out/ * https://www.scaleway.com/en/ [37:54]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
Anne Currie: That is the nature of renewables, is that they are variably available, and we just have to, we have to take advantage of that, not fight against it, and not constantly wish we were in the fossil fuel age.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host, Chris Adams. Hello, and welcome to the Green Software Foundation podcast, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. In this episode, we welcome back the authors of the book, Building Green Software, Anne Currie, Sara Bergman, and Sarah Hsu, for an episode of This Week in Green Software,

our roundup of what's happening and hot at the intersection of sustainability and software engineering. So Anne, Sara, Sarah, I know that you've been on the podcast before, but I wanted to just provide a bit of space for people who are new to this to let you introduce yourselves. Anne, it's okay if I give this floor to you before we run through the usual roster?

Anne Currie: Yeah, thanks Chris. So, my name is Anne Currie. I am the CEO of a training company, Strategically Green, and I have been in the tech industry for pretty much 30 years now, and I am one of the co-chairs of the Green Software Foundation Community Group.

Chris Adams: Cool. Thank you, Anne. All right. Sara, is it okay if I hand over the floor to you next?

Sara Bergman: Sure. Thanks for having me back. I always enjoy being on the podcast. So my name is Sara Bergman. I am a senior software engineer at Microsoft, where I work with the Microsoft 365 products, which is very fun and exciting. I'm also one of the co-authors of the book Building Green Software. And other things that are new in my life is I'm recently back at work after maternity leave.

So I'm still figuring it out, you know, what is life now?

Chris Adams: Well, welcome back and congratulations on, yeah, the new instances of Sara, I suppose. Yeah.

Okay. And moving on to other Sarah. Sarah Hsu, if I give space to you to introduce yourself.

Sarah Hsu: Hi everyone. It's nice to be back. So my name is LSara Hsu. I am an SRE working for a financial institution. I'm also a project lead for the green software course for the GSF and similar to Anne and Sara, we recently just published a book by O'Reilly called Building Green Software. Very excited to be back.

Chris Adams: Cool. Nice to see you again. And Sarah Hsu, we met in person for the first time when you were in Berlin delivering a keynote for, was it CamudaCon, the conference there?

Sarah Hsu: Yes. A Process Orchestration Conference, which is exactly what we need, right? Because their motto is automation. And automation is the foundation of modern software systems. So...

Chris Adams: thank you for that, Sara. I was also pleased for us to both realize that we had arms and legs and were more than just a YouTube square, basically, or a square in a Zoom call. So yes, that was lovely as well. Okay, for folks, if you've never been listening to this podcast before, my name is Chris Adams. I am the executive director of the Green Web Foundation.

It's a Dutch nonprofit focused on reaching a fossil-free internet by 2030. I also work as one of the policy chairs of the Green Software Foundation Policy working group as well. And before we dive into some of the stories, that's the format of this show, we'll be sharing links to the show notes and all the stories that we do discuss.

So there'll be on GitHub and Markdown, what else, for you to look through. Alright, so the format we normally do is do a round up of news stories, but you three, because I have the pleasure of speaking to people who've written a book about green software, we figured we'd make it a little bit more interesting for listeners and touch on some of the topics in the book, so we've got a bit of a kind of nice way in to cover some of that content. Does that sound okay to you folks?

Anne Currie: Great.

Chris Adams: Alright then, so the first story that we have is actually about a new project called SpinKube. So this is hyper efficient serverless on Kubernetes powered by WebAssembly. Now a few podcasts ago before, we did a whole story all about Wasm, WebAssembly, and why it's an interesting piece of software. But, previously, back then, it was only available on Nomad, which is a similar scheduling tool, but not the same as Kubernetes. And this story, as I understand it, is basically the idea of providing some of these kinds of tools for Kubernetes, the most popular scheduling tool for this. This basically means that if you thought that was a cool idea, you've got access to it yourselves. And Anne, I think I might hand over to you for this, because this really touches on some of the things you spoke about in your book about operational efficiency versus coding efficiency. Maybe I will hand over to you here.

Anne Currie: It really does. So Wasm is something that I find absolutely fascinating. It's both, as you say, both from, at the moment, the operational efficiency perspective, because they're really focused on how you can bin pack as much work onto each machine as possible. So you can reach that magic 50 percent utilization number and then get even higher, which is very hard to do without a tool to help you.

Very hard to do. But beyond that, what also is, is they have ambitions even further, which is that they want to start actually optimizing the code that you write in WebAssembly as well, so that under your feet, it will become more efficient. And we all know that writing efficient code is really, really hard.

There's a, there's a huge impact on developer productivity. And we, we cover this quite a lot in the operational efficiency and the code efficiency chapters of our book. And one of the senior engineers, Danielle Lancashire at Fermion, who's behind all this Wasm, one of the, one of the groups behind all this movement in Wasm came and talked to me, talked for me at a conference in London a few months ago, and she was actually talking about code efficiency, the code efficiency improvements that come from Wasm.

Now they're a bit down the road. The moment they're focusing on operational efficiency, but I really like to see a platform with a vision for, because in the end, we're all going to have to run on much, much less power at times when the sun isn't shining and the wind isn't blowing. That is the nature of renewables, is that they are variably available and we just have to, we have to take advantage of that, not fight against it and not constantly wish we were in the fossil fuel age.

And so I really like to see a platform which is thinking about operational efficiency now and also thinking about code efficiency down the road. So I was, I like Wasm from that perspective. I think they're doing a lot of nice work.

Chris Adams: Yeah, we have some nods here. I just realized when I spoke about this story, I dived straight in without really explaining why some people find this actually exciting in the first place. So when we spoke about things like, say, serverless, and one of the, as I understand it, one of the key things behind this tool is it's like a very fast version of a serverless platform that spins up and down quite quickly.

So we've had previous generations where you might need to have a bit of a wait before a piece of software can start running before you can really use it. And this is like one of the key things that Wasm has made available. And that allows for, like you said, time, it basically means that there's less wasted time, but it also provides, opens the door for newer, more efficient platforms like this. Okay, before we move on to the next story, Sarah, Sara, is there anything that you want to add to this?

Anne Currie: Actually, before we move on, I'm going to just hark back to something that Sarah said just before this, which is that the benefits of modern ops and automation is that a big part of automation, of modern automation is the ability to spin up quickly because things like auto replacing, just having stuff sat around waiting and for you to fail over to with autoscaling, which is vastly more operationally efficient, relies on things being able to spin up fast.

If you can't have fast instantiation, you can't have a lot of these modern automation, this modern progress in automation. So yeah, it is a really good thing.

Sara Bergman: Also, I think one thing that has been said before and can always be said again is the benefit of the sort of platform that makes it easier for people because people want to be green, but sometimes it's a lot of work and anything that can make it less work to be greener is a great thing and should be celebrated.

And on the ops side of things, not every software developer or software person is like, highly interested in that. There are some people who love it and like go all in, and there's some who like, "I just want to write my code and like deploy it in some way to my users." So therefore things like this is so important to, to help bridge that gap in a green way.

Sarah Hsu: Yeah, yeah. I a hundred percent agree. Like software engineers, we're inherently lazy people, right? Like none of like, not speaking for you guys, I'm not a security expert, but I know how important a secure application is, right? I'm waiting for this tooling framework and best practice from the security people. So I think that's the gap we really trying to fill, that "how do we make everyone else have that ability to be green at their fingertip without having all the knowledge of like being really green?" And like, yeah, I feel like we can talk about operation efficiency to... I mean, to, 'til tomorrow, yeah, because it really is the lowest hanging fruit and people don't realize how many things we're already doing or have like knock on green benefits, like exactly what Anne said about reliability and resiliency.

Yeah. They all like come down to like automation and how do you utilize automation? Right. Anyway, I think we should stop. We can always come back to it. Let's get through all the other stuff. And then we come back to talk about Green Ops.

Chris Adams: Okay, all duly noted. All right, so we've spoken a little bit about operational efficiency, which is the running of servers. Spoke a bit about coding efficiency, which is what a lot of people might reach for first, or people wouldn't typically think about. And, but there's other ways you might talk about this.

So let's move to the next story. Sara, I might actually ask you about this one. So this one is a story from Grist magazine, which basically is talking, it covers the staggering quantities of like, Transition metals that we're currently throwing out when we could be mining them. And while we'll share a link to this in the show notes, one of the key things that the four of us can see right now is a chart showing some of the minerals that we hear associated with a transition away from fossil fuels to greener forms of power. There was a report by the UN called the Global E-Waste Monitor and they've shared some of these stats for the first time. And one of the key things is basically that we are throwing out something in the region of 62 million tons of electronics. And when you look at the actual mineral content of that, in some ways it's actually comparable to the demand for new kinds of metals that we have.

So the charts that we'll link to here, things like, say, copper, it's not that, it's quite similar to each other. Some things like cobalt or neodymium. These are, we're basically looking at the amount of minerals that could be circular. Some cases are not the same. So things like lithium, for example, we still, there's still a lot of demand and there's not nearly enough that's in circulation. But this feels like this provides an interesting flip side to the whole discussion around what we do with our stuff. And I think the term that I saw in the book, which was hardware efficiency. So I kind of wanted to like, see what you folks thought about this, in particular Sara, because this is one thing we spoke about in a previous podcast, like, this feels like there's more than just "hold on to your kit," for example, there's maybe a chance to talk about things in a more circular fashion.

Sara Bergman: Absolutely. And I think the key word there is circularity. E-waste is the fastest growing waste stream in the world, which is saying a lot. And it is growing for several reasons. Like we consume more, we have more devices, like more devices are smart devices. My, like kitchen fan has an app. I don't know why it needs an app, but you know, there, there are an increasing amount of what can be classified as electronic, not what can be classified, but what is electronic.

I see the same with like toys and things. So that's one thing. And also we crave the newer and the newer things and things have shorter and shorter Life cycles or the use phase is short and shorter. So it's, it is fast growing and before, in a time before time...

no, but when it was not the case that it was so fast at growing, we could maybe afford to mine everything.

But now when the consumption is so high and the throwout rate is so high, we really need to start thinking in a circular way. Because, in the end, there is only so much metal in the ground and our earth is finite. It's not something that grows back, at least not very quickly. So having this thinking, I think it's going to be, it needs to be a game changer.

And I know several countries have adopted what's called the right to repair, which is basically that you

Chris Adams: is big thing in Europe.

Sara Bergman: Yeah, it's a big thing in Europe. China has, no sorry, not China, India has a similar legislation. New York has a similar legislation. And that's really good. And that's about what you said, holding onto your kit longer.

But that's really only one side of it. I think the right to recycle should be equally hotly debated, perhaps even more hotly debated. Because we, the hardware industry has been forced to make hardware kind of hard to recycle because we are demanding better, yet smaller devices, or bigger screens, but thinner, lighter hardware.

And that's really complicated to produce. And it makes it really hard to recycle. Also in this article that you linked, let me find the number. But, what they said, the percentage of ethically recycled waste was also staggeringly low. It's like a business as usual case was only 20%. It's, well, you're all going to have to go to the show notes the article for yourself to find the percentage.

What I'm meaning to say is that this is incredibly important and something that is an additional dimension to the conversation beyond holding on to your hardware. It's also the reuse and recycle part of the story.

Anne Currie: It's a sales feature as well. It's recycling and it's a sales feature. I just bought a new phone, new, it was an old Pixel 7a, because my previous one had run out of security patches, the classic way that you have to throw away a working piece of kit. So I was quite annoyed because I was having to throw away a perfectly working piece of kit.

So I bought 7a. But the 7a sent me all the stuff to do a, to send my old phone back, and I got 25 percent off and I thought, "well, actually, that was pretty good." I actually felt quite good about that in the end. I thought, well, it's going to be recycled. I got 25 percent off. All right. That was, it was, it felt like a feature that they were offering me.

Chris Adams: Well, this is, maybe this touches one of the key ideas that, if you're moving away from linear economy, once you've, dug these minerals up once. One of the ideas is that once they're in the kind of sphere that we are in, right, you don't need to have, it's not that going into the atmosphere like say fossil fuels for example.

You can have these things circular. Now, this is one thing that we don't have quite the policy support for yet, but this is one thing that we could definitely be seeing more of in future, and this feels like the direction we might be heading towards if things work out, basically.

Sarah Hsu: Yeah. I also think it's an age old thing, right? We should find the thing that fits your purpose. It's similar to say, we want to find the VM instance that fits my purpose. I feel like people shouldn't want the latest and the greatest. Like my laptop is not that great, but I don't do that much on my laptop.

So like, I think people also need to start having that mindset. Like, "Oh, I don't need like the fastest, like the most, you know, cores, power laptop, choose to go on Zoom call, do a little bit of coding." And yeah, I think that's another bit of the things that also really fit into operational efficiency, you know, where you want to find things that fits your purpose.

And I think that applies to hardware as well.

Chris Adams: I agree, actually. All right. Thank you for that, Sara. All right. So, we're going to move to the next story now. This is a story from Carbon Brief. And, Anne, I'm going to hand over to you for this one because this is one thing we discussed before. So, this is a story from Carbon Brief who basically mentioned that earlier on this month, no, last month, actually, now.

The UK's electricity grid operated for a whole hour with just two, almost no power coming from fossil fuels. Now this is a record low for the country and this hopefully is a sign of things to come. So Anne, I know that we discussed this here, but maybe you could talk, touch on like why you found this interesting and what it's kind of telling us as software engineers perhaps.

Anne Currie: Yeah, I mean, obviously this is an incredibly positive story, and it's actually the direction that almost everybody's going in. If you haven't had a play around with electricitymaps.com to have a look at how green all the grids of the world are, it's absolutely fascinating. You'll learn a lot. And if you step back in time, it shows you what the carbon intensity, the average carbon intensity is of every grid in the world that they can get data on, which is a surprisingly large number of grids.

You'll see that if you, and then you can go back in time and step forward and you'll see that everything is becoming greener and greener. The energy transition is happening. You know, it's not just something that will be happening in the future. It is happening, but it won't be easy. Oh, I saw an excellent Uruguay is apparently completely a hundred percent green for eight solid months this, this year.

So there are, but that is because, but the interesting thing on this is that every country does it in a different way and every country being the green intensity of their grid, it varies over time in different ways. It depends what you're using to generate the power. So places like Uruguay have loads of solar and wind, which is fantastic, but they also have tons and tons of hydro and the hydro is used to smooth out the times when the wind isn't blowing and the sun isn't shining.

In the UK, we don't have so much in the way of stored, so it's great if it's windy, and if it's sunny, but mostly in the UK, so if it's windy, we do an awful lot of offshore wind, rather, not onshore wind, but offshore wind.

Sara Bergman: I thought going to say, we don't do a lot of sun here.

Anne Currie: We do not do a lot of sunny here. It's actually, it's not as bad as, I've got solar panels, and through the summer, it's actually, well, through half the year, that will cover all my household usage.

It's oddly much better than you'd think, but nonetheless, in the UK, it's mostly wind. But there's not so much in the way of storage. So it's, the UK is an absolutely excellent example of we're going to have to get good at using power that's variably available and cheap when it's available and either demand shift or demand shape so that we are using the renewable power and using less of non renewable stuff.

So it is absolutely fascinating. It's a great story. It's a really good move forward, but not all grids are identically green. They all have difference. Different ways of doing it and results.

Chris Adams: Alright, I've got a pop quiz for you then, because you're talking about the fact that the grids change, and sometimes they're going to be greener because there's more clean generation on the grid versus other times, right? We know in the UK, for example, there's groups like Octopus Energy, who basically will change the cost of your power, depending on the time of day.

In some cases, they even pay you to use this. And we see this in other parts of the world. When do you reckon we're going to start seeing cloud providers do this in the net? Because we know it happens, and we see this stuff, but none of these signals are passed on to software engineers yet.

Anne Currie: No, and every time I'm speaking to somebody from a cloud provider, I ask about it. Normally the people are quite green people and they want it to happen, but I think it'll be a way off. Now, it's, it's interesting. I spoke to somebody who was working for a cloud provider, but was a software engineer who used to be in the insurance industry.

And he was saying to me, "Oh, well, you know, I can totally see it being to the advantage of the cloud providers to start doing dynamic tariffs, time of use tariffs, because then they have another product they can sell." So the people who can't do it, they will sell them insurance with a price cap. And obviously they'll charge a load of money for that.

If you know, but, and then that is a product. Now, well, is that what they're gonna do? They'd be quite sensible to do it. It's, you know, the cloud providers are very good at making money and it won't be cheap. So I would love to see it, but I think it's going to be years before it happens.

Chris Adams: Okay, so you're thinking three years at least for you, Anne, yeah? Okay. Any other takers for anything faster?

Sara Bergman: Yeah, no, I think, well, working for a cloud provider, I just want to say, I don't know. But what I think all, at least the major cloud providers are fairly open with their use of PPAs, so Power Purchase Agreements, as a way of, yeah, meeting the green energy needs, because they have data centers sort of where they need to have data centers and then use PPAs to, to handle their Scope 2 emissions.

And I think because all of them at least are so seemingly tied to those agreements, it is a contradiction between those and billing a customer for actual usage. So I think it could be like a complicated thing for them is what I suspect. But I also think it's something that customers would really appreciate.

So I'm hoping it will be sooner, but no, I'm with Anne.

Chris Adams: Okay. Years away. And Sarah, you've got something to say, it looks like.

Sarah Hsu: Oh, I was just going to say, probably not in the near future, but we just need one person, one cloud provider to do it and everyone else be like, "right, we need to do it too."

Chris Adams: Do you know what? I had a conversation from people outside of the big three, the big cloud providers. So, in Texas, there's a company called Build AI. They've been doing some work to basically, they'll provide you computing, but at certain peak times, you don't have access to it. And as a result, they're able to have much lower costs for this stuff.

So I'll share a link to that. And there's a company called Saluna, also in Texas as well. And what they do is they speak to generators, people who run like clean energy. And they'll basically say, we will give you a floor price under which you will never, you know, we'll always get give you something like that.

And using that, they are able to provide these kind of services. So we are seeing this start to develop, just not with the big providers. And we'll, I guess the next question will be, at what point do these new providers get bought by the big providers to protect the margins? Because that might be the logical thing to do if you have these kind of funds. All right, let's move on from that, because that was a, we spent a bunch of time talking about carbon awareness, and there's a few other stories that we have up here.

Anne Currie: But carbon awareness is the most important thing.

Chris Adams: It's definitely

Sara Bergman: And operational efficiency.

Chris Adams: Alright, ok, so let's move to the next story then. So, we have another story here, this is actually probably the nerdiest story we have here. This one is actually a link to an issue in the OpenTelemetry repository. Basically, there is a standard called OpenTelemetry which is designed to make it easy to understand what the, I guess it's to make Infrastructure Observable, and Sara, I might need some help from you on why observability is important.

But this one is basically put forward by, I think, one of the people who's inside the Green Software Foundation to start agreeing some sustainability metrics to expose in all the kind of tooling that we currently do have. This was really interesting because this feels like, A, this is something that I saw discussed in the book, but also for people who are not familiar with OpenTelemetry, OpenOps, or even Observability in general, is anyone who might want to go, like, enlighten us or at least give us some points about why this might be interesting from a Green Software perspective? Sarah, I might hand over to you because you wrote part of this chapter for the book, I believe.

Sarah Hsu: Yes. So I guess observability was born out of necessity because things are so complicated now. Microservices is made out of our world. And sometimes one requests have to travel like the entirety of a street of like a hundred houses before they actually reach a part of their journey. And it's really impossible to figure out what and where things have gone wrong, right? Metrics is for when you know something is going to go wrong and then you set up a metric to monitor that. But then in this unknown world, it's really hard to figure out who is going to break, for example, like, oh, I can't, I forgot that guy's name, but someone from Honeycomb.

You guys know how much I love Honeycomb. He gave a really good example. Like if you're like a, like an iOS developer and you support like 10 different phones in 10 different countries, and suddenly one version of the phone in this country is going to break. How do you know to monitor that using metric?

So I think that's a really good example, like why we need observability and observability borrowed its thinking from control theory, which is like, we are trying to understand the internal state of a system by just looking at its outputs. And outputs here are like telemetry. And telemetry, you've got logging, you've got metrics, you've got traces.

And so basically OpenTelemetry is, it's like a set of framework. It's about the creation and then the management. All of those telemetry, it's actually not a backend. So it's not like Prometheus. It's not Jaeger. It's not like Grafana cloud. It's just a convention, which is really good. I remember when we were all in QCon a few years ago and Daniel was talking, Daniel from Skyscanner was talking about their OpenTelemetry migration plan or something.

They basically went from like 300 different components down to 150 because they used OpenTelemetry as a standard, as an auto collector. And then that's the way, become one stop shop for all the telemetry. It's like, you don't need developers sending three different telemetries to three different backend systems.

And then one big thing, everyone's being on call here. One big thing we find difficult is how do I context link everything? Why I need to basically, "oh, this logs happen at 1:21 PM. Right. Let me go find the traces that also happen. But what if time shift, right?" And sometimes like Something is in a different time zone.

So anyway, that's a massive rant about why we need observability. So it's, I know, sorry, it's my job guys. And then I guess one big thing we talk about in the book is that green software needs to be ready with observability. Like we need to be with it. Right. So for example, in this complicated microservices world, we want to be able to know which component, which process.

It's emitting the most carbon. Right. And that's where we want to be. And we need OpenTelemetry. We need people like OpenTelemetry to help us get there. So it's like absolutely amazing to see so many people are standing up and then it's like, Hey, we should add this like semantic thing.

Chris Adams: I'm really excited about seeing this because I've used Honeycomb to understand what was broken about some applications I've been running before. And I was always a little bit wary about saying, well, okay, I'm not sure about, I want to be totally tied to one provider. And this here seems, and we have seen some providers who have started to make some CO2 figures for this. There's, confusingly, a, so a company called Sentry that do provide this and they even propose like a HTTP header for CO2 per request, right? But to see this at a kind of standard level, this feels like it might make it easier for a larger set of providers to come up with and at least make it easier to kind of see some of this because I think this is something that came out the book was that we, you need to be, you need to observe this, but it's often quite difficult to get the underlying numbers from some providers, and this is something that we need a bit, we need some more work with, or we need some progress on, basically.

Sarah Hsu: Yeah. And I guess one big thing about OpenTelemetry is that it, because it is just a framework and it's vendor neutral, I think sometimes people forget how important staying vendor neutral is. So yeah, I think that's why it's so important that we locked in with OpenTelemetry now, because it is going to be the solutions for this observability space going forward.

Sara Bergman: Absolutely agree, because I think sometimes when people talk about software, they think of a specific type of software that runs in the public cloud. But that is not the entirety of software that exists out there. There's so much software who runs on different places and nowhere near the cloud. And that software is equally, equally important.

So, having something that fits more than just the one most popular scenario is incredibly important. And, and I just want to say that, I think this is important because I don't think anyone should get away, quote unquote, from doing sustainability work because, oh, I don't know my number. That should not be an excuse.

Anne Currie: No, I totally agree. But, but even if it's impossible to get your number, there's still so much you can do without the numbers. as well. And yeah, it's amazing how people go, "Oh, I can't get the numbers to get" well, just work on your operational efficiency.

Sarah Hsu: Yeah. Yeah. And like one of the biggest takeaway I gave at the CamundaCon in Berlin was that you can think of BinOps as a really natural evolution of DevOps and FinOps. FinOps is the optimization with money. We basically need to do the same for sustainability. And there are so many things we already can do and yeah, people should really pack themselves on their back because they didn't realize the transition is going to be much smoother than they thought.

I

Chris Adams: Okay, I'm glad you mentioned FinOps actually, Sarah, because this is talking about OpenTelemetry, some ways to expose some of the figures into this. As I understand it, there is a is it focus, which is the standard that the FinOps groups are pushing for trying to come up with like standardized cost, cloud cost figures, because I understand, as I understand it, there are some people pushing to put some CO2 figures in those as well, so that you'd be able to get some of these ideas from not just billing, but also from operational figures.

So, because in some cases, one view will give you a slightly different view than the other, for example. We've got this, and we're just moving to the last of the stories that we have today. One of the largest providers has published their sustainability report. Microsoft published their 2024 environmental sustainability report in the last week or so, and there's a lot in it, actually.

So, they're one of the large providers, and they have various commitments about getting to net zero by a certain times, but there's actually quite an interesting amount of data for the nerds inside this. Sara, I might hand over to you, because I suspect that you've been poring over this in quite a lot of detail, actually.

Sara Bergman: Thank you. Yeah, I think I love it when this report comes out every year, because even though I work for Microsoft, there's no way I can keep up with everything that's Like, it's just too big. So I always learn so much. But I think for me, I'm a measurement geek, in case that wasn't obvious already.

So some of the things I thought was super interesting was firstly, that the PUE of the data centers was published. I don't think Microsoft has ever published that number, but they said that this year, the design rating of the new data center is 1,12. And I think that's pretty impressive. That's pretty close to 1, which is, you know, the dream where all the energy that goes in goes to actual compute and to know other resources.

Chris Adams: I'm glad you mentioned this, because I wanted you to actually just, for folks who are not familiar with what PUE means, maybe you could just, like, expand on that a little bit, and say why people, why you might even care about that number being high or low, for example.

Sara Bergman: Yeah, absolutely. So P U E stands for power usage effectiveness. Or if, yeah, effectiveness. Yeah. I always mix up the E words. Power usage effectiveness. And I think in the sort of early days of green software, this was the number people spent a lot of time focusing on. It is a number that's higher than 1.

So it measures all the power that goes into your data centers and how much goes to actual compute. If, if all the energy or all the power that goes into your data center goes to meaningful compute operations, your PUE = 1. Only half of what goes into the data center goes to actual useful compute.

Then your PUE number is 2.

Chris Adams: I see.

Sara Bergman: There's been a race to get to one, where you waste basically as little power as possible.

Chris Adams: And when you say little power, you're talking about, like, keeping the machine from overheating and melting, or stuff like that, right? Like keeping cool enough?

Sara Bergman: Yeah, cooling is one thing that consumes a lot of extra power. It's probably the biggest consumption of power, but they're like, they're lighting in the data center also, that's also consumes power. So anything that's in there that doesn't contribute to compute, go into this rate.

Chris Adams: Do servers need to see? I mean, they don't need to be in

the, like, it's not like they have

Sara Bergman: there people who work there.

Chris Adams: Okay, that's fair enough. Okay, so this is, so in this report, they're publishing this information, which has traditionally been a thing that you do not see, all right?

That's one of the key things from this.

Sara Bergman: exactly. And I thought that was interesting. And in the sort of early days of green software, this was a number of people obsessed a bit about because I think there was like this, I don't want to say miscomprehension, but this notion, at least, that if you just got the PUE to 1, all the problems would be solved, like, magically, everything would be so efficient that we would not have to care about everything else.

People were, like, hyper focused on data center design. And I'm not saying it doesn't matter. Of course it matters. Of course it's important. But it's an area where, over time, we paid down massive knowledge and spend time on. And in the end, that's only one side, because if whatever compute operations you run are vastly inefficient in themselves, it doesn't matter if all the power going in goes to compute if the compute is wasteful in its matter.

So it is one part of the puzzle, but it is not the most important. But I'm glad to see it getting so close to one. I think it was very impressive.

Chris Adams: Yeah, this is interesting to see this because there's a project called Realtime Cloud which is run inside the Green Software Foundation and one of the key things that people are looking to do is figure out the PUE for all the different regions from all the different cloud providers right now. And they've got a carbon intensity figures for each hour of compute. But now they're able to use, because there's this information published at a data center level or actually a region level, you've got a level of transparency that you don't see from the other two so far. I think. Google might be sharing some of this, but we still have a kind of like patchy spreadsheet listing this stuff.

What I'll do is I'll share a link to the spreadsheet for this, because this is one of the things that once you have this, that should allow you to start being able to kind of optimise what the carbon intensity and of the compute you're using based on these kinds of figures here. This doesn't touch everything though, and I wanted to just leave the floor open. And Sarah, is there anything that caught your eyes on this, because there is more to this report than just PUE, for example.

Sarah Hsu: Don't want to be the bearer of bad news, though, although I remember hearing this from Anne, so I'm just their messenger. I'm not the bearer. I remember you and Anne mentioned that because PUE has got a lot of branding around it at the moment, and people know that it's like the sort of like the efficiency factor for a data center.

So like people then don't want PUE to go up, even though they need cooling. So they end up using water to do the cooling. So they actually trying to get PUE to as little as possible, closer to one as possible as Sara mentioned, but then they compensate that with using water and water is another like sources that's just as sacred.

Is that how you say that word? Yeah. But anyway, I will like, and talk about this because I remember I heard this from you.

Anne Currie: Yeah, no, as you say, we do fetishize PUE a little bit. It's a measurement and everybody loves to meet it. But the other thing is it's not a carbon aware measurement because it's just a flat number. So it doesn't say, "Oh, well, actually, you know, this is what we did when the sun, when the carbon intensity of the grid was high.

And this is what we did when the carbon intensity of the grid was low." And actually you want, we need behavior to change. Between those two, two times. So it's nice, you know, it tells us something, but we need to make sure we, with all things, you know, it's context specific. We, it doesn't provide a lot of context and we might need more context.

Well, we will need more context in the future.

Chris Adams: Okay, so better than nothing. So two cheers rather than three cheers. So good to see this. But as Sara mentioned, I believe the technical term is impact transfer when you go from one factor like energy to impacting water, for example. And in some places, you may be, you may have data centers sited in regions of water stress or pulling power from like local aquifers and things like that. If that's used for drinking water or agriculture or things like that, that's not really ideal. But there's a big discussion about what happens with this water. In some cases, it might be, I think the term is withdrawn and waste and consumed. So you have water that might be taken in and some of it might be discharged, given back.

But if it's at a different temperature, that might not be ideal for fish. And stuff like that. Or if it's consumed and like just evaporated away, that's not ideal either. So there is a whole bunch here. And maybe this is one of the things we need, we should be hoping to see, or we should be looking to see more of. There's, okay, if we've got data center level PUEs, should we be thinking about water of usage effectiveness and other things like that?

Sarah Hsu: I think there's one, I don't know what to call them, but I know they're called Scaleway. And I think you did a thing for them that they, I think now they have like a landing page where you can see the PUE and the WUE. So I think people are start doing it, but again, like much smaller scale provider instead of like cloud providers,

Chris Adams: I'm really glad you mentioned this actually, Sarah. So, the thing you're referring to, we'll share a link to this. So, Scaleway, they're basically one of the largest cloud providers in France, and they also operate in a number of other countries, but they basically do have these dashboards. But the thing that's, the thing about these dashboards, they were initially created by by Facebook in 2014. So there is nothing stopping every data center exposing these numbers from a technical point of view. And like, if you're looking at a policy level, what they have there is totally something that could be done. It's something that we could be seeing if people chose to be disclosing some of that. And we might see some of this come out as a result of new laws that may be landing or that have already landed in some countries.

For example, Germany has this. But there are more on the horizon, actually. Anything to add from there, perhaps, Anne, you're about to just say something, yeah.

Anne Currie: I am. So, so Scaleway, I think it's kind of related to stuff we talked about earlier. I was on this podcast with Scaleway where I learned a lot of stuff about what they were up to. And there's some interesting things that they're doing totally away from PUE and WUE reporting. So, in Europe, there's a group called the SDIA, which is an acronym.

I can never remember what it stands for.

Chris Adams: Sustainable Digital Infrastructure Alliance,

Anne Currie: Excellent. And their raison d'etre is to try and get European data, non hypercloud data centers to start learning from the American hyperclouds and actually delivering some of those services. And one of the, one of the things they're pushing for is actually starting to orchestrate and offer services on your data centers that will provide operational efficiency and code efficiency in the same way that the hyperscalers do. And that generally, you know, your bog standard data centers don't. And that's a really, that's a really bad thing about bog standard data centers.

They don't do this because it's very hard to do. If you can get your data center to provide it, then that makes life much easier. And interesting, on the podcast that I was on with Scaleway, they had a, one of their engineers on who was working on their serverless offering. So a bit like Wasm we were talking about earlier, services that improve operational efficiency and code efficiency provided through your data center. That's what we want. That's where the cloud is good with being, is potentially green, but only if you adopt them. And all these things, if you just lift and shift into the cloud, if you lift and shift into good data centers like Scaleway, you don't get any benefit really, or don't get much benefit.

You need to be moving over to efficient services.

Sara Bergman: Yeah. And I think that was another thing that Microsoft mentioned in the sustainability report that they are working on several ways to increase resource utilization. And just to mention too, they have these power aware workload allocations, and they're also like smartly allocating CPU cores for internal workloads.

Because don't forget Microsoft is also a software provider, not just a cloud provider. And I thought that was really good that they called out because sometimes when we say things like this, yeah, the hyperscalers are good at this, people question it, like, "oh, is it really worth their time?" So I thought it was good to see them calling out specific things that they're doing that can also hopefully inspire others to do the same with their data centers.

Chris Adams: So here's one question I have there about this report. So, yes, it's very good that you see some transparency here. And yes, there are definitely cases where moving to the cloud can be more, can be greater. But we've seen, both Microsoft and Google and Amazon, their emissions climb. Year on year. And this year, we're seeing emissions 30 percent higher this year than last year, which is not going to make it easy to get to net zero.

And this is one of the key things that Microsoft themselves have been talking about, saying, yes, this is a real challenge for us, and a significant chunk of our emissions are in our supply chain. Scope 3 is the largest source. So this is one thing that I think that it's, it feels like when we're talking about this, green software doesn't really have that much to say about right now in terms of the actual creation of data centers. And this is something that I kind of want to open the floor up, like how do we actually deal with this fact that things can be more efficient, but still growing in absolute terms? Is this something that we can be doing or do we need to be having discussions about absolute resource limits, for example, and things like this, or how are we going to get here? I'm going to hand to Anne because you've got something, but you're about to say something I think.

Anne Currie: I am always about to say something. I think this is a really, the whole, the whole thing of, you know, the degrowth, people shouldn't be allowed to, we shouldn't ban people from doing things, it's a very unpopular argument and it is why people, you know, are not, even though everybody now believes in climate change, they don't want to have to give up all the things they want in life.

Now, efficiency can often really deliver you the same standard or less. I mean, it's not all, I mean, Jevons paradox, we all know about Jevons paradox. The Jevons paradox is you, you, things become more efficient and where there's untapped demand, where people really wanted to use them and they couldn't previously because they were too expensive and now they can.

That's a, that's actually, that's a big improvement in life. But it's not a guaranteed lock in. Everything that you make more efficient doesn't always result in overall there being more usage. So we use a lot less electricity to run household appliances now than we used to. They've become more efficient and there is only a certain number of times that you can wash the dishes with the dishwasher or wash, you know.

At some point, demand does become

Chris Adams: there's an upper limit to how often I want to vacuum my room, for example. Yeah,

Anne Currie: me, it's quite a low number of times I want to vacuum my room. I'm more worried about things like Bitcoin, where there is no upper limit. I mean, so what worries me about things like Bitcoin is there is no, literally no upper limit to how much you might want to do it.

There is no, there's no point at which you go, "Oh, do you know, I'm happy now, I've just done all the things I wanted it to do." So with those things, where there's no upper limit, I think. And they potentially don't have a great deal of benefit for most of society. We might want to go down the China route and start banning them.

But for things where eventually our upper limit will be reached and they are providing societal value, I'm minded to let them grow a bit, at least. I don't know. I don't know what everybody else thinks.

Chris Adams: No, this is actually, this is, you're right, this is a complicated question to deal with, and this is one of the things that we, one of the things that's probably bigger than green software that we need to be aware of when we talk about this, because if we make things more efficient, then we've got to figure out, okay, what's the flip side of this, like you mentioned with Jevon's paradox? We do have an episode with Vlad Kouraoume, where we dive deeply into this if you're interested in listening, and we'll share a link to that. There's a number of other things we might want to talk about for this, but what we'll do is we'll share a link to the report so that there's plenty for us to be discussing. All right, I think that takes us to the stories that we do actually have. We're coming up to time. Folks, I want to say thank you so much for kind of coming onto this. If people were curious about these terms that we've been using, like operation efficiency, coding efficiency, things like that, this is what's outlined in the book that you three have been working on.

Is that correct?

Anne Currie: It is indeed. Yes. Building Green Software, the new book from O'Reilly.

Chris Adams: Anne, there's one question I want to ask because we spoke about this a few months ago. So this is currently available right now, and you can get it via O'Reilly, but there was a discussion about this actually going. Available into the commons eventually. Is there one thing we could just touch on some of that, because this is a really cool thing about this that I was really excited to hear about when you first shared this with me, Anne.

Anne Currie: Like, I feel terrible about this because this is, we just haven't had time to do it. 'Cause we're crazily busy. We've got to take the code, but we, we do have a license. We negotiated, O'Reilly very kindly allowed us to make it available under the O'Reilly Creative Commons license, which is a, a kind of read only license, but totally that's, that's still absolutely fine.

That's great. And so we just need to do it, but we haven't got around to doing it yet. Cause we have to do some tidying up and actually publish the thing, but it will at some point be available under a Creative Commons license.

Chris Adams: Cool, alright, brilliant. Well, thank you for that, Anne. Well, folks, this takes us to time. If people do want to find out about, if they're interested in what you have to say, or what you've been looking at, folks, are there any maybe just do a quick whip round of where people should be looking. Anne, if I hand it over to you first, then to the Saras. Anne, if someone has listened to you and they want to find out more about what you're up to, is there a website you direct people to or a network or anything?

Anne Currie: If you want to find out more about me, then LinkedIn is where I tend to hang out these days, and I'm very happy to chat to people and answer questions. And/or our website strategically.green will give us an idea, and I do an awful lot of public training as well, so you can always sign up for that.

Chris Adams: Brilliant. Thank you for that, Anne. And I'm going to go for Sarah with an H, if that's okay. So where should people, if they want to learn about your things, or maybe hear about your talk, where should, where should they be looking?

Sarah Hsu: Similarly, LinkedIn, I call LinkedIn the grownup version of Instagram,

Chris Adams: Yeah.

Sarah Hsu: but yeah, LinkedIn and yeah, I do fair bit of public speaking. So if you're ever catch us or catch one of us, don't forget to come get the book signed and because it's such fun, who can get to collect all three signatures. Because we are never in the same place once.

Anne Currie: We're never in the same

Chris Adams: Okay, sara, and over to you. If people want to find out some of the work you're working on or things, where would you direct people's attention to?

Sara Bergman: Yeah, I'm also on grown up Instagram, aka LinkedIn,

Chris Adams: Yeah.

Sara Bergman: but follow me, don't send me a friend request because I'm terrible, or what's it called, a contact request maybe, because I've not been good at accepting or rejecting people, so now it's an uncomfortable list and I just ignore it, it's a red flag with me.

So yeah, you can follow me and that that's the best way probably. And yeah, I'm speaking at NDC Oslo in about, yeah, in June. So if you have the book, come and get it signed. It will be lovely to meet folks. I also have a few copies that I can hand out if anyone catches me. h

Chris Adams: Ohere., exciting. Thank you for sharing that little one. All right, then. Well, folks, it sounds like I guess we'll see if people want to follow what you're up to. Millennial Twitter, LinkedIn is the place to go to. All right. What we'll do, if you have any of this interesting, folks, we are going to, and if you're listening to this for the first time, we'll be sharing the show notes with all the links to the projects that we've mentioned here, along with some of the other episodes where we touch on some of the things like Jevon's paradox, or some of the finer points of serverless. All right, folks, this has been fun. Thank you so much for giving us the time and,yeah, have a lovely day, folks. See you around, all right?

Anne Currie: Cheerio everybody. Bye

Sarah Hsu: Bye guys. Lovely seeing you

Sara Bergman: Thank you. Bye.

Chris Adams: Hey everyone, thanks for listening! Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundationon. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode!

View Details

Join us for a special episode of Environment Variables as we celebrate over a year two years of bringing you the best insights on Green Software! In this episode, we explore the key insights and voices that have contributed to the weaving of sustainability through our conversations this year. Tune in for a refresher on the most interesting discussions on the progress, challenges, and future of green software development.

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

Episodes:* The Week in Green Software: AWS & Scope 3 Emissions Data | Ep 27 * Fact Check: Colleen Josephson, Miguel Ponce de Leon & AI Optimization of the Environmental Impact of Software | Ep 29 * The State of Green Software Survey with Tamara Kneese | Ep32 * We Answer Your Questions Part 2 | Ep 39 * Sci-Fi Fantasies with Anne Currie and Jo-Lindsay Walton | Ep 42 * The Week in Green Software: New Research Horizons | Ep 47 * Decarbonize Software 2023: Recap | Ep 53 * The Week in Green Software: Google, Grids & Green Software | Ep 55 * BETA Impact Framework | Ep 58 * AI Legislation | Ep 63

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
Chris Skipper: Hello and welcome to this special Year 2 Roundup episode of Environment Variables. I'm Chris Skipper, the producer behind the scenes. As we mark the second anniversary of this podcast, it's a perfect moment to reflect on the journey we've undertaken with the Green Software Foundation over the last year, and how that has been encapsulated through our episodes.

From its inception, Environment Variables has aimed to be more than just a podcast. It's a platform for advocacy and education on sustainable software practices. Over the past year, We've seen the Green Software Foundation grow and evolve, and we've been right there to document and discuss each milestone.

This podcast has not only followed the foundation's developments, but also mirrored the broader shifts towards sustainability and tech, bringing these insights right to your ears. Today, rather than revisiting our top episodes, we will explore how the themes of sustainability have woven through our discussions.

Highlighting key insights and the impactful voices that have contributed to this dialogue. You'll hear about the progress, the challenges, and what lies ahead for green software development. For your listening pleasure, as always, links to each of the episodes will be down in the show notes below. Or, if you want to listen to all of the episodes of Environment Variables, you can head to podcast.greensoftware.foundation, preferably after this episode, please, to hear them all. So, without further ado, let's dive into the collective journey of the past year with Environment Variables.Chris Skipper: To kick us off, let's start off with an episode of one of our segments entitled the week in green software, or as we like to call it twigs,

This segment delivers a concentrated blast of the latest in green software news, keeping our listeners informed and engaged with current trends and advancements in the field.

In fact, it's a nice touch that this episode covers AWS and Scope3 emissions data, as the very first episode of Environment Variables way back in April of 2022 also covered Amazon's Customer Carbon Footprint tool. In this snippet, our host Chris Adams discusses a fundamental concept in environmental accountability, the Greenhouse Gas Protocol, which is the de facto standard for measuring the carbon footprint of any organization or activity.

Chris breaks down this somewhat complex subject using a relatable analogy involving coffee, explaining the three scopes of emissions. He uses everyday examples to illustrate Scope 1, Scope 2, and Scope 3 emissions, making it accessible for both newcomers and seasoned professionals, which has often become the role of twigs.

This approach not only simplifies the understanding of these emissions, but also highlights the significant impact of Scope 3 emissions, which often constitute the majority of an organization's environmental impact. Let's listen to Chris explain this in more detail.

Chris Adams: So I'll just quickly, for those who are new to the subject or folks who have never heard of GHG, the greenhouse gas protocol, essentially, this is a way, the kind of de facto standard for measuring the carbon footprint of any organization or any activity. And you typically split it into three kind of buckets of emissions.

And because we're nerds or developers and drink coffee, we can use hot beverages as the mechanism for understanding the difference between scope one, two, and three. You can think of scope one, which is from combusting fossil fuel. That's a bit like turning on gas to heat up water so you can have a nice cup of coffee, right?

Scope two, it's like turning on an electric kettle. So someone is setting fire to something to heat up some water somewhere to generate electricity so that you can heat up a kettle. So it's all the emissions associated.

Scope 3 is a bit like walking into a Starbucks or a Third Wave coffee shop and then buying a cup of coffee. So you're not involved in actually farming beans or burning anything, but there is definitely a supply chain associated so that you can have coffee. So these are the three kinds of scopes. And typically, Scope 1 and 2 are quite the common ones that organizations tend to report on, but for these, for lots and lots of organizations, scope 3 can make up 80 percent plus of the environmental impact.

And this is why we've been talking about it as being quite a big deal because if you do not have 80 percent of your reported numbers, they may look somewhat different to the other providers.

Chris Skipper: In the past year, Environment Variables has also introduced a new segment called Fact Check. This segment focuses on verifying claims and clarifying misconceptions related to the environmental impact of technology, providing our listeners with accurate and actionable information. In episode 29, Host Chris Adams discusses the role of artificial intelligence in optimizing the environmental impact of software.

He is joined by experts Colleen Josephson and Miguel Ponce de Leon from VMware, who delve into the intricacies of sustainability in virtualization and networking, as well as VMware's internal efforts towards decarbonization. In the snippet we're about to hear, Colleen Josephson highlights the challenges associated with training AI models in the telecommunications sector, a field where VMware has significant expertise.

She points out the substantial energy required to train these models and raises critical questions about the energy savings versus the environmental cost of AI, emphasizing the importance of evaluating the longevity and efficiency of AI models before committing resources. Let's listen to Colleen Josephson.

Explain these complex trade offs.

Colleen Josephson: Training is a very expensive process nowadays. Whether it's in the telco space, because, again, VMware, as you hinted, we have a long history of virtualization and cloud, but that also has become very relevant to telecommunications. We need to train the models that we use to make these decisions to try and save energy.

And the process of having so much data and training it, it can be really power consuming. So I think one of the things that stands out to me is, what is your anticipated energy savings? savings. Once you've deployed this model, how long do you anticipate that this model will be good for? And do you need to retrain it?

All of those you want to have some idea of so that you can calculate whether or not it was worth the energy to train this model in the first place.

Chris Skipper: Continuing the insightful discussion on the role of technology in environmental sustainability, we turn to Miguel Ponce de Leon, who shares his experience working on a collaborative project in Ireland. This initiative, a partnership between VMware and a local grid utility hosting a data center, focuses on integrating measurements from renewable energy sources directly into data center operations.

This effort not only enhances the understanding of energy usage within the data center. but also promotes actionable strategies for optimizing energy efficiency. Let's hear Miguel elaborate on how this collaboration helps data center operators become better environmental stewards by enabling precise monitoring and proactive management of resources.

Miguel Ponce de Leon: So one of the things I can mention is that we are working with a grid utility in Ireland and with that grid utility that also hosts a data center if that so happens. We're also working with an accelerator program, a program that is helping startups to look at how you can not just link but actually be able to take the correct measurements from the green sources, the wind farm locations, and the usage within the data center for its performance.

So, again, here it's about leveraging not just the research, we'd say, that would come from research performing organizations or from the offices of CTO of VMware, but also looking at start ups and start ups within the space and being able to link this. And that is helping the utilities. understand what type of usage, and imagine it's a utility that has their own data center.

So it's helping them be a good citizen even within their own environment, but being able to measure it and then being able to take action on it, right? Because that's the important thing is, okay, you've got your baseline, but what can I change about what I'm delivering within that data center? Even down to the containers, how can I move my clusters and pods over and maybe consolidate some of the pods?

We're even moving some of that research as well to look even with the pods. It's been available. How many of the CPUs are they using within the cluster? So again, it's about being able to help data center owners being good citizens around that space.

Chris Skipper: This next snippet comes from episode 32, which was all about the State of Green Software Survey, with lead researcher at the GSF, Tamara Kneese. The State of Green Software Survey serves as a political resource for the Green Software Foundation, offering crucial insights into the involving landscape of sustainable software practices.

By highlighting trends like the carbon footprint of crypto mining and the need for stringent regulations for generative AI, the report informs and influences stakeholders across the tech industry, from developers to policy makers.

In this snippet, Tamara emphasizes the report's role in enhancing the visibility of green software initiatives.

Tamara Kneese: So one of the main goals was really to raise the profile of green software. And I was really interested to see the percentage of developers who actually had some degree of awareness of green software. And so it makes sense that a lot of the people who filled out our survey already were somewhat aware of it.

and already interested. Although there were a number of people who replied in the comments that this was the very first time they'd been exposed to green software. And so by putting out this public report that can be taken up by the press, that can be taken up by policy makers, that can be taken up by academic researchers, it is a way of really getting the word out about green software.

Thinking about the reporting Court as a mechanism for evangelizing green software is really part of what we wanted to do. And we also wanted to understand after knowing that 92% of developers who surveyed said that they were concerned about climate change and wanna do something about it. So what do they need to actually make that happen?

What resources, tools. and other forms of support do they need to take action. And another key element of this is reaching out to ICT industry leaders to the C suite who really want to know how and why they should make green software part of their organization. And really trying to emphasize the business case for green software from their perspective was another really key part of this survey.

Chris Skipper: As we continue to look back on the previous year's journey, our next segment brings you insights from the Green Software Foundation's HotCarbon event, which took place on World Environment Day, June 5th, 2023. In episode 39, host Chris Adams, alongside Executive Director of the Green Software Foundation, Asim Hussain, Delved deep into a mailbag session, addressing questions that remained from this engaging live virtual event.

Their discussion begins with a look at the challenges of quantifying energy consumed by various computer components in the software carbon intensity specification, and transitions into real world applications of measuring SCI and CI/CD pipelines. The efficiency of GPUs and innovative uses of data center cooling water.

In our first snippet, Asim highlights a memorable talk from the previous year's Hot Carbon event, emphasizing the critical role of green software in managing the burgeoning demands on cloud infrastructure without the need to expand physical resources. Let's hear Asim explain this further.

Asim Hussain: It shows how important the work that we're talking about is. It's like, actually, it's one of the really great talks from last year's HotCarbon, which I loved, which was, I've forgotten, I've got to apologize, I'm not going to remember which one it was, but it was talking about how projecting forward kind of compute growth and how green software was a way of being able to handle the additional usage and load of the cloud without actually having to build more servers.

Because fundamentally we are constrained at the rate with which we can actually increase the cloud. But the growth is growing significantly as well. So like being more efficient actually allows you to, to deal with growth. So I think that sounds like what you're describing. So you have to be green, you have to use green software if you want a realistic chance of generative AI being as ubiquitous as you want it to be.

Chris Skipper: In this second snippet from Asim, he emphasizes the importance of broadening the dialogue beyond carbon to include other critical resources like water, acknowledging that managing environmental impacts often involves navigating trade offs between different sustainability goals. Let's listen to that now.

Asim Hussain: There might be situations where it's mutually the opposite, being more carbon efficient might actually make you more water intensive. Like for instance, doing things that reduce carbon emissions might require more water consumption, which is why I think it's exciting that we're actually are starting to have this conversation right now because I think we're so focused on carbon.

And we're optimizing for carbon, but actually the landscape is much more complicated. It's much more of a surface where you're trying to minimize the environmental impacts of your choices, and you might have to make trade offs versus one versus the other. If there's a water scarcity right now, you might have to increase your carbon emissions.

I'm excited that this is where the conversation is evolving to, because once we add water to the mix, we can add other things.

Chris Skipper: As we continue our exploration, our next episode takes a fascinating leap and dared to go where no podcast, or at least this podcast, had gone before, into the realm of science fiction and its role in envisioning a green future. In episode 42, host Anne Currie is joined by Joe Lindsay Walton, a research fellow in Arts, Climate and Technology at the University of Sussex.

Together, they delve into the imaginative horizons that science fiction opens for tackling climate change, the practical application of these ideas to green software, and the impact of speculative futures on our environmental strategies. In this snippet, Joe Lindsay Walton questions who really holds the reins in crafting a global strategy against climate change.

Let's listen to Joe's interesting take.

Jo Lindsay Walton: Are these orbital data storage facilities, are they going to Out compete the earthbound data centers that are using the dirty energy. Who actually holds the big picture of global strategy here, of addressing the urgent issue of climate change? Is it the conference of parties? Kind of, but they're mired in all these geopolitical rivalries.

Is it the scientists? The IPC? Yes, but they're constrained by the remit of political neutrality and face challenges around communication. Is it the finance and markets? They're waking up to something. They're trying to incorporate climate into these risk management methodologies that they don't really play all that nicely with.

Is it science fiction? Yes, we're drawing in a really interdisciplinary way. We've talked about Kim Stanley Robinson throwing everything at climate change, but it is ultimately a story. I'm not really sure who does hold the big picture. And if I was to try and summarize it in a crude way, it seems that we're hoping to adjust the rules of the game.

We haven't even adjusted them yet, but we're hoping to adjust the rules of the game so that Goods and services and enterprises and value chains and industries and sectors and whole communities and regions that are incompatible with a broadly livable planet are going to be destroyed in the Schumpeterian whirlwind of creative destruction, will crash and burn.

And I think there's a lot of emphasis. on the creation side of that, building data centers on the moon or in orbit, but not enough imaginative, creative, realistic thinking about the destruction side of it. There's this expectation that enterprises are going to snitch on themselves. Oh, we've tested for impairment.

We're reporting against this particular standard. All our assets are stranded. We're just going to shut up shop. Goodbye. So I think I would be interested in more science fictional Thinking about the potential pain of switching from carbon intensive activities to the sustainable ones. Not just the focus on the kind of shiny new possibilities, but also the focus on what it's like to shut up shop.

Chris Skipper: Environment Variables also dared to break boundaries on the academic front. Our next snippet comes from episode 47, titled, New Research Horizons, which takes us to the forefront of innovation in green software. Host Chris Adams is joined by Dr. Daniel Sheehan from the University of Bristol to delve into the evolving landscape of digital sustainability.

Their discussion spans from the implications of historical studies to the transformative potential of recent research, offering listeners insights into how new findings are reshaping our approach to sustainability in technology. In this snippet, Daniel discusses the nuances of energy consumption across different media delivery platforms, emphasizing the complexities in interpreting data that could potentially mislead consumers about the energy impacts of their viewing choices.

Daniel Schien: The academic publication that I'm sure you will link to it in the show notes. There's a graph that compares the energy intensity of those four different modes of delivery of television from the BC. So IP, cable, satellite, and terrestrial. And even though they, they differ. So between, if I remember correctly, between 60 watt hours to 180 watt hours, that's in the year 2016, there's a potential step in the interpretation of those results that consumers might take, that needs more support.

If you see this graph, you might I think as a consumer, if I change from streaming to watching something via terrestrial broadcast, I am going to save 100 watt hours per viewer hour. However, that would not be a correct interpretation because all of those delivery modes, they are provided by an infrastructure that is inherently inelastic in its energy consumption.

Chris Skipper: Jumping to November and Decarbonize Software 2023, an essential event for the Green Software Foundation took place. This annual gathering is crucial for those passionate about reducing the environmental impact of software. Bringing together experts, practitioners, and innovators worldwide to exchange insights, breakthroughs, and strategies for sustainable software development.

With COP28 kicking off on the 30th of November in Dubai, we wanted to highlight projects which are driving momentum towards a low emission and climate resilient world. At COP28, global leaders discussed how to reduce global greenhouse gas emissions by 43 percent by 2030.

In sync with this ambitious goal, Decarbonize Software served as a vibrant forum to promote collective action and shared knowledge. in our pursuit of greener software practices at the forefront of climate action. In episode 53, I was joined by Sophie Trinder and Adam Jackson of the GSF to give a rundown of what happened.

In this next snippet, Sophie gives a rundown of one talk from the event titled Responsible AI, a fireside chat in which Jesse Mccrosky, Head of Sustainability and Social Change at ThoughtWorks, talked about integrating real time environmental impact metrics into our everyday software tools.

Sophie Trinder: Jesse painted this hypothetical picture. What if there was a carbon counter or there was a water gallons clock at the top of ChatGPT? Would you use it differently? Would you only use it when it was essential? Maybe you would write shorter prompts? Would you ask it to write its answers briefer? Similarly, he painted another picture where, what if a software developer's screen went red?

If the developer made a decision that, yeah, might make them save some time, might make them slightly more efficient, but what if it came with a huge carbon cost? So their screen went bright red when there was a carbon cost associated with the code that they were writing. I think it was just a really interesting way to Start thinking about being more transparent with that data so that we can be more conscious with our decision making.

Chris Skipper: Continuing our dive into the impactful insights from Decarbonize Software 2023, next we'll hear from Adam Jackson. In this snippet, Adam eloquently draws parallels between well crafted software and green software, emphasizing the necessity of built in quality throughout the entire software lifecycle.

Let's listen to how Adam articulates the holistic approach needed to integrate sustainability into software development.

Adam Jackson: I often tell folks when they ask me what green software actually is, that there's a lot of parallels with well crafted software. So well crafted software like green software focuses on built in quality throughout the complete software life cycles and architecture, development, operations, and getting all of the stakeholders together to take responsibility.

And we need the same thing for green software. So at the GSF, we often talk about software practitioners. And this is a broad term that goes beyond developers alone. It includes product managers, uh, program managers, designers, UX, testers, IT operations. And what takes the time, and GSF does have some materials that can help here, is developing the best practice, the processes, and the learnings that bring all of these people together.

into a really holistic software life cycle and I think that's why we're really keen to get organizations to hear and listen to others even if they're competitors. What's the best practice that we can all share that's gonna deliver green outcomes?

Chris Skipper: Transitioning now to our next insightful episode of The Week in Green Software, we delve into the pioneering sustainability strategies at one of the tech world's giants and GSF member, Google. In episode 55, Chris Adams is joined by Savannah Goodman from Google.

Who shares the ambitious climate goals set by the company. Google aims to achieve net zero emissions by 2030 and to operate on 24 7 carbon free energy by the same year. Savannah explains the complexity of moving from annual global matching to local hourly matching of energy use. illustrating the innovative approaches Google is deploying to meet these goals.

This episode not only highlights Google's efforts, but also discusses broader implications for the tech industry's push towards a more sustainable future. Let's hear from Savannah on how Google is tackling these ambitious targets.

Savannah Goodman: Google has two main climate goals. One of them is to be net zero by 2030. The other is to be running on 24 7 carbon free energy by 2030. And just to clarify too, 24 7 carbon free energy is much more complex. And I'm going to talk to you about how we've been able to make this a little bit more complex than the annual matching schemes that have been most common to date, because we're essentially moving from global annual matching to local hourly matching.

And so you can imagine how, especially over a global system, how complex that is. And there's no playbook, but we see these goals as a way to actually help scale new global solutions that drive broader system wide decarbonization because we're actually aligning our own goals with what the grid

Needs.

Chris Skipper: Next, we focus on episode 58 that dives deep into the Green Software Foundation's impact framework, probably the biggest highlight of the previous year. Host Asim Hussain is joined by Srini Rakanathan and Naveen Balani. who are at the forefront of developing this transformative tool. They discuss the challenges and solutions in creating a framework versatile enough to assess the environmental impact of software across various platforms, from large cloud providers to personal devices.

This conversation sheds light on the critical need for standardized models that can adapt to different environments without compromising on maintenance and adoption. Listen in as Srini shares Insights into the decision to implement model plugins for more effective integration and broader applicability in green software efforts.

Srini Rakhunathan: With the original concept that we had, where we wanted to cover all, we would have had to build multiple flavors of the impact framework. And that would have caused issues in maintenance, that would have caused issues in adoption. I think the standardization of a model plug in was more important. a decision that we took once we realized that one model is not going to cut the cake for all of us and you had different models depending on whether you are hosting it on AWS or Azure or GCP or your laptop or even your mobile devices.

But if someone wants to just look at the raw emissions from the software, agnostic of the hardware, you could do that only if you have a very thin measurement tools.

Chris Skipper: Finally, let's finish off on another episode of Twigs. In episode 63, we focus In episode 63, Chris Adams, Asim Hussain, and Anne Currie delve into the evolving landscape of AI legislation and its implications for green software. This first snippet from Asim highlights the accelerating integration of AI technologies and their significant energy demands, which could dramatically reshape global emission profiles by 2040.

Asim Hussain: The growth in AI has been significant. We all know on this call that the previous dirty secret of data centers where most of those servers were idle, in a future of AI, those chips are not going to be idle. They're going to be running at a hundred percent. So like, I think we've spoken on this call previously about, you know, various previous reports that talked about, you know, given the current trajectory by 2040, the tech sector will be like 14 percent of global emissions.

I wonder if anybody's doing any analysis. To revisit, well, now, given what we now know about the complete AI will take over everything. It is taking over everything right now. How does that look now? Where will we be in 2040 with the current growth in AI? Will tech be half of all emissions? And will we just be sitting there, you know, being carried around by robots and being fed by little tubes like that robot show?

But I think, I strongly suspect that they factor that in, and I wonder if it's an underestimate.

Chris Skipper: Our final snippet comes from Anne as she contemplates the future of green software practices.

Anne Currie: All discussion we're doing around this is great, fantastically great, but I always think about taking it back to my Maturity Matrix projects on the GSF Maturity Matrix project. You need to do different things at different times, so this information is useful to you in different things at different times of your journey.

So for most of us at the moment, we're not doing anything at all. Just, you know, you really don't need that much data. You know, your scope 1, scope 2, scope 3 are not immediately critical to most people who just need to turn off the machines they're not using anymore, do a bit of right sizing, have a think about what they're up to.

To start to think about, are they in green regions? What are the future, what platforms are they choosing? Are they likely to be aligned with the green future? To start with, where most of us are at the moment, you don't need a great deal of data to, to really make a huge difference. So it's absolutely fantastic that they're doing this work and that every, that we're doing this work.

Everybody's doing this work, but we don't want to lose sight of the fact that. For almost everybody at the moment, we don't even need data. We just need to start to, to use best operational practices.

Chris Skipper: What does the future hold for green software? Is it all doom and gloom? Absolutely not. The GSF is actively working on expanding its initiatives, pushing for widespread adoption of sustainable practices across the tech industry.

You can expect this podcast to bring you all the significant updates showcasing both the challenges and the innovative solutions that are making a real difference. Thank you for joining us on this look back on the last year of Environment Variables. Make sure to follow us on your preferred podcast platform to stay updated on all future episodes.

And don't forget to check out the show notes for links to further information discussed today. A final reminder. You can visit podcast.greensoftware.foundation to listen to more episodes of Environment Variables. See you all in the next episode. Bye for now!

View Details

Joining Chris Adams today is Mike Gifford, an accessibility and open web veteran, to look at the drivers adopting digital sustainability in the industry, learn from the field of accessibility and inclusive design how we can further sustainable software development. Mike tells us about the wins from the accessibility movement that we can learn from in this engaging episode.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Mike Gifford: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Web Content Accessibility Guidelines (WCAG) 2.2 [28:04] * https://w3c.github.io/sustyweb/drafts/star.html#considerations [42:44]

Resources:* FOSDEM 2024 - Web Accessibility and Environmental Sustainability and with Popular CMS [11:10] * https://github.com/GovTechSG/purple-a11y [36:23] * https://apolitical.co/solution-articles/en/keeping-tech-sustainable [47:42] * https://minumeco-99-preview.netlify.app/publications/ecodesign-framework/ * https://apolitical.co/solution-articles/en/keeping-tech-sustainable

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
Mike Gifford: Yeah. So that's an interesting approach to structure content so that you're hopefully trying to go off and encourage your, the organizations to push themselves to better understand their users and be able to build a website that meet the needs of their users.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams. Hello, and welcome to the Green Software Foundation podcast, Environment Variables, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. When we look at the drivers adopting digital sustainability, in industry. As much as we want to think people will build greener digital services out of the goodness of their own hearts, it's worth bearing in mind that in a commercial environment, other concerns frequently take precedence.

And if we want to see wider adoption of more sustainable practices in digital, a lot of the time we have to be somewhat strategic, learning from other fields, for example, and being thoughtful about how we spend the social and political capital we might have available to us. So where should we be looking for people who have done this before?

One commonly cited field is the field of accessibility and inclusive design, where over the last 20 years, we've seen accessibility move from a field where lone, heroic actions were the norm, to one where, in growing parts of the world, accessibility is a non-negotiable, mandatory requirement in new projects with the full force of the law behind it now.

So, are there wins from the accessibility movement that we can learn from to apply for digital sustainability? And where in the history of accessibility online should we be looking? With us today, we have Mike Gifford, an accessibility and open web veteran, to help us navigate these questions. Mike, thanks very much for joining.

Can I give you the floor to introduce yourself today?

Mike Gifford: Absolutely. I'm Mike Gifford. I'm a senior strategist at Civic Actions. I'm excited to be here. And this is, I'm definitely an active listener and I've really enjoyed all the. Discussions that have taken place from other leaders in this field. I'm also a Drupal core accessibility maintainer. Drupal runs about a million websites around the world.

And I've been trying to improve accessibility in that field. And increasingly trying to do work in sustainability there as well. At Civic Actions, I lead the accessibility practice area. I've also been involved in contributing to the W3C's sustainable web community groups, draft web sustainability guidelines.

That's a bit of a mouth mouthful, but it's essentially just a group of people within a standards body called the W3C that is trying to go off and create a set of best practices around sustainability, and I've also spearheaded the development of a tool called OpenACR. Which is a new way to try and help organize vendor claims around digital accessibility.

Chris Adams: Brilliant. Thank you for that. And for folks who are listening to this for the first time, we do have a podcast episode specifically with the W3C, some of the other members, we'll link to that in the show notes. If you're new to this podcast, my name is Chris Adams, as I mentioned before. I work at the Green Web Foundation. Foundation, where we are a Dutch nonprofit focused on reaching an entirely fossil-free internet by 2030. I also am one of the chairs of the Green Software Foundation's Policy Working Group, and one of the maintainers of a software library called CO2.js, which you can probably guess what that does from the name.

It makes it easy to work out the environmental impact of various digital services. Mike, before we start, I should ask, because when I have spoken to you before, I've generally assumed you're in Canada, but you mentioned you might not be, so first of all, where are you calling from, and how's the weather?

Mike Gifford: So I'm calling from outside of Carcassonne, France, and I've been here for just over five months and I've got another four months to go. My wife wanted to have a sabbatical between careers, and this was a good place for us to learn French and eat cheese, stumble across castles and explore the culture of Europe.

So that's why we're here. And the weather here generally has been really good, especially compared to Ottawa, but right now it really has been a cold, nasty week this week. And so it's not being very good and it'll actually be warmer in Ottawa later this week than it is here in, in, you know, outside of Carcassonne.

It's a lot of climate chaos is going on around the world. We're seeing it all over the place. It's inconsistent weather.

Chris Adams: Wow, I did not, realize that. I generally would assume that Ottawa and Carcassonne, I mean, they're more or less the same latitude, right? But they are definitely not the same temperature most of the time, and Ottawa's definitely colder normally, right?

Mike Gifford: Yes, absolutely. We can get down to minus 20, minus 30 Celsius in the winter. And in the summer we can get up to plus 30, sometimes 35 Celsius, but it's a, it's definitely, it gets much colder. It has a much heavier impact from the Arctic weather.

Chris Adams: Wow, so I guess, thank you Jetstream for the clement weather in Western Europe. Okay. Long may it stay, I suppose. Yeah. All right. So I think you're sitting comfortably. For folks who are listening, we have show notes, so we're going to mention various projects and we'll do our best to list every single project and website that we do.

So if you are listening along and you want to learn more about one of the things we have, please do check out the show notes at podcast.greensoftware.foundation for more. All right, then, Mike, sitting comfortably, I guess should we start, yeah? Okay, so I did this introduction talking a little bit about accessibility, but I didn't do a particularly good job of explaining what accessibility might be.

And I'm wondering, before we talk about sustainability, maybe you could just expand a little bit about what people tend to mean when they talk about accessibility in this context, because I think there are a few misconceptions that people tend to bring when they first hear about accessibility.

What is accessibility, and what are the kind of myths that we might want to think about that we should probably dispel?

Mike Gifford: First of all, people assume that accessibility is just for the blind and deaf community. Like this is who we're trying to go off and to meet. And there's just a small number of people who comply with that. Why do we need to really worry with this? This is just a, you know, a government overreach additional administration, but that's, it's actually not the case.

If you look at permanent disabilities, most countries in the Western world, a quarter of the population has some form of disability. That could be, and that's a permanent disability, so that could be somebody who's got low vision or no vision, people who have hearing problems, mobility problems, could be cognitive problems, people who have dyslexia, color blindness.

It's a whole range of different aspects. And I tend to think of it like just part of a human experience. Is it that, that when we're born, we have certain limitations and we grow up and we learn how to do things. And we have, you know, we have abilities that we have at this time. But they change over time, you know, when I have allergies, my eyesight isn't as good because I have blurry eyes because I've got allergies.

There's also situations where as we age, like as soon as you're over 40, your eyesight begins to degrade. Probably most people listening to this podcast have glasses. That's a form of assistive technology. If you didn't have glasses, you probably would, would have much more difficulty reading a book or reading a monitor or your phone for that matter.

There's also issues of, you know, temporary and situational disabilities. So if you're, if you're injured, for example, where you're carrying a baby or you're in a loud environment, it may be more difficult for you to go off and to hear the other information that's going on around you. The other thing is looking at people who might be in a place where there isn't a lot of internet, like where if you're using an older device, these are also places where there's limited elements people can access.

And if you're in, in, in rural Canada, you can have a lot of difficulty going off and getting the bandwidth go off and to download a web page. And that's not a disability as such, but it is a way that is people are being disabled because the assumption is that people who are using the technology are going to have super fast

Chris Adams: infinite bandwidth, newest iPhone, everything like that.

Mike Gifford: If you don't have the latest device and the highest bandwidth, then you're going to have a lot of challenges. And so many people outside of urban areas don't. And even inside of urban areas, there's places where you can get, there's dead zones in cities where there, or that the things are wrong or inconsistent.

So a lot of our assumptions are incorrect. And I like to think about it also in terms of just, ultimately, you know, the planet is going to be fine with, you know, with or without us, the planet will survive. It comes down to us as a species and as a species, as Western civilization or civilization, how do we want to organize ourselves to survive?

And the brass tacks is that we have to work on a very fragile planet and we have to work with the fact that we are fragile species and that we need to go off and think about it not us at the height of our abilities,

Chris Adams: The whole gamut,

Mike Gifford: abilities throughout the whole gamut of our lives, right? Hopefully we'll all grow old.

Hopefully we'll all be able to explore and experience worlds where we, we do have different abilities because we've managed to live to 80, 90, a hundred years old, but that will be a different experience for all of us.

Chris Adams: I see, okay, alright, that's actually quite an expansive and interesting way of framing it. I haven't actually thought about it in that way, and the idea of saying, well, accessibility is actually a kind of... the fact that you've shifted it somewhat to the situation you're in is actually something that I think that's that's quite helpful framing. Okay, so we've got a rough idea that accessibility isn't just about helping a small number of blind people It's actually a significant part of the population in many cases probably larger than 25 percent when you include the different situational aspects someone might actually be in.

Okay, and it sounds like you know, did you ever see the London Olympics opening where they've got Tim Berners Lee or like Timball to his friends saying, where he has this whole thing, like this is for everyone. He's talking about the web and the internet. There's a thing that it seems very much that you're kind of, there's a reference to that, I suppose.

So these sound like good things, right? But we know that historically, when people are working on digital projects, accessibility hasn't had the same kind of priority that say, shipping a new feature might be, or making sure a particular date is hit by a team working on something. So let's say that, as society, the things you've described sound like good things to be aiming for and wanting to include.

How has maybe the accessibility community made sure these do get prioritized? Because they don't immediately all sound like they would have an immediate short term kind of benefit, for example, or that you might explain to on an earnings call, for example. Maybe you could, say, lay some of that out there and we can explore some of that area as well.

Mike Gifford: You'd think that it really wouldn't take much more of a carrot than trying to go off and support your future self, because that's ultimately you're doing. It's just trying to go off and make sure whatever you, whatever abilities you wake up with tomorrow, which may not be the same as they are today, are going to be, but you're going to be able to use the technology around and interact with the world as best as you possibly can.

That's not much to add, but it's not how people think. People think, people are very much more geared on what's the sexy new thing. Like. At FOSDEM, I gave a talk on accessibility, or sure, on sustainability, and I was, I've given talks on both of them, but it was, and I think it may have actually been both of them, an integration of the two and that, that one.

But the previous two sessions were on AI and they were packed. Like they were, it was like standing room only. And then my talk came up around sustainability. I mean, the room wasn't empty, but it certainly emptied out. And yet this is one of the things that like, this is life. This is us. You know, AI is neat and all, but ultimately it's not the thing.

But in terms of answering your question, what caused accessibility to go off and actually become a, a thing that people are paying attention to is the efforts of people with disabilities who have lobbied long and hard and protested often with civil disobedience in order to go off and to make sure that their rights are respected, seeing accessibility as a civil right.

And so that they are able to go off and have the rights to access by law. And in most Western countries, people with disabilities have rights to work and to employment, to housing, and to be able to communicate with their government. But that process is not being well respected. The digital world is being very much a move fast and break things kind of world, and, and actually supporting the bulk of their users is something that generally most companies don't invest in, even most governments.

Most governments have, far less accessible websites than they say that they should or say that they do. and, and it's something that, that you know, it's only through protest and through awareness raising and decades of effort that, that we've been able to get to where we are right now. and, and that's something that is still not where we need to be.

We're still not at a point where there's a final site that we can say, "Yes, this is accessible." This is like, it is... sites are more accessible, there is more awareness, but it's, it's just like security. It's about perpetual vigilance. So how do we make sure that we're more accessible today than we were yesterday, and that people are pushing that, that type of a framework forward?

Unfortunately, many people have a checklist mind set. They want to go off and say, "has this been done? Yes, let's move on." And that just. Unfortunately, it doesn't help people with disabilities who are actually experts around their own experience of where they're facing barriers with digital interfaces and you know, they need to be able to find ways to engage with their governments or engage with their stores or their friends in ways that are just like everyone else.

But that has, that does require effort and maintenance.

Chris Adams: I see, okay, so it sounds like there's a degree of, like, hard won essentially campaigning on various levels, and there's degree of, like, organ and there's maybe a degree of actual, like, organization with the people who are able to say, "well, okay, we need to find a way to translate these into concrete things you can ask for," or that people who do want to do the right thing, so they know how to go about doing that.

Mike Gifford: Right. Which is, which is how the web content accessibility guidelines. And the Web Accessibility Initiative from the W3C got that started because they saw that this was a need to try and, and provide some guidance and direction that everyone could agree on. And that would be a universal point that would allow everyone to agree that this is an improvement that, that benefits people.

And creating standards is a huge challenge, but it's been really important for organizations and governments to being able to lean on those and build legislation around that. Some of which actually have teeth for a lot of agencies or organizations around the world. So the, having legislation that requires accessibility is a, it's a huge deal.

Chris Adams: I see, and okay, so there's one thing that you just spoke about just there was this idea that, okay, you're essentially able to kind of capture this idea that society values this thing, which is not maybe immediately helping in a quarterly earnings call, for example, but it's still something that people tend to value, and that has ended up being translated into various forms of law, and one of the things that helped with the creation of that law was essentially things like the existence of some of these standards so that people could then say, "well, we want to have, you know, because we value access for everyone rather than just a very specific set of people, we're going to refer to these standards here saying you need to at least hit this kind of bar."

That's how some of it came about. Okay. And if I understand correctly, you, some of the examples you used earlier on about the situational example, like when you've got a broken arm or in your, I think I've seen some of that mentioned from Microsoft, actually, in some of their inclusive design things, so presumably there's an argument about the regulatory certainty that gets provided and means that organizations themselves might want to invest in saying, "well, okay, this is how we are competing in this by, you know, we're going to meet this bar when other people aren't," for example.

That's another kind of argument people take. Okay.

Mike Gifford: And Microsoft has had a great deal of leadership around the thinking around inclusive design and trying to think about how do we make sure that we are thinking about the whole self and not just ours, everyone on their best days.

Chris Adams: Okay, cool. So it sounds like there is a bit of a push. And so one way that some of these were adopted was essentially going through the public sector route to kind of demonstrate that there's demand and there's something that people need to go for and that and by creating that demand that allowed people to then respond to this.

Okay, so I've, are there any like particular countries or examples you've heard of? Because I've heard of like stories like say, I don't know, the things that started in the public sector that then kind of, percolated down. So like maybe I think things with Kindles, Kindle books, for example, or something like that, are there any examples we might point to show how something that large organizations might have been prioritizing first, but this end up kind of shifting them to start prioritizing something in a way that they weren't previously prioritizing?

Mike Gifford: I think that one of the challenges has been that, that governments have initially tried to go off and create their own legislation and, and not to build on a common standard. And one of the issues with this is that the tech is often global. And so if you're trying to go off and create a legislation, like so many governments individually in government agencies just don't have the clout to go off and to go to Microsoft and say, "Yeah. We want you to go to this and implement these standards because these are, if you want to sell to us, you have to follow these standards." Like maybe Microsoft will say, "sure, we'd love to do that. We're happy to go from bend over backwards and make that happen." But most likely they won't. They'll say, "sorry, if you're, this is what the product is.

And if you try it, we'll charge you X amount to go up in additional costs to go up from to meet those standards". But it, but it's not something that, that we can cover because you're such a small entity, generally how, how government procurements work. But, but if you're able to go off and work on a global standard, then technology, and especially if technology companies are involved, like they are, they have been to the W3C, that there's, there's an opportunity to, to get them on board and make sure that a lot of the kinks are worked out of the process, when it comes to implementation.

So that there are things that we know that can be implemented and can be maintained by the technology that we work with, whether that's open source or proprietary, there needs to be an engagement around how we're working on those same set of standards.

Chris Adams: So, one thing that you've just spoke about there was this notion of, okay, you, there's some work that goes into creating standards, because that allows both organizations, at governmental level to say, "hi, we need you to meet at least this bar," but from the other point of view, for people who are trying to meet these standards, let's say like, okay, you're calling from Europe instead of Canada today, right?

Everyone having 28 standards per country in all of Europe, for example, having one makes it a bit easier for someone who's inside the company saying, "hey, can we even at least meet this bar? Because this one will mean that we can, we don't need to do it across all these other countries as well," for example.

That's one of the ideas around the kind of some of these global standards. Yeah.

Mike Gifford: Absolutely. Having a single standard is much easier to get compliance around, particularly if you get a few larger economies that are adopting it early. Like if the European Union is able to adopt a standard around digital sustainability, that's something that will have real impacts around the rest of the world, because a lot of people want to sell their products into Europe.

So. So that's just like the GDPR has had a large impact on privacy outside of Europe as well as inside of Europe because it was something that was, was agreed to amongst a larger group of countries that there was a, an opportunity to really make waves across the digital sector.

Chris Adams: Okay, so that's quite interesting. So we spoke, we were speaking a little bit about accessibility and essentially the same things, because there is maybe not a short term gain for this, you might talk about it in terms of, okay, there is, you're creating some certainty and saying, well, these are things you need to actually have, and I guess in the context of some recent laws we're seeing passed, you might see some of that start to play out in the form of, I think we have things like, say, the CSRD, the Corporate Social Responsibility Directive in Europe, as one example, but even in America, or even in, I think, California specifically, because California is a big enough economy in its own right.

You're seeing some regulations there which end up acting as a kind of driver to kind of move to rather than just have people inside companies saying, "we'll save you some money on your green service." It's like, "no, this is the thing that's actually going to be, this is the bar we need to meet if we want to kind of keep selling to these people here," for example, or "this is a risk that we can head off by making sure we're compliant with this."

That seems to be the argument you're essentially kind of making around that, right?

Mike Gifford: That's right. And I think that, that the, it'll be interesting to see as scope 3 emissions get, get, more closely monitored and evaluated the, the impact of digital, I think is going to be a lot bigger than it currently is because most people don't, don't own a data center, they use services. So if you're, if you're suddenly looking at those people who are managing all the different technology that we're engaging with our lives on a regular basis, that has a third party impact and in terms of virtual pre-emission changes, and I think that we, we're going to, it'll be more of a challenge to try and figure out how to regulate those and to address them.

The web doesn't really affect most people for their scope one or scope two emissions, but it will certainly affect for, for scope 3 emissions.

Chris Adams: Right, I'm just going to take a kind of step back out for this. So I just want to check. So when you've mentioned the words scope 3 and scope 2 and scope 1, I assume you're talking about, say, the Greenhouse Gas Protocol. This is a bit like an international standard for tracking carbon emissions for an organization, for example.

So where scope 1 might be me burning, say, gas and emissions caused from, I mean, I use the hot beverage example because that seems to be quite easy way to get your head around it. Scope 1 is me burning wood or coal to heat up a kettle so I can have coffee, right? Scope 2 is me consuming electricity, so someone else somewhere is burning coal or gas so I can have coffee.

And then scope 3 is the entire supply chain, so that's like me going into Starbucks so I can have coffee. And then, there's still a supply chain, but I'm not burning anything myself, but, you know, there is still someone accounting for the emissions that way, and that's what you're talking to when you talk about these kind of scope 1, 2, and 3 thing here, right?

Okay, brilliant. So, we spoke a little bit about how there are maybe some patterns, some ideas, and some lessons from the accessibility movement where, with the creation of some standards, we've then seen people tie this to, say, how projects get bought. Like, someone help people allocate time and money to do a piece of work and I think the one thing that when we spoke before you mentioned about how you saw this happen at a kind of public sector level first saying "we have to make this accessible because we have a mandate to serve all of our population not just the rich people basically or not just like the this one target market we've decided to segment and go after" essentially but that ends up creating a kind of norm which then is allows, say, other sectors or kind of more other private sectors to start looking for that as well.

And I think there have been examples of, was it the Domino's pizza, for example? The famous example where once people had set a norm that you actually had accessible websites, then was it, maybe you could expand on this one because I think I'm going to get it wrong, but I do remember like Domino's had to start rebuilding their websites and making sure their sites were also accessible to people because the norm had been set.

Mike Gifford: There's a, the US has an unusual piece around accessibility where if your website isn't accessible, you can be sued. There's people who've set up lawsuits and yeah, and some of them are not as legitimate as others, there's easy enough to find accessibility bugs in various different websites. But, but there are, there are people who are chasing the court system in order to try and get revenue from lawsuits.

So then that happens quite a lot in the states and that's a huge motivator around accessibility in the world actually, is the, the sphere of lawsuits from or within the United States. But domino's got sued and they were like, "we're not going to pay for this. We're just going to go off and channel just in the courts.

We don't think this is necessary." They did end up losing the case and they also spent quite a lot more in, in, legal fees than they did in actually hiring web developers who knew what they, they were doing and actually were able to fix the issue. But it was a, it was an interesting case in that, that they, just the egos of the senior management at Domino's.

Were like, "well, we don't want, we don't believe this is the right way to do it. So we're just going to do it our way." Even though they were explicitly excluding customers who could not, who were trying to go up and buy their services,

Chris Adams: Like, "hey, want a pizza." And they're

Mike Gifford: yeah, "I want a pizza." yeah, so I was like, why couldn't a blind person order a pizza through Domino's pizza only ordering system?

It seems ridiculous. They wouldn't want to go off and to address their customers, but that, that is the case for some companies. And having a hammer to go off at, to come down and for those organizations who are opposing best practices is sometimes needed. Unfortunately, you need to have the carrots and the sticks.

Chris Adams: Okay, so one thing you've said, there was basically an immediate harm that was being felt by some groups who were able to then look to some specific laws and say, "hey," this is, that was essentially the basis for that. And that's how you've been able to kind of maybe compel some activity from organizations who might not be prioritizing otherwise, right?

Now, I, for that to be possible, presumably, you needed to be able to demonstrate that a website was unusable, for example, or something wasn't working the way it would. I mean, are there any lessons that we might apply from how we think about maybe normalizing some things around digital sustainability for this?

Like, is there anything we can use from there? Because it sounds like there are I don't think anyone's been sued for not having a green website or a green digital service or anything like that. And I don't I'm not saying you should reach for that first, but It's clearly one of the techniques that people have been using in other fields to kind of compell action.

Mike Gifford: It's interesting though, that Europe is suggesting now that you can't claim to have a green, green product if you don't. You know, they're making greenwashing illegal, which is, it's similar in some ways, but so much around accessibility has been around the creation of these web content accessibility guidelines.

Which have been a set of best practices that have been created by people around the world. Very much like in the, the, sustainability field, the web sustainability guidelines are much newer and they're only being developed by a committee, so they're not something that is a full W3C working group recommendation, but it's something that is moving in that direction.

But I think that in terms of motivating people, you need to have some bar that you can say, how do you demonstrate what the expectations are, and that you're meeting those expectations. And then have a common bar to, from, and to, to compare yourself against 'cause, I mean, how many people have a website that is green enough?

There are not that many. And there, even when you're looking at trying to create the standards and look at, "well, how large should a webpage be?" There's a lot of different views. And the average weight of a webpage, we know right now is about, I think it's 4 megabytes is the average weight of a web

Chris Adams: Bigger than Doom, then, yeah.

Mike Gifford: so it's only the initial release of Doom after all, but it's still shocking that it's that as large as it is, and there's so much cruft that is not necessary. But do you think we can get a website down so that the average site is a hundred kilobytes? Well, maybe, but it's going to be a huge amount of effort to go off and remove all that cruft and advertising and layers of JavaScript and to weed out what is actually necessary to convey. And then there's also elements of how do we build society that, that is where there's, privacy exploiting, JavaScript apps that are adding to the bloat of the infrastructure that we're not addressing. Security issues 'cause, again, if you've got a lot of software, you probably haven't monitored it to make sure it is meeting best practices. And having secure, sustainable code is really a huge part of just creating quality code. If you just redefine it as part of quality, then that's something that, that is really an important way to reframe the advantages of building for accessibility and sustainability.

Chris Adams: So thanks for that. So there's a couple of things that we spoke about and I realize I'm showing my age I'm making a joke about Doom and I realize that most people for them to like get Doom they need to know what a floppy disk drive is and you realize oh my word we... I realized that ages me quite a lot.

So for anyone who... doom was a very popular 3D shooter, and it was, it's definitely smaller than most websites these days. Okay, all right, let's move away from that somewhat depressing note and try and get back to what we were talking about. So you're talking about, there was essentially a way of demonstrating that there are some expectations you have, and then you're able to demonstrate if a website was meeting a certain bar of accessibility and I think when I've heard people talk about accessibility they use this term POUR, like is it perceivable, operable,

Mike Gifford: understandable and robust. Robust is a tricky one, but basically trying to go up and make sure that you're doing this in a real world environment, that it's something that it's not just from set up in a lab, but you've actually got real people, real engagements, real user flows,

Chris Adams: I see, and these and so perceivable is like okay if you're not blind you can't see obviously so you should be able to perceive something. Operable, I get the idea that you can operate it, right? Understandable, self explanatory, and

Mike Gifford: Plain language, all that

Chris Adams: yeah, and then the robust thing is basically this idea that Okay, you've opened this discussion about saying in certain parts of remote Canada you can't access something.

For example, that's like robust, like something might degrade gracefully, so you can still achieve a particular thing even if you don't have like the latest greatest iPhone on the super fast Wi Fi or something like that, right?

Mike Gifford: Right, right. Exactly. It's, it's looking at what are people using, how are people engaging with your site and how do you train and address those? And there's, there's not as many success criteria for robustness because it is a trickier one. Perception is certainly one of the easier ones to address and that's mostly about trying to go up and have textual equivalents for non textual content and making sure that information is visible for people with however they're able to, with whatever senses that they have that they're able to perceive that.

Chris Adams: I see. Okay, so one thing that I guess One insight I'm taking away from that is that these don't necessarily have to be like a binary yes/no thing every single time. Obviously it helps, and it means you can automate things, but that's not an absolute deal breaker for creating any set of guidelines, for example, or something that you might write into a commercial agreement, or might say that, you know, every public website should at least be doing this kind of stuff.

It sounds like you don't necessarily need to have that kind of binary thing.

Mike Gifford: One thing that they've tried to, I mean, the courts definitely want it to be binary. and there's definitely things that, that are, there's different levels of WCAG. There's, there's level A, AA and AAA

Chris Adams: Sorry, sorry, you said WCAG. Is it WCAG? This is Web Content.

Mike Gifford: Web Content Accessibility Guidelines

Chris Adams: got Okay. That's okay.

Mike Gifford: people just pronounce it WCAG, but I've gone with, with WCAG because that's.

Chris Adams: Yeah.

Mike Gifford: Somehow rolls off the tongue faster than, or easier than WCAG.

Chris Adams: Okay. All right.

Mike Gifford: The W3C three in general is good at many things, but not naming things. But the point of the level A, AA, and AAA is it's try to say what are the bare minimum things that organiza that things people should do.

Easiest stuff that affects the most people. What is sort of AA is what is legally required. So in most countries, it's WCAG 2.0 AA is the legal requirement and AAA is sort of aspirational stuff. So knowing that your users are at this base, if you're dealing with senior citizens, for example, you might want to go above and beyond what WCAG 2.0 AA provides, because you know that your users are going to have less perception of color. So you want to have higher contrast available for them than you might for other users. So it's really a, about stretch goals, for, yeah, so it's an interesting approach to structure content so that. And you're hopefully trying to go off and encourage your, the organizations to push themselves to better understand their users and be able to build a website that meets the needs of their users.

Chris Adams: I see. Okay. So if maybe one thing I'm taking away from that is that first of all, okay, there's value in binary, but there's also value in certain kind of grades as it were. And that might be more useful for the specific, I don't know, set of audiences you're trying to reach or who you're trying to cater, for example.

And presumably this, by kind of breaking into something like this, kind of removes some of the need to be an absolute domain expert so that if you're commissioning some work, you can say, well, "you need to be meeting AA," for example, for this, and that's what you could write into, say, a procurement thing to make sure it definitely does happen inside a new project, for example.

Mike Gifford: I mean, and that's what what a lot of organizations have tried to do is they tried to go off and put in contracting language that their product or service must be WCAG 2.2 AA compliant. what the current best practice would be. But unfortunately, procurement officers often drop off the necessities that if, if the client says that the site is successful, they'll leave it at that, and that there'll be no, not necessarily any follow up.

If the project manager on the client side doesn't care or isn't motivated to address this or doesn't have a subject matter expert that they can evaluate, then it's something that that can be quite difficult to implement it. And especially since like so many things, if you don't think about it early enough in the process,

Chris Adams: easy to count, yeah.

Mike Gifford: yeah, so you know, so often accessibility has been left to the end.

And then, well, the budget's spent, the time has run out and now you've got these accessibility issues you've just now discovered. Well, guess what? They're not going to happen, right? They're going to be, or they're going to be done badly. And in a way that's more expensive because it's being done after the fact.

And, and that's often a more fragile way to go off and implement technologies. Think about it from the beginning.

Chris Adams: I see, okay, so there's two things that come out of that that I think are possibly worth exploring in a bit more detail. One of these was this idea that basically, the cost of checking if something is still working the way it's supposed to. Like, you know, people say, "oh, it's totally accessible." But being able to check if something really is accessible, this is one thing that I think you've pointed me to some work where there's some software like Purple Accessibility, Purple A11y.

Yeah, Purple A11y, yeah. This is, I'm not sure where the A11y thing came from, but for people who are not familiar with the lingo, A11y is A one one y, which is the number of letters for accessibility, and Mike, you introduced me, what was the name of

Mike Gifford: It's a, it's a numerium. Anytime you go, you take the, the letters of the beginning of the end and you squish them together. Internationalization is I18N, localization is I10N. It's just, you squish them together and create a number of

Chris Adams: Ah, I see. And that would explain the whole S12Y that I think people keep trying to make happen with sustainability in the kind of digital world, right? Yeah. It feels a little bit mean girl saying stop trying to make, like, fetch happen, right? But this is something I struggle with as well. And if people who are curious why this episode is called A11y to S12y.

Now you know why. It's, numeriums at work, basically. Okay,

Mike Gifford: And they make a lot of sense, especially in Twitter, they make a lot of sense. But now that we no longer are limited by 180 characters, it's, and actually in some ways just complicates things because since sustainable development has been a term popularized by the Brundtland commission, I guess it was the eighties, the sustainability has been overused and generalized in a way that makes it very difficult to understand things and just sort of shortening it into, you S12Y doesn't actually make it more understandable or any more specific.

It's just made it more, added another, fewer characters and more confusion. So it is something that does happen.

Chris Adams: Does make for a cool hashtag, though, so I suppose, you know, swings around about. All right, so we digressed and the reason we mentioned Purple Alley or A11y was because I think this was something you were me about, how there are ways of, there are increasingly tools which, rather than just doing a one off check at the end of a project, might continuously be tracking some of this.

And this is maybe a way to kind of almost provide like continuous audit or something as one of the mechanisms that you might use to kind of maintain a level of quality, for example. I believe Wagtail is one example. They've built some tools so when you're editing a web page, they will basically give you a kind of check ahead of time.

So it's a bit like, shift-left, but for content editors or people who do this. So before you publish something, you'll see some of this and I would assume that other content management systems have these kinds of checks as part of the kind of workflow process rather than it being a thing that gets checked once a year, for example.

Mike Gifford: Right. Drupal has it with the, for the code level. We don't have it for the content level. There are plugins you can add in for modules. You can add in for Drupal that give the authors that sort of context, but we don't have it built into core. And that's something, so it's an effort to install that. It's hopefully it's something that will come into core at some point, but that's a much bigger discussion, right?

How that, how and what tool they use and how that would be implemented. But Purple A11y is a great tool for scanning websites and providing a, an understanding of where accessibility issues are across hundreds, if not thousands of pages, because there's a lot of tools that are built into your browser that you can use to scan a single page. So, like there's WebsiteCarbon.com and the EcoGrader from, which are great tools. But they're, they will evaluate one page and you can pay for services, certainly from EcoGrader that will go off and allow you to scan your site. They keep a sense of your site, but most people are, are not necessarily going to do that.

And not everything is designed for that. And site scanning tools. Yeah. It's nice to be able to have an open source solution that is able to give you a, a sense of the challenges and the barriers that you're running into as you're developing the site. They can see that you're making progress or your site is more accessible today than it was yesterday.

And the incorporation of something like CO2.js into that. It would be a really great addition and there's other tools that could be useful to go off and add to aggregate quality as well and get a sense of like plain language as a, as something that it's very difficult for people to go off and write.

People under think they understand it, but it's, it actually takes a whole lot of work to go off and write in plain language. But this type of language complexity can be evaluated on a code level, at least on the English language. It's more difficult for other languages, it can be. The more we can sort of build in testing early in the process, however, when a site's being developed, if it's built on a weekly or two week sprint cycle, the team, when they're doing their script planning, should know what their accessibility issues are this week compared to the last sprint, so they can see if they're actually making it more accessible today than it was previously.

And the same thing should be applying for sustainability, because there's things that do change in code, like a new JavaScript library is added. And things slow down or there's an image that, that somebody added and that's something that is not noticed by the development team and you want to catch that as early as possible, partly because it's easier to fix them because you've just added it, so you should be able to the issue and, and, and you're like, "Oh, it's just the last sprint.

We know we approved that" and you can learn from that process. I think much like, like spell checkers, like if spell checking was something that you only did right before you submitted your paper,

Chris Adams: Yeah.

Mike Gifford: like you're not going to learn, you're going to be frustrated by the process. It'll be something you ship off to somebody else to deal with and you're not going to go off and build that into your own practice.

But if you see the errors and you see them as you're writing it, eventually you will write better and you'll have a sense of what are the mistakes you often get and how do you try and avoid them going ahead.

Chris Adams: I see, okay, so it's basically a piece of, like, incorporating into, like, your workflow, I suppose. You, you said one other thing that I wanted to unpack, if I may, which was a little bit about setting expectations. Like, talking a little bit about how, like, because you, you mentioned there's things you can do for, like, language, for example.

And we spoke a little bit about this idea that, okay, there's a certain level. I think you mentioned WCAG AA or something like that. And I know the one example I've seen from other places are saying "we aim to meet this level and this is how we check for this and here's how to actually contact us for any kind of breaches" for example like these seems to be mechanisms that i can see being adopted to talk about digital sustainability like one of the reasons i'm particularly interested about Purple A11y and that one there is a it's an open source so anyone can use it for free assuming they have access to like a computer to do that.

But also the Singapore government have been talking about using this to check their own digital estate as well. And that's how I know that in the public sector, some people are using these to do some of this kind of continuous monitoring, or at least some way to kind of flag things up to make some of this a bit more kind of observable and actionable, I suppose.

And like, as far as I'm aware, we don't really have any way of, do we have a way of checking that for accessibility when a... so, you know, you go to a website or a digital server, you say, well, do you, is there a way of seeing a kind of consistent URL, like wellknown/a11y or something to see where they say what they are, say what level they're trying to reach, and then how to kind of test about this.

Because this feels like something you could at least for certain things, be able to kind of verify, you know, verify the claims that you're making, basically.

Mike Gifford: Right. I mean, I think right now for accessibility, the best practices is around trying to create an accessibility statement that's in the front of a web page. So if you go to any European government website, now you'll see a page that is about accessibility, that gives you information. And if it's properly structured, it'll say, it'll have a feedback form that allows you to go up and give feedback if you run into a barrier.

It'll tell you what they've done and how they've done it and get a sense of what some of those challenges are. Also, it's useful to highlight the, yeah, what are the processes that they've done to go off and assess accessibility. All of that can be built into an accessibility statement. And the same type of thing could, could very much be included as a sustainability statement.

And there are going to be pages, there's out,

Chris Adams: we target this, yeah.

Mike Gifford: That's right. I mean, there's no reason that couldn't be done the same, in the same way. You just have a little link in the footer that explains what the process is. And you evaluate that page on an annual basis to make sure that there are things that are being, so that if you're changing your processes, which they do, you come back and reflect on that and say, well, how do we make this better this year than it was the last?

Right. That, that reflection, I think is an important part of it, as well as the feedback with the users.

Chris Adams: Okay, alright, so there is a way, so maybe this is actually quite a nice segue for us to move from, okay so that's one pattern that we've seen adopted in the accessibility field where we know there's a tradition of being quite specific about things you're looking to purchase but also some ways of checking that people are actually like meeting the things that they're saying they're doing.

I mean, there's some parallels to the whole kind of green claims discussion I suppose and that you might see online where people are saying, you know, you can't mark this product as carbon neutral by buying offsets anymore, but they say like if you're gonna make any kind of claim you need to kind of substantiate these claims now rather than actually just having some woolly language around this.

So, okay, and maybe this is a nice way to talk a little bit about what that might look like for digital sustainability because I believe the I know there's these Digital Sustainability Guidelines. I don't, I, WSGs, I'm not quite sure what we would call them. I mean, in Germany, you might call them like WSG, as if it looked like a joke on ESG.

I don't, okay, ignore it. Like, we don't have a good word for them. I mean, nothing is, snappy as WCAG, yeah. So, come up with something for those. I do know that there has been some work to make some of these checkable. I think, I remember the name, it was Star, wasn't it? Star, which is. Sustainability, Technology, Accessibility, something.

Do you know the thing I'm to here?

Mike Gifford: I do. But I don't the

Chris Adams: Sustainable Tooling And Reporting. This is what it was actually. Yeah. I just looked it up in a tab. Yeah.

Mike Gifford: There's whole, there's a whole lot of effort to go off and get a pronounceable acronym that is also somewhat meaningful and doesn't offend anyone. And that was, yeah, that, that's what we came up with STAR, because it's a generally universally appreciated type of thing, so.

Chris Adams: Okay. Well, this is good. And this is like machine readable things that you could check. So you could check it each year, but you could almost Yeah.

Mike Gifford: And that's it. The more that there, I mean, I think that there's always going to be things that are going to be, you know, there's some things you're going to check by machine, but you're not going to be able to check it all by machine. Like even with WCAG, that's being around for as long as it has, you can only catch about a third of the issues using automated checkers.

So with sustainability, there is going to be need to be manual but there's stuff that you can check, knowing where the site is hosted and where the third party libraries are that's stuff that's checkable because it's just an IP address you

Chris Adams: Look it up. Yeah.

Mike Gifford: against database and determine whether it's there.

And the same, the size of the pages and the, the, the use of JavaScript. These are all things that can be. evaluated in a very, black and white sort of manner, like compared year after year to see how, how are you doing or print after sprint to make sure your, your. We're actually making movements on this and just to make, for people to realize that these tools are things that have been hidden, like the weight of a page has been hidden for people for so long.

They're becoming much easier to evaluate and to track and to identify. So a lot of the stuff is, is going to be more noticeable for people and for them to say, well, "why is my page taking so long to load? Who's responsible for that?" Like that's, that is going to be an issue that, the people will start to pay more attention to cause they have to.

Because there will be legislation, hopefully, that requires an organization to demonstrate that they are improving their performance and have improved customer experience and making a more sustainable site.

Chris Adams: Okay, so I'm speaking to you with a, because you're in France, and I know that if we're talking about digital sustainability, France is currently one of the countries which is kind of at the forefront, and they, I'm going to butcher the, the, the RG... I can't remember what they're specific, and it's basically the French version of digital sustainability.

I think it's Référentiel général d'écoconception de services numériques, but basically it's the equivalent to digital sustainability stuff. It looks a little bit like the digital sustainability kind of guidelines, but the French version that they've been written as a, and there's, as far as I'm aware, this is something which has been adopted nationally as a thing that you would actually include.

Now there's another discussion about how you might kind of maintain that and enforce that and make sure and what the remedy mechanisms are if you are in breach of that. But like, that's one of the examples there. I guess, you know, that's one people, one thing that people might be looking at as an example of, okay, here's some ideas, but here's what some of this might look like, for example.

Mike Gifford: Yeah, no, I think it's great. And there's things that I think would have been quite useful to have done for accessibility as well. For example, engineers are required to take a course on sustainability when they're getting educated in universities. Well, why isn't that part of how things are done in accessibility as well?

That's a big one. There's certainly a lot of elements around evaluating municipalities and evaluating other government agencies in terms of what their digital sustainability plans are. A lot of work around recycling, the recycling electronics, again, that's a big part of this puzzle is trying to make sure that the, all of the carbon and resources and energy that goes into these devices is managed as effectively as possible.

So again, that's really forward thinking stuff. And also it's wonderful that France has gone first on this and highlight that, that this is something that, that like somebody has to go first. Somebody has to demonstrate that it's a possibility. And France has legislation in place long before people are even thinking about it.

So it's been a real good thing for the Web Sustainability Guidelines to be able to look at and learn from, what's being done in France and, and to say, well, "how do we take this, this model that is being successfully implemented in France" and try and say, well, "how do we scale this to the rest of the world?"

Chris Adams: see, so like you said before about, okay, are there lessons you can make more general? We should probably give a shout out to the fact that, I mean, and one of the reasons I know about this is work, some work from Gautier Rosilla and also I think a gent, Thibaut Collas was one of the people who basically draw attention to basically a translated version of the old RGSN as examples of this and when I first read them, I was like, "wow, this is actually really, this is actually quite well written" and it kind of stays in its lane in the sense that it's just focusing on digital sustainability, it might refer to some other things, but it's not repeating too much of the other guidance that exists in other forms with other groups and other working groups.

Okay, cool.

Mike Gifford: Also, a shout out to Laurent Devenry, who's also been, I'll include a link to an article I wrote for Apolitical, talking about the, the French, the French legislation and trying to help make it more accessible to the English speaking world. Cause I think that's something that is often a barrier for good ideas is language and culture.

And so trying to encourage more, a broader adoption and understanding of what countries are doing effectively to make these changes.

Chris Adams: Okay, all right. Well, I think we're just starting to come to time, but it sounds like there are a few things we could learn from the world of accessibility, like it's not perfect, but yeah, the idea of like setting some basic standards that you can then write into procurement is one thing that we've got.

Like, we don't really have the equivalent to poor, like perceivable, operable, robust yet. I wish we had that for digital sustainability, and maybe one day will, but if that seems to be a thing, that would be helpful. But the whole notion of being able to like continuously check to see if something is or at least have a way of checking if people are saying something and then are they able to kind of deliver against that.

There's a precedent in accessibility that may also be relevant for sustainability too and we have a growing number of standards from outside of technology that we might even be able to refer to for the things outside of how a website is built that might actually speak to some of the kind of other wider sustainability considerations as well, by the sounds of things.

Mike Gifford: Absolutely. And, and I think that the more we can learn from other people's work, the better it is. It's not like we're anywhere where we need to be around accessibility, but there's been some advances around accessibility that are, that are, are useful to learn from. With sustainability, we just don't have the two decades or three decades of struggle to get us where we need to be.

We need to have countries very quickly taking on regulations or that, that allow us to quickly start scaling down the technology. There's so many organizations buy technology that is there for at least a few years, if not for a decade. And larger organizations are buying technology that, that is going to be in place for a long time.

It takes a long time to shift from one stack to another. So we need to be prioritizing sustainability in the procurement process as early as possible so that it's something that can be built in as we go ahead and as we're building towards a more sustainable future.

Chris Adams: Brilliant. Well, Mike, thank you very much for sharing your perspective and your experience with us today. If people are curious about the, what you've been discussing or some of the work you're doing right now, where should people be looking? Where would you direct people's attention to if they wanted to learn more?

Mike Gifford: Right now that the best place to go from find me is on LinkedIn and it's Mike Gifford is the easiest way to access me. I'm also on a bunch of different Slack channels, like the Drupal Slack or the Climate Action Tech Slack is a facility to reach out. I do have other social media accounts like Mastodon and Twitter, but I generally don't use them as much as I do LinkedIn.

Chris Adams: Okay, right, and CivicActions, that's CivicActions.com, presumably, and if there's any of the other kind of user groups or working groups you're part of, are there any ones we should be thinking about? Like, is it OpenWeb? I forget the name of them actually, you said there's another CMS

Mike Gifford: Open Web Alliance that's, that's, that's coming together. That's, that's an effort to try and get, different content management systems to be able to support and work together to go off and build that more effective open web, so that's one group. Also the Susti Web Community Group is definitely something to consider joining if you're interested in sustainability.

And there's an effort to turn that into a full working group, which will require more effort and leadership for people to be involved. And so, yeah, those, those are definitely some of the main places to see. On accessibility, you can also find us on our accessibility sub site, which is accessibility.civicactions.com.

Chris Adams: Brilliant, okay, and I just realized, you mentioned something about FOSDEM in a talk, There's, I'll share the link to the FOSDEM, Sustainability and Accessibility Talk, which was what prompted some of these discussions in the first place. This has been fun, and I didn't realize that you were in Europe, so if I ever do pass through Paris, or pass through Carcassonne, or France, maybe we'll get a glass of wine or something.

Mike Gifford: That'd be lovely.

Chris Adams: Thanks a lot, Mike. Lovely to chat to you again. All right. Take care.

Mike Gifford: See you, Chris.

Chris Adams: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode!

View Details

In this episode of Environment Variables, host Chris Adams explores the theme of Community Publishing and Greening Software, by talking to Branch Magazine’s Hannah Smith and Marketa Benisek. They discuss community publishing and the lessons learned from producing Branch Magazine, which supports sustainable digital practices and includes diverse voices from the Green Software Foundation. The discussion covers the complexities of adopting digital sustainability and how Branch Magazine, through its innovative, carbon-aware design, has been a platform for expressing these nuanced themes in sustainability and how finding beauty in the imperfect might just be the answer to all your problems!

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Hannah Smith: LinkedIn * Marketa Benisek: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

Topics:* Branch Magazine | climatetech.action [1:50] * Designing a Grid Aware Website [13:09] * Content Trends [20:38] * Sneak Peek Preview of issue 8 [27:12]

Resources:* Grid Intensity Library | Green Web Foundation [02:29] * Green Web Foundation [3:30] * Wholegrain Digital [4:04] * WebsiteCarbon.com [4:07] * Solarpunk [24:12] * The Wabi Sabi Web - Branch | Tom Greenwood [28:49] * Embracing friction: A conversation with Luna Maurer and Roel Wouters - Branch | Marketa Benisek [30:08] * Talking it out: Restoring information ecosystems through authentic human connections - Branch | Bárbara Paes and Olivia Johnson [31:26] * Echoes of electronic waste - Branch | Joanna Murzyn [31:37] * Connectivity, infrastructure and the defence of the Amazon's socio-biodiverse ecosystems - Branch | Hemanuel Veras [31:41] * One Movement, Four Wings: Connecting climate strategies - Branch | Melissa Hsiung [32:47] * Ministry of Imagination - Branch | Rob Hopkins [34:58] * Issue 8 community-assembled playlist - Branch [36:30] * Curiously Green, the green web newsletter - Wholegrain Digital [39:59] * co2.js | The Green Web Foundation [40:44]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
Marketa Benisek: Perfection is essentially the enemy of progress. So it doesn't really matter if something is imperfect, but we can build on it. That's when Hannah came up with the idea that actually we could collaborate on the next issue of Branch Magazine, and this could be the theme.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello, and welcome to another episode of Environment Variables, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. The world of green software and digital sustainability has come a long way since the Green Software Foundation was created three years ago.

The Software Carbon Intensity Specification is now an international standard. All of the large hyperscale cloud providers in North American Europe now publish guidance about incorporating sustainability principles into building on their platforms, and we're also seeing unprecedented policy interest in both understanding and managing the emissions associated with digital services in general.

There's more to sustainability than just making our software greener, though. If we want a truly sustainable industry, we also need new visions of how we relate to technology and the role it might play in a more positive, regenerative future. One such vision. Is that laid out by digital magazine Branch, a publication featuring writing from many of the active feature figures in the Green Software Foundation and one of the first ever websites to pioneer a carbon aware design that changed in response to the carbon intensity of the underlying electricity grid that its servers ran on.

Originally from climateaction.tech and published by the Green Web Foundation, Branch is a twice yearly publication, and at the time of this podcast being recorded. It's now into its eighth issue. Now, in the interest of disclosure, I should probably share that I've written for Branch a few times and that I worked on the grid intensity library, the JavaScript library, that the site relies on for its carbon aware design features.

I'll try my best to keep my bias out of this episode, but it's worth acknowledging that before the GSF, The Green Software Foundation was as prominent as it is now, is one of the better known non commercial places to read about the intersection of software and sustainability and see how folks are doing it.

I'm joined today by two of the contributing editors, Hannah Smith and Maketa Benesek, to talk about community publishing as a tool for change and the lessons learned publishing a magazine that tries to walk the walk as well as talk the talk on sustainability in the digital realm. So, Han, Marketa, thanks so much for joining me today.

Can I give you the floor to introduce yourself and what you do?

Hannah Smith: Great. Well, thanks, Chris. Thanks for the introduction. And yes, you are definitely a little biased in talking about Branch. I think that's fair to say, but anyway, I'll introduce myself. So hi, my name is Hannah Smith. I am director of operations at Green Web Foundation, where some of you might know, I work alongside Chris and I'm very excited to be here.

I was a WordPress developer for a long time. I also run a meetup community called Green Tech Southwest. And quite recently, sort of over last summer, I was very involved in a project looking at grid aware computing as a, as an alternative or an improvement on carbon aware computing. So, Marketa, I guess over to you.

Marketa Benisek: Thank you. Thanks for the intro, Chris. So, my name is Marketa Benisek. I work as Digital Sustainability Lead at Wholegrain Digital, the authors and kind of creators of WebsiteCarbon.com, the online kind of first and original online carbon calculator. And I'm really, really excited to be here. And I'm super excited about this project. I also did a climate reality training with Al Gore, uh, during the pandemic and I'm a carbon literate professional. So that means that I essentially, I'm just really passionate about explaining people kind of the essentials and the basics of the climate science so that they understand the urgency of why we need to take action.

Chris Adams: Thank you for that, Marketa. Now, before we dive into the world of Branch and community publishing and all that, we normally ask where our guests are calling from to get a bit of background color, really. Han, can you just tell me a little bit about where you're joining me from? And then if I hand over to Marketa after that.

Hannah Smith: Yeah, so thanks Chris. I am dialing in from the temperate rainforest in Exmoor National Park, which is over in the southwest of England in the county of Somerset. And today, as I look out the window, all the trees are coming into leaf and it is a truly, truly glorious view.

Chris Adams: Wow, I spent 30 UK and I'd never realized there were rainforests. So you said temperate rainforest as opposed to a tropical rainforest. Is that how it works?

Hannah Smith: Absolutely. Yeah. I didn't know that temperate rainforest was a thing until I moved here either, but there is this growing movement to reestablish these, these ecosystems or, or just make people aware of them. It's basically a forest, which is on the coast and pretty wet, and that's how you end up with a temperate rainforest.

It sounds, it sounds exciting, but you know, you need good wellies and a good Mac and not to be afraid to get a bit muddy if you live here. Yeah.

Chris Adams: Marketa, over to you as well.

Marketa Benisek: I am joining this call from Prague in Czech Republic. That's where I'm based currently. I relocated here a couple of years ago from very busy London after having a kid. So yeah, it's just, it was a beautiful spring weather just about a week ago. And now we're back to snowy weather. So we got all of those like winter jumpers. And yeah, we'll see what happens.

Chris Adams: Wow. Okay. I did not know that you were in Prague actually, Marketa. I thought you were still in London. Okay. I should probably go myself and also introduce myself because I realize I've just done this massive introduction without saying who I am, what I'm here for. So folks, if you are listening to this podcast for the first time, my name is Chris Adams.

I am the executive director of the Green Web Foundation. I'm also one of the organizers of Climate Action Tech, which is a online community full of essentially climate aware techies, I suppose. I also worked as one of the policy chairs in the Green Software Foundation, and that's partly how I know Han.

As Han mentioned, I did work on the Branch Magazine, a few years ago, basically. So I have some kind of background there. I'm calling from Berlin where today it's been sunny and hailing at the same time. So that's my kind of contribution to the meteorological diversity, I suppose. All right. Okay. So I think we're all sitting comfortably and we've got a good idea of where we're all kind of calling from today.

Maybe we should talk a little bit about Branch. So I understand there was a new theme for this that the two of you wanted to kind of talk about because it's, we've had different themes for publishing different issues, but the theme this time was I think finding beauty in the imperfect. And I believe this was on, this is a kind of reference to some of the struggles we see when people start trying to adopt digital sustainability principles or kind of working around that.

Would either of you maybe just explain a little bit about how this came about or maybe what drove you to kind of come to it from this point of view, actually?

Marketa Benisek: Yeah, absolutely. So I should probably start by saying that Hannah was one of the first to I met a lot of female voices that I came across shortly after I met Vinita Greenwood, the co founder of Wholegrain Digital. And she was one of the first female voices that I've heard talking about digital sustainability and digital carbon emissions and all that. And I introduced myself, this is it must be about six years ago, seven years ago, something like that. And then we kind of stayed in touch ever since, you know, we collaborated over several projects and we just stayed in touch and connected about once a month over a call just to catch up and talk about what's new in the digital sustainability world, so to speak. And about six months ago, we got together on a call. We were both pretty upset about some recent articles and mentions of the different tools and, and projects that people criticize for their imperfections. And it felt, it wasn't really the criticism itself that was so upsetting, it was mostly the fact that they made it sound as if there's just no point in trying

if it's not perfect in the first place. And so we got to talk over this and, and about this, and we just realized that this is something that we feel really, really strongly and passionately about, and we wanted to address it and kind of just voice out that, you know, perfection is essentially the enemy of progress. So it doesn't really matter if something is imperfect, but we can build on it. That's when Hannah came up with the idea that actually we could collaborate on the next issue of Branch Magazine. And this could be the theme that would kind of give the platform to lots of different voices in this field and to people from CAT community on like, what can actually be done and what is already happening in this space that is imperfect, but it's still very much meaningful.

Chris Adams: Okay. So thank you for that, Marketa. That does provide some of the context that makes it a bit easier to understand this theme. Han, maybe I could maybe hand this over to you to talk a little bit about why you chose to explore this theme using a magazine like Branch, for example, rather than trying to get a white paper written or something like that, perhaps.

Hannah Smith: Thanks, Chris. Yeah. So, so as Marketa has said, we kind of had these conversations and we kind of realized that we felt that this narrative, which can be quite dominant in the tech industry of, you know, of always having perfection in your data or, you know, always striving for everything to be a hundred percent accurate.

We kind of felt that we had a lot to say on it, and we also thought that there'd be a lot of members within the climateaction.tech community that would have a lot to say on it too. Perhaps they were in a place of work where they were having to overcome some of these, you know, some of this pushback from their own team, or perhaps they're in, you know.

Developer communities that were maybe not embracing these ideas again, for these reasons. So we kind of realized that Branch would make an absolutely amazing place to bring loads of different voices. From across the whole tech industry together into one place. And, you know, Branch is very much founded on this idea of bringing together different voices and perspectives from even different industries, not necessarily just the tech sector.

You know, we know that there's people working in research or people who work with tech. You have an awful lot to say here too. So Marketa and I were like, yeah, okay. Let's get the CAT community involved in this. Let's see if people want to tell stories from their places of work, or maybe there are founders of companies that want to talk about how they're embracing things in different ways.

Maybe there are some people who are, you know, uh, practitioners, maybe freelancers, maybe independents. Maybe people from research organizations. Let's get all of these voices together, let's get all of these perspectives together, and let's kind of create, we've been talking about it as a bit of a tapestry, a kind of tapestry of views that start to answer these questions or start to explore what it actually means in practice when you're working in digital sustainability to find beauty in the imperfect.

So what is beautiful, and what is imperfect? So yeah, we've kind of thought Branch just lent itself to be the perfect place for people to do that. And again, the awesome thing about Branch is it's a non profit magazine, as you well know, Chris. So that awesome, we thought made it easier for people that were perhaps within organizations that maybe don't have a platform to speak within their own organization.

They could come and use Branch. And be able to talk about things in an open way that perhaps their organization might not be so cool with them publishing on their own blog. So it feels like a great opportunity to bring a really diverse, in the biggest possible way, set of voices together, I think.

Chris Adams: Okay. I see. So you've got this idea of diversity. And one of the key things is that it's not just one person, you know, the internet isn't just for like developers, for example, there's other, there's users and there's other people who are affected by it that it's worth hearing some of their voices involved in it as well.

Okay. Thank you, Hannah. That does make it a little bit clearer, actually, since you spoke a little bit about Branch and actually the design part of it, maybe we could just switch gears for a second and talk a little bit about some of the realities of trying to make some of this, because one thing we mentioned before is that Branch was one of the early magazines that essentially changed this design based on how green the grid is, basically.

And I figured maybe we could just provide, have a bit of kind of catnip for the nerds talking about how that was actually done. So maybe you could talk a little bit about, okay, yeah, that's a cool idea, but. There's all these considerations from a production point of view. So maybe are there any kind of particular challenges you found or things we would have bear in mind if they're going to take their first steps into designing, say, kind of a grid aware or carbon aware design like this?

Hannah Smith: Yeah. Well, thanks, Chris. So Marketa, I might pick that question up if that's okay with you. Cause I

Marketa Benisek: Yeah, please do.

Hannah Smith: yeah, so, I mean, Chris, I know you were sort of involved in building the first issue of Branch. I came on board to help out on the second issue and beyond. And so I think it's worth saying that first of all, the way that Branch responds to the grid is that it provides a different experience based on what's going on, on the grid on a certain day.

So if you've got loads of fossil fuels on the grid, on a particular day, you don't see the images by default. So you have to actually opt in to see the images. If you've got a nice windy, sunny day, maybe then the intensity will be low. And so you will see the images. And then you've got this middle, middle scenario there, where the images are converted into a really fuzzy kind of web format so that you can see the images, but there's a clear and obvious degradation.

The thing I really, really like about Branch and the way it does that is that it's, it's giving you a different, um, experience based on the renewables that day and in that place. So it's, it's more responding to demand or, or supply really of what's on the grid. And I think that's quite clever. So rather than sort of doing stuff like shifting around location or time based. I find that that is actually a very, very visceral way that people can understand what's going on in terms of the supply coming on to the, onto the grid. Actually, I find it throughout Marketa and I putting all the articles up for issue eight, I found it brilliant. I've now know exactly what's going on on the given day as to what the renewables are, because the background color of Branch tells me, which is super, super handy.

But actually we did notice just last week as we were kind of finalizing some of the images that well I don't know if it's a new level of carbon intensity or if it's a just a level of carbon intensity we don't get very often in the UK. But I, to my absolute shock and horror, went on Branch and it was grey and I was like, oh, That's not a color Branch.

Chris Adams: What's going on here?

Hannah Smith: That's not supposed to happen. What's going on here? And we looked into it and realized that actually the grid was running at very low carbon intensity that day, which kind of made sense because when I looked out the window, it was super windy, yeah, super sunny day and we were like, all right, cool. So I guess like, that's quite a fun bug in a way, or a fun thing is that, you know, I guess our expectations over different carbon intensity levels can change a little bit, or, uh, you know, if you're connecting through to an API, something, something suddenly shifts and, and you get a bit of a surprise.

So that's definitely a bit of fun to be aware of on the production side of things.

Chris Adams: I remember you, I remember you talking about some of this actually, like, like, you thought, oh, the grid's never going to get that green, right? And then you see it changing, like, oh, Christ, you need to update the design because of this. Yeah. This idea of like having different thresholds was, you know, Yeah, that was, that was a new thing because I remember you asking me and like, it took scratching my head a little while because it doesn't seem to be anything wrong with the code.

And then you realize, oh, the API that tells us the carbon intensity must then have started to introduce some new levels that we need to design for. So yeah, that's, uh, that, that, that was, that was actually kind of a fun thing from this. Okay, cool,

Hannah Smith: Happy days though. I mean, I'm happy that we were running on very, very low intensity on those days of, you know, Hey, that's what we're here for, right?

Chris Adams: Yeah, that was, I guess, the technology being somewhat more enthusiastic than the design five years ago, or four years ago, perhaps. So that's like one of the examples that we need to take into account. And maybe one thing that I'm glad you mentioned the idea that when you first visit this, you don't see the images.

One of the things that I think is There was some fair amount of focus, which is often overlooked is the accessibility of this, like deliberately trying to make sure that if someone can't see an image, you at least have some way to make it perceivable to people, for example, maybe we could talk a little bit about some of that thing, because people tend not to, this may be a thing that is overlooked in publishing, that's actually, I guess, part of the web, maybe, and maybe you could expand a little bit on the accessibility aspects before we talk about some of the actual content of Branch, perhaps, Han.

Hannah Smith: Yeah, sure. So I mean, something, when you're uploading content to Branch, you realize just how important alt text is on your images. Because that's one of the key features of Branch is that if you have a very carbon intensive day, so e. g. there's lots of fossil fuels, bad, that's not what we want, you don't see the images.

And what you see instead is the alt text and a caption, which describes it to you. You do see kind of, you see a grayed out placeholder of the image. So you're very aware that there is an image there, but you can click show image and you can see the image and opt for that to get downloaded to your machine and opt for for that, that additional action to happen. So accessibility is a really interesting aspect here as well.

Chris Adams: Yeah. Cause I guess on one level you're, that's kind of like forcing how other people might perceive the web, if it might be, might be partially cited or something. It's kind of some of the decisions there to kind of foreground the fact that the way that you experience a digital service may not be the only way it can be experienced, for example.

Hannah Smith: Yeah, it's, it's interesting. I love the way that Branch does that. It plays with almost messing with your perception of what a website is and can be, and I, I mean, that was always one of the key ideas of it was to imagine different ways that a website could be, it doesn't always have to be the same, exactly the same.

It should be responding to different things. And also remind you that people interact with these things in different ways as well. As you rightly said there, Chris, you know, not everybody will see the images all the time.

Marketa Benisek: It's a great preview into someone else's world and how they see the world, how they see the digital world as well. I think this, this often doesn't really get enough attention. That not everybody sees the images in perfect high res, you know, some people might see it blurry, some people might see it, I don't know, pixelated, whatever, you know, so paying attention to these alt texts and, and just a different setting for people who might have different needs and different kind of health conditions is really important and the entire web. should be built that way. I mean, that's why we have this technology in the first place. So the fact that Branch has that is really important, I think. And I'm just, that's just one more reason why I love it so much.

Chris Adams: So, Marketa, you're right, actually, there is this notion about, I guess, the web being something that should be accessible for everyone, because, like, the internet is for everyone like this. Maybe we could talk a little bit about, actually, some of the high level themes in the content for this issue. Like, are there any trends that you felt really deserved attention or could do with more people writing more openly about, for example?

Marketa Benisek: Yeah, absolutely. I think that, first of all, you know, the, the theme, we were pretty set on, on the theme, Hannah and I, you know, since. The very early days, finding beauty in the imperfect. I guess as two women working in tech, you know, it may come across, it may have come across slightly more poetic or feminine to some. And I think that some people, there was a need to kind of explain what we really mean by this. So we spent quite a bit of time on this explanation, you know, through the open call page, just to really clarify what this means. And obviously it was an invitation for everyone, not just for women in tech. I just wanted to make that really clear, but yeah, I, I mean, after we set the open call page on Branch, we received a really great number of submissions that we carefully read through and selected the best ones that really spoke to the theme and then we narrowed it down to I think seven or even eight categories and we got super excited and obviously we wanted to involve everything and you know, we wanted to give a platform to everyone who even reached out and things like that. But then we got a bit more realistic and we realized that actually, you know, we really do need to narrow it down. So we narrowed it down to four key categories that kind of spoke really strongly to just new ways of building just and sustainable web that is also a humane web. And so now we have four categories that, that they are meaningful connection, kind of solar punk and imagining different future, new ways of looking at the design philosophy and how we might be able to build the web.

You know, that is not perfect or not in that kind of usual perfect way, seamlessly perfect. And then finally, obviously the perfection itself and just not letting it be the enemy of progress. So those are kind of the four key categories that were really, really, important for the theme, I think. And yeah, I just really can't wait to share that with the world.

Chris Adams: Okay, and that's presumably the logical grouping inside the content. So someone, when they go to the magazine, they'll see it grouped like that. So they might look at dive into one, for example, and then the other, right?

Marketa Benisek: Yeah, absolutely. I mean, obviously this wasn't a straightforward process. You know, we spent a long time kind of going through all of those images, grouping them together. But shortly after we received all of the submissions, we could see patterns in some of these, you know, submissions and we obviously group them together and kind of organically these four key themes.

Chris Adams: Ended up being the logical group for this.

Marketa Benisek: And yes, ended up being the four categories, yeah.

Hannah Smith: And I think I might just add a little bit onto that as well, because the, the whole idea of this theme was that we wanted to explore the subjective ways that people Think about finding beauty in the imperfect in digital sustainability, whatever lens they're looking through, be that developing carbon calculation methodologies, be that designing things, being that the way that people use the internet, being that even questioning, should the internet even be a thing in the first place?

So we did throw it very, very wide and then as Marketa explained, you know, we, we grouped things. And then what we kind of discovered, the thing that makes me very happy because I'm quite nerdy and I do like everything to be neat and tidy, is that those four categories then yes, you're laughing because you know this is true because we then noticed that those four categories almost become a journey in themselves.

So, as Marketa said, that the first category we saw was around meaningful connection. And I guess the first thing that you ask yourself when you're Looking for beauty in the perfection when you're designing something is, why? What are we designing this for? And we realized that actually, at the very, very heart of it, what the internet should be about is creating meaningful connection.

Not just connection for connection's sake, but meaningful connection that's humane, that is just, and that is sustainable. And we kind of really noticed that theme. And then we kind of thought, alright, so you know what you want, So the next thing that happens is, well, in an ideal world, what does that success look like?

And that's where that imagination piece comes in, these ideas of Solarpunk. And if anyone's listening and hasn't heard of Solarpunk before, you're in for such a treat because it's just such a cool movement. It's all this idea of kind of imagining regenerative, renewable futures. So you kind of, once you know what you mean, you know what you want, EG, a meaningful connection, you start to imagine what it looks like.

And we had so much fun with all the pieces that imagined the future, like there's some absolutely amazing, beautiful, yet imperfect stuff in there. And then once you're imagining things, what we realized is the next step on your journey is the logical question is, well, how are we going to make it? And we realized then that we had this grouping all around design philosophy of people talking about all these different ways that they want to make this stuff, that they want to make things on the internet, that they want to design things on the internet.

And then we came to this fourth category and I wouldn't say it's the last one because the other thing we realized is that everything is just so deeply interconnected. And I think you realize that when you're doing anything in sustainability is that connections that are everywhere. It's never finished and it's never linear.

But we noticed this last question was around, well, let's talk about some of the things that get in the way of us designing our things or building our things. And we realized, well, perfectionism is this key thing that seems to come up and up again and is so often used as a kind of defensive measure for why we shouldn't bother.

We kind of realised that that was almost the last stop on the journey,in a way, probably before you go around again. So the categories do stand in isolation from one another, but can also be read and taken on a journey as well for kind of completing a whole process here as well. So when, when that kind of made itself obvious, I was very happy cause that, that felt very neat, very neat and tidy, so-

Marketa Benisek: Yeah that was a beautiful day that one

Hannah Smith: It was a beautiful day, but obviously there's imperfections there too, even in that.

Chris Adams: I see. Okay. Thanks. Maybe I'll just bring, hand over to Marketa. So we've spoken a little bit about themes and like the kind of, the motivation for this. Maybe we could just move to like some of the concrete pieces, for example, if we would have like a preview of some of the things you'd like to draw attention to, or kind of give a sneak peek, sneak preview of this.

Are there any articles you particularly enjoyed or you found a lot of, that you, would like to draw people's attention to, for example, if I hand over to you, Marketa, first, and then Han, I'll give you a chance to kind of name some of your favorite children, as it were, or favorite babies, or whatever, whatever phrase you want to use for this, then we can see what we've got there.

So, Marketa, you first, if I can.

Marketa Benisek: Yeah sure so I guess throughout this process, what I enjoyed the most was seeing these kind of similar patterns occurring in different places around the world. That was really just fascinating to, to witness and to be a part of, because, you know, all of these authors are from different parts of the world. They are talking about different problems, different solutions. And yet they were using very similar language. So for example, we mentioned perfectionism as kind of one of the obstacles to building a more just and sustainable and humane web. And interestingly, several people, at least my authors, you know, the authors from my group, they kept mentioning friction and the need of friction.

Somehow it seems like friction and imperfection is what makes any experience more human. And the web and trying to make it kind of perfect and frictionless and seamless and everything like that, that goes against that human experience, that humanness in the first place, which was really interesting, kind of realization out of this whole process, this project. Some of the articles that I really love, obviously, there is Tom Greenwood's article, the co founder of Wholegrain, who talks about the Wabi Sabi Web. And I just really love how Tom thinks and how he articulates his, his thoughts. It's just, it's kind of like a beautiful journey through his mind. And so Tom picked a Japanese philosophy called wabi sabi, and he used several examples of how we might use it to build a more humane web.

So wabi sabi is a concept where you kind of accept the imperfection and kind of the fact that all things All of these are beautiful because they reflect the time and the experiences that they have been through, but we don't necessarily see that on the web. And maybe that's the problem. Maybe, you know, all of the data are kind of like set in stone and we don't see how the users behind the data changed and evolved over time.

So this is just a really interesting and very fascinating exploration of how we might. Imagine a different kind of web called the Wabi Sabi Web, so to

Chris Adams: S W S W, instead of dub dub dub, right? So, W W W, W S W, perhaps.

Marketa Benisek: Yeah. Yeah,

Good point. Then also just going back to friction, I actually, Hannah pointed me to a really fascinating project called Designing Friction by two artists based in the Netherlands. And I did an interview with them and they really very much go against this whole concept of what the web is becoming. You know, it's becoming this unhuman frictionless space that doesn't really allow for playfulness. And they are against it, not only as artists, but as parents, as human beings. And so it was really interesting to read through their principles of how we should kind of make friction part of the digital culture.

It should be something that is celebrated and even sought for. You know, it shouldn't be something that we should avoid. And they give a whole bunch of examples of how we might be able to do that. And just to clarify, this is not to say that friction should make the internet slow or, you know, it's not about making the user experience awful. It's just about making the whole user experience more human. It shouldn't be about users, but it should be about people. So to speak, and then we've got a whole bunch of real examples. Uh, from authors who are actively trying to understand what the internet is like for people in different parts of the world. And yeah, for example, there's a really lovely article from Barbara and Olivia from the Engine Room who talk about their research on the information ecosystem in Latin America. And another one about e waste in India and another one from Hemanuel on the importance of the internet connection for the peoples of Amazon. In order to help them kind of defend not only their own rights, but also the nature around them that they are living in harmony with. So these real examples of what the internet is like in different parts of the world, not just in our kind of privileged, rich, you know, Europe or our part of the world, has been just really so eye opening and I really, really strongly recommend people to, to go and have a look.

Chris Adams: So you spoke a little bit about say, you know, friction, making things a bit more kind of legible or possibly understanding where it's not just kind of totally seamless, fast thing where there's no agency for people at the end use, but you've also spoken, and there's maybe some content about essentially this intersection of climate and technology, how it manifests in different parts of the world, like you just mentioned, those, those writers from various places.

Thank you for that. Okay, Hannah, can I hand over to you perhaps to talk about some of the things that have been catching your eyes, that you direct people's attention to now that you've been working on this magazine for the last, like, couple of months, for example,

Hannah Smith: Yeah. Thanks, Chris. I think there is a piece written by Melissa, who's one of the organizers at climateaction.tech. And she has talked about a concept using a four winged butterfly. And the idea of the four winged butterfly is it represents a social transformation. And I think if we're going to transform the internet to be a more healthy place, to be a more humane place, to be a more just place, to be a more sustainable place, I think this is something everybody should read.

She talks about the, it's not her concept. It's, it's a concept from somebody else. But she's put it into a digital sustainability context. And the basic idea is that you need these four different elements of change. So each element of change is a wing of the butterfly and a butterfly needs all four wings or all four parts in order to be able to fly.

So it's this idea of, yeah, it's a lovely idea. I think it's a really, really good one. And the way she talks about it is, you know, she says, well, look, if you're looking at something that somebody's trying to do, if you're looking at a project and you think, ah, this is rubbish, this is no good, this isn't, you know, perfect, what about X, Y, Z, she said, well, you know, you can look at these other wings of the butterfly or these other aspects and actually maybe understand that, you know, this particular change or this particular initiative you're looking at is only one part of the butterfly.

But if it's connected with other parts of the butterfly together, it actually makes a movement, you know, a social change that can move, that can fly. And I loved that practical toolkit that she was giving there to say, hey, you know, if you think something's imperfect, perhaps You're only narrowing in on a really tiny part of it and, and if you zoom out, there's yeah, look at the bigger picture, you might realize that this is an absolutely essential part of making other things move or, or of giving other areas flight.

So I loved Melissa's piece and I, I really recommend that for anybody who's, who's interested in, in creating change and, and making progress. And I'll say two other quick things. One that just, it was a bit of a late addition to Branch, but it's just absolutely captured me, floored me, is there, it's a piece by Rob Hopkins.

And he's just published something called the Ministry for Imagination, which is the work coming from a hundred podcast episodes where he invites people onto the podcast. To talk about the world. Yeah, it's pretty cool. So you've got a long way to go, Chris, a hundred episodes. So he has sort of through working with these different people, they're interviewing on the podcast, come up with this manifesto for what it means to imagine a better world.

And it's not really just tech related. It's far broader than that. It's across all of society, but it is an absolutely incredible example of why imagination is important. And how sometimes it can lack a little bit in the digital space. I think we, we can get a little bit narrow minded about things perhaps, or see things in a bit too black and white and maybe not, not be playful enough.

So here's Ministry of Imagination. I can't recommend strongly enough that everybody takes some time to have a look at that for like an absolute definition of the power of imagination and solarpunk. And then the last thing I'll, I'll mention super quickly. Is when Marketa and I were looking at all of the articles, we had a hope at the beginning that we would not just have loads of writing, but that we would have art and we would have poetry and music.

And we noticed that poetry and music was a little bit lacking in the edition. So we've set off and created a Branch issue eight playlist. Where we have asked a whole bunch of people from across the community to suggest songs that motivate them to take action. But then also pick out lyrics that really speak to them.

And actually I had a chance to listen to the playlist before launch. It is so eclectic. We've got rock, we've got classical, we've got trance, we've got acoustic, we've got reggae, we've got funk. We've got like, hardcore dance music. We've got all this stuff. And I think what that speaks to me is that there is no perfect music choice to get motivated by.

Everything is different. It's, it takes a diversity of perspectives and a diversity of, of vibes, energies to make change. And I think the playlist really, really embodies that. And I think it also speaks to. The wider movement as well around needing a diversity of viewpoints and a diversity of cultures.

Songs are all in different languages as well, but actually you bring all of that together and you get a real tapestry. And I loved listening to the songs and I loved reading the lyrics that people highlighted and their reasons for including these songs. So it's, I know it's not that much to do with tech, but we are all humans at the end of the day.

And I think music is, can be a really, really big motivator and something that really brings people together as well. So I'm a big fan for the playlist as well that came about and you can find that on Spotify too.

Chris Adams: Okay. All right. So it sounds like there's, okay. Let's say that we have prose, poetry and music and references and links to other forms of music as well. All right. This is, this is sounding quite rich actually. Okay. We're, we're just coming up to the end of time. So this is basically a kind of project. If there's something of a passion project, but there is still a focus very much on like digital culture and things like that.

I understand that you do more than just make magazines. So Marketa, we should probably tell people where to go to look for this. I mean, maybe is there a domain name or a search search term they should be looking for if they want to learn about some of the things we've been talking about?

Marketa Benisek: Yeah, absolutely. So if anyone is interested in reading any of these articles and much more, they can go to branch.climateaction.tech. They can find all the information there and all the articles, the playlist and everything else that we've been working on over the past four or five months, something like that. Yeah. So that's,

Chris Adams: so Branch. climateaction.tech is the way to look up, and that'll give you the most recent issue. So we're recording this on the 22nd of April, but I believe it's going to coming out in the next week or so, maybe the 25th, I think it was the date that I've heard. And presumably that'll be the big day.

Okay. So when this comes out. If you're listening to this, it's probably out already, so you can check it out yourself along with the other previous seven issues worth of content that you have there. All right, and if I understand it, this isn't all that you do, so maybe I could actually just, while you're here, give you a bit of space to kind of talk about some of the other things you're doing.

So, Marketa, for example, where else should people be looking if they want to learn a little bit about digital sustainability or some of the ideas or some of the kinds of things that we've discussed, for example.

Marketa Benisek: Sure. So we frequently publish new articles on our blog. So people can go to wholegraindigital.com and then go to our blog and they can find lots of stuff related to digital sustainability, humane web thinking, that sort of thing over there. And I'm also very happy and proud to be on the team that creates a monthly newsletter called Curiously Green. And that's all about. All the things, digital sustainability. So yeah,

they can just go to,

Chris Adams: I really like that as well, actually. I'm glad

Marketa Benisek: thank you

Chris Adams: And Han, if people are curious about where you've been coming from, I suppose, is, are there any projects or things you'd like to draw people's attention to in the last few minutes that we have for this?

Hannah Smith: Yeah, thanks Chris. So I guess my day job is at the Green Web Foundation. So you can head over to thegreenwebfoundation.org and you'll see a lot of my work represented there. You'll see a lot of blog posts coming out from me, where we talk about the Green Web Dataset. We talk about our open source co2.js package, and also there'll be some really nice work coming out soon.

With some really nerdy deep dive work into the practicalities of carbon emission estimates for digital. So Chris, obviously you and I are working on that together. Yeah, head on over there and I think you'll get a good insight as to what my day job involves on that website.

Chris Adams: Okay. And just before I go, I believe outside of life, you also have run, you mentioned Green Tech Southwest, that's another community that you're involved with.

Hannah Smith: Yeah, that's right. So Green Tech Southwest, it's, it's kind of location based. The community at its heart is in the southwest of the UK. Anybody is welcome to come. All of our events are online. We've got another event coming up in May the 2nd, where we'll be looking at a methodology for measuring CO2 emissions.

And we'll also be looking at some really cool visualizations of renewable energy projects in the UK. So if you can't make it in person, if you're not based in Bristol or near to Bristol, you're very welcome to join online. And that is applicable to anybody, wherever you are in the world. You're super welcome to come and be a part of that community.

Chris Adams: Cool. Thank you for that. All right. I think that takes us to time actually. So folks, thank you so much for giving me your time and talking to, and giving this sneak peek of a project that's kind of close to all of our hearts, I suppose. And hopefully some of the listeners who get exposed to this, I guess all we have left is to say, thank you very much.

Have a lovely week and yeah, best of luck with the launch.

Marketa Benisek: Thank you. Thanks for having us.

Hannah Smith: Thank you, Chris. Thanks for having us along.

Chris Adams: All right. Take care, folks.

Hey, everyone. Thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please do leave a rating and review if you like what we're doing. It helps other people discover the show. And of course, we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again and see you in the next episode!

View Details

In this episode of Environment Variables, host Chris Adams introduces the co-authors of Building Green Software - Anne, Sara, and Sarah. Through candid discussions, they explore the process of writing about green software development and highlight key insights gained along the way, touching on the interconnectedness between sustainability and existing best practices in software engineering, and emphasizing that embracing sustainability isn't about adding extra tasks but rather integrating it seamlessly into existing protocols such as security, resilience, and monitoring. Join for a thorough conversation on the lessons learnt writing the newest book on green software.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Anne Currie: LinkedIn | Website * Sarah Hsu: LinkedIn * Sara Bergman: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Building Green Software [Book] [07:57] * Amazon.com: Building Green Software: A Sustainable Approach to Software Development and Operations

Events:* QCon London [30:36] * NDC { Oslo } [32:00]

Resources:* What Adrian Did Next: 2022 Conference Appearances [17:53] * https://github.com/adrianco/slides/blob/master/Carbon%20Moonitorama%202022.pdf

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Anne Currie: A lot of the best practice in sustainability is often also the best practice in other areas. So it's just one more good reason to adopt best practice in security, in resilience, in monitoring, you know, it's not something you're going "oh my goodness, mate, we have a whole extra thing to do." It's just another reason to do all the things that you should be doing anyway.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host, Chris Adams. Hello, welcome to another episode of Environment Variables, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. We talk about green software a lot on this podcast, but if you're coming to this from, typically, a background of software engineering, it can be hard to figure out where to go next after you've done some of the kind of free training or seen a few talks online. So, you might ask yourself, "how do you build green software?" Fortunately, today, I'm sharing a podcast with three women who've written a book called precisely Building Green Software. I'm joined by Anne, Sarah, and Sara. So, before we dive into this and talk about how you build a book called Building Green Software, I just want to give a bit of space for my co-host this week to come on. Anne, is it okay if I give you the space to introduce yourself and then hand over to the next of your little gang?

Anne Currie: Absolutely. Yes. So my name is Anne Currie and I am the CEO of a green training company called Strategically Green. And I'm also one of the co chairs of the GSF community working group, and I am the lead on the GSF's new Maturity Matrix project. So yeah, those things, and I'm one of the co-authors of building green software along with, and I will hand over to Sara.

Sara Bergman: Hi, my name is Sara Bergman, or Sara Bergman, Bergman. I never know how to say it in English because it's so different from the Swedish. But yes, I am a senior software engineer at Microsoft, even though I'm currently on maternity leave, hence why brain is not fully switched on, and one of the co-authors of the book Building Green Software.

Sarah, over to you.

Sarah Hsu: I've been waiting for that sentence for so long. Sara and myself have been working together, but we never really shared a stage. So Sara over to you, or Sarah over to you, has been our dream for a long time, and now it's finally happening. But anyway, hello everyone. My name is Sarah Hsu. Similar to Sara, my surname is actually pronounced very differently with an English accent.

So yeah, Sarah Hsu, it's fine. So currently I'm a site reliability engineer working for Goldman Sachs, but I'm also one of the co-authors of the Building Green Software book. And this is why we are here today. I'm also the project chair for the Green Software course that we recently launched with Linux Foundation a few years ago, and we currently have over 70 000 completion, which is amazing.

But yeah, anyway, that's me.

Chris Adams: Cool, thank you, Sarah, sara, and Anne. I'm saying hello from Berlin and Sarah Hsu, you're calling from London.

Sara, whereabouts are you calling from today?

Sara Bergman: I am in Oslo, Norway. So yeah, I am Swedish, but I live in Norway. This does not matter to anyone who lives south of Denmark, but for us Scandinavians, it matters a great deal.

Chris Adams: Cool, thank you. And Anne, where are you calling from today as well?

Anne Currie: I'm calling from London as well. So we're not quite as international as all that.

Chris Adams: Oh, well, it's not bad. Four different cities in three nations isn't, isn't too bad, I suppose. All right. Okay, so if you're new to the Green Software Foundation podcast, my name is Chris Adams. I'm one of the policy working group chairs in the Green Software Foundation myself. I'm also the executive director of the Green Web Foundation, a Dutch non-profit focused on reaching a fossil free internet by 2030. And before we dive into what it's like writing books about green software, here's a quick reminder that everything we talk about will be linked in the show notes on this episode. And because we're a software engineering podcast, the transcript will be available on GitHub in markdown format. So if there's any typos or there's corrections, then we do accept pull requests.

And if there are pull requests that are accepted, we'll then credit you and shout you out in the next episode. All right, then. So, itooks like you're sitting with us comfortably, Sara, Sarah, and Anne. Should we get into it and talk a little bit about writing green software and or writing about writing green software?

Yeah?

Anne Currie: Absolutely.

Chris Adams: All right. Okay. I'm going to hand to you, Sarah, first. If I understand it, this is one of, your first book writing about green software. So maybe you could just talk a little bit about how you found that process, writing about, say, a developing field like this.

Sarah Hsu: Yeah. It's my first time writing a book and it's also my first time appearing on a podcast. So maybe we can make another episode on this experience. I'm joking. So what was it like writing a book on green software? Honestly, I don't want to sound too cheesy, but it has been a really fulfilling experience.

And why is that? It's because finally I can use what I'm good at, which is software engineering, and use what I've been training for the past seven to 10 years to have a positive impact on the environment. And it just, it's great to see that ripple effect from something I'm good at and instead of just individual actions.

So I feel that really, really close to my heart. And of course that Anne and Sara made, they're not, they're more than just the icing on cake. They're absolutely integral to this entire experience. I've always admired them since I first met them three years ago. And working with them has taught me so much.

Yeah, couldn't have asked for better co-authors. And, and thankfully we all share similar humor. So when one of us put a joke or put a pun in a book, it doesn't get like, "this is not funny," cross it out. So I think that's also another icing on the cake. Yeah. But yeah, hopefully that's not too cheesy of an answer...

answer but

Chris Adams: No, it's okay. It's okay to be genuine if you've enjoyed working with other people, especially if you're doing something you believe in. Absolutely. All right. So that's the skinny from someone who's basically been writing books like this for a while. Anne, this isn't your first rodeo, you've written a few other books.

And I know that you, and we've spoken a little bit about all kinds of sci-fi books before, so maybe you could, I could just touch on you about maybe some of the differences between writing about wacky sci-fi or writing about things when you're, if you forgive the term, at the coalface of software development trying to figure out what to do next here.

Anne Currie: Yeah, that's a good point. So this is my tenth book, eight of which though were sci-fi, were futuristic sci-fi, but kind of like more speculative fiction than hard sci-fi. So it was all kind of surprisingly similar to writing an actual book about stuff that's happening now. But oddly enough, writing the fiction is much easier because you get to make it all up.

Whereas, although I try not to make it up, I try to keep it quite, quite, quite,

realistic. It's hard sci-fi, Yeah. but the book was much more difficult because the book, I mean, I think this is true for all of us. It was really important that we got everything right and we, and we phrased it right and we made it so that people could read it. Which I also want to do with my books, but they aren't quite so important, if you know what I mean. This feels like an important book, or we need there to be an important book, so hopefully this will be the important book, because if it isn't, then it'll be quite a long time before there is another one.

It's a lot of work, writing a book.

Chris Adams: I can definitely concur with that. Alright, so, one thing I didn't mention was that this was actually published by O'Reilly, who have some form writing about sustainability in this field. There was a book by Tim Frick, in the mid 2000s, called Designing for Sustainability, which was focused on web. But as I understand it, this has more of a focus on parts of cloud, perhaps, or some of the other practices. Sara, you've been working with cloud for a good few years now. Maybe you could talk a little bit about what actually the content covers inside green software, because it's quite a wide term and there are ideas like web for sustainability. Maybe you could just, maybe give a high level on some of the areas you focus on, then we can talk a little bit about how you folks work together remotely.

Sara Bergman: Yeah. Sure, sure. Yeah. So definitely if you run on cloud, we have a lot of content for you, but even for people who have their own data centers or on prem and you're allowed to call like a few servers in a closet, a data center, as far as we're concerned, there are definitely material for those people as well. We all come from a more backend point of view, but there is.

Web and front end content as well. Some of the points are on a much higher level than this applies only to you if you deploy to this specific type of machine. We tried to go broader, so it's really for anyone who writes or works in the software industry. Not just for, for the engineer, but for someone who is in a role that's not so directly linked to, to code.

We focus a lot on ops as well. So if you are on that side, there is a lot of good content for people like that. And that was really important to us. We come from slightly different backgrounds and we don't want to exclude anyone. That was one of the things we talked about really early on in the process.

You should pick this book up and feel like there is something for me here. And that's been really fun, I think, to sort of go broader than maybe you do in your regular, like, nine to five job.

Chris Adams: Okay. All right. Thank you for that, Sara. So, I now. If I may, I'm just going to touch on a couple of things that you spoke about there. You spoke about the idea that you're writing a book for a number of different audiences, so it's not just for people who are like optimizing code. It's not just about green code, there's maybe aspects of ops as well and things like that. And, given that you're not all in the same space, and given that O'Reilly has quite a, like, established kind of setup for writing books, maybe you could talk a little bit about how you wrote this. Like, was it like, you're using a bunch of GitHub together? Was it Google Docs? Or is there some kind of magic platform behind the O'Reilly firewall that you might be using to keep track of this stuff?

Because I've never, I've never understood, and we're a bunch of engineers here, or at least coders here, because I'm curious, I'm interested in it, and like, it seems a bit weird to maybe use like email versions of Word around to write a book about code, for example.

Anne Currie: Yeah, it was all Google Docs. Well, well, one of the interesting things is O'Reilly have a lot of different options for how you're going to do it. So they have a kind of, there are kind of GitHub integrations where you can do all through GitHub. But we decided to do it all on Google Docs because we were so remote. And in fact, we've only met all the three of us in person once before. So it was all, all had to be remote. So we would use Google Docs. And I think it went pretty smoothly. That was quite easy. I don't know what you two thought.

Sara Bergman: Yeah, I agree. And especially because all of us have been traveling at some point, or some of us traveled quite a lot, I've had, been very pregnant and then had a baby. And there are circumstances where you don't want to boot up a laptop and like sign into a Git repo. Like that's second nature to some, but sometimes it's very convenient to be able to do it from your phone at 3am, if that's when you have the time.

Chris Adams: All right. Okay then. So that gives us a bit of idea of like how the sausage was made, so to speak. All right, then. Anne, I'll put this to you first and then see who else wants to bite. Last time we were speaking, Anne, you were, we were talking about, I think, lasers from space as a way to power data centers, about whether that's a good idea or a bad idea. And I learned a bunch of things about there. So are there any particular things you learned about green software along the way when you're writing this book? Because you can't, you know, you can't be the expert automatically then, and it's a very, very fast moving field. So were there any things that kind of leap out at you or that you were surprised by as you were writing this, that you had to kind of change your opinion on or rethink perhaps?

Anne Currie: Well, probably my favorite chapter to write, which was, was the one that I had to do the most work on, the most research on, we only decided to add later on in the course of the book, which was the networking chapter. Because I was quite interested in what, how does networking fit into green software? You know, is it, where is all the electricity being burned?

You know, and I've, the, the most interesting thing I think in that was I interviewed a whole load of people and I did a lot of reading of papers and things like that to find out what was going on. And the interesting thing for me, I think was the last mile, comparing how good or bad, or green or ungreen all the ways means of connectivity are. So, finding out that that fiber is by far the best by a long chalk actually. So fiber is fantastic. So the backbone is pretty good. The Metro, which is what takes your data across cities, that's pretty much all fiber these days, it's pretty good. And The Last Mile, if it's fiber, it's pretty good to your house. That's the best, followed by Copper. Copper is actually pretty okay, if you're still, I'm still on Copper here, and don't, you know, don't feel too badly about Copper. But once you move into wire free stuff, then Wi-Fi isn't too bad, but 3G is absolutely terrible. 2G is terrible. 3G is better than 2G was.

4G is much better than 3G was. And 5G is much better than 4G. But one of the things that interests me about it is that the mobile generations are a classic. Something we talk about a lot in the book is Jevons paradox, which is the idea that as things get more efficient, you use more of them or to a certain extent, you don't use more of them because the, well,

they, you,

Chris Adams: The savings can be eroded by the increased amount of use in absolute terms. That's what you're getting at, right?

Anne Currie: Indeed. Yes. Yeah. And 5G, I would say is the classic example of that, which is it's much better than 4G, but you know, people didn't invent it for that reason. They developed the efficient 5G because they wanted us to be doing a lot more stuff on mobile devices, and we will use it. The whole point is for us to do more stuff on mobile devices, more mobile gaming. And so, yeah, 5G is vastly better than 4G, but it will drive massive increase in the use of mobile. And mobile is very energy intensive compared to a landline or Wi-Fi. It's different use case.

Chris Adams: So there's one thing I want to just check on before I kind of hand over to one of the... Can I say one of the Saras, or one of the... Sarahs, Saras, all right, yeah. I'll hand over to you if there's anything that you found surprising. So when you're saying better, you're talking about in terms of energy use per gigabyte transferred here. That's your use, like it's efficiency that you're referring to there, right?

Anne Currie: Bits per watt or watts per bit is the industry term for it. And it's something they really do focus on a lot. And the interesting thing is, yeah, I mean, obviously networking is there because everybody wants to do more networking. There's, there's so much untapped demand, which is a classic Jevons paradox issue, really.

Chris Adams: Well hopefully the fact that we've got a bunch of dark, do we still have significant amounts of dark fiber from previous dot com booms and busts where we've got all this stuff available for us to use? Surely that's one thing that we have been able to pick up on, right? Right,

Anne Currie: Well, yeah, there certainly would have been, but to be honest, the past is of no use to us really. It's all the stuff that's been, we're just still laying cable at an unbelievable rate to handle people's, the desire for streamed content.

Chris Adams: So there's an aspect of embodied carbon that we need to be thinking about as well then. So that's one of the things we've learned. Alright, I'll open the floor to, yeah, Sarah Hsu, in London. Are there any particular things that surprised you when you were writing this or caused you to kind of change your mind or think, "Oh. This is probably something we should be spending a bit more time thinking about," for example.

Sarah Hsu: Yeah, so we have a chapter called Core Benefits. And our initial idea was to basically examine green software from different perspectives in software engineering. We have like security, we have reliability, resilience we've performance, data, all that. But while we were writing that chapter, we realized, "hey, actually, this is all very important, but one thing that we're seeing is, because of what's going on around the world, there's so many other things going on. People really are not taking green software as seriously as maybe say 2021." So we actually wrote a chapter on like how we can help our readers to convince others that green software is not as difficult as it's thought out to be, and we came up with like a three bullet points on like how you can convince others. But most importantly, that we want to say in this chapter is that there are so many other knock on benefits from doing other best practices in software engineering already. Green software is not its own ivory tower, like people shouldn't be worried like, "Hey, like everyone is already so overstretched," you don't need to worry about. "Oh, now I need to have a whole new team just to work on sustainability." People who are already very skilled in security, very skilled in reliability, they all can help our software to be more sustainable. I think that's a really strong information we really want to send out there, especially to like the grassroots people and not fail them to be really helpless in the current climate.

So yeah, that's probably quite interesting realization we had later into the book.

Chris Adams: Okay, that's quite an empowering message, and that sounds like, there's a really lovely quote from Adrian Cockcroft, who's leading the Realtime Carbon Project, so he says like "carbon is another metric," and yes, there are other, obviously more metrics that you need to track, but it's not like people in software engineering have never had to measure something before.

So that's one of the things, like, obviously there's things about transparency that can help, but yeah, to an extent, there are lots of transferable skills that can be applied into this domain as well. That seems to be what I'm getting from you on that one.

Anne Currie: Yeah, I mean, I really liked your chapter that you wrote on that. You put something in, Sarah, about "it's not a new work stream." It's, you know, a lot of the best practices in sustainability is often also the best practice in other areas. So it's just one more good reason to adopt best practice in security, in resilience in monitoring, you know, it's not something you're going "oh my goodness, mate, we have a whole extra thing to do." It's just another reason to do all the things that you should be doing anyway.

Chris Adams: Okay, that's a useful framing actually. Sara, I, are there any things that you've learned, that you found, that you want to share, or that you would think would be salient for the conversation here?

Sara Bergman: Yeah, sure. I think, and that maybe goes back to the process is we interviewed people, a lot of people for this book and got their perspective. We also have amazing tech reviewers, and all those people have been very instrumental to the book as well. And, and that's something where I learned a lot from to reach out to people and how willing people are to help and contribute and share their expertise inside the community.

So the community is great. So that's not maybe a hard skill or a hard thing, but that's something that I really enjoyed about the process. And that's something I learned a lot from specifically around the hardware chapter, because I don't work with hardware every day. So. That was a lot of learnings for me.

And actually, I listened to previous episodes of this podcast, for example, the one about the Junkyard Data Center, which is very interesting to include as well as a way to combat e-waste and how big of a problem that is. And then you also get to sort of step outside your bubble and like, okay, but e-waste is surely something that concerns software people, but also other people.

And then you get to realize, okay, but there is lots of legislation around the world working to combat this. And like things are already moving in other sectors as well, which is really fun to see. And then you get additional knock on effects because industries and countries come together to work towards the same goals.

Chris Adams: Okay, all right. Thank you for that, Sara. So, we've, you've written about this, and the thing, you know, when you write a blog post, and as soon as you've done that blog post, you realize, "oh, there's a things, a few things I wish I'd couldn't have put onto it." I imagine it might be somewhat similar when you're getting a book out the door, because once it's out, it's not like you can push updates to a book the same way you can push updates, you know, hotfixes and things. And now the Building Green Software, the book has gone to print, are there any things that you wish you had a bit more time to kind of write about, or that now that you've seen it, go, you know, "oh yeah, we totally missed this," or "here's a thing we should, if I could do that again, I'd spend a bit more time writing about." Sarah, if I can, if I start with you, then I'll kind of go around and then we can round this up perhaps.

Sarah Hsu: I definitely had that same reaction, like two weeks before we were about to submit everything... And this is not a software product. We don't have a process on how to mitigate an incident. What if we wrote something wrong? How do we go about it? I remember just like panicking as well. But it is very interesting, like looking at publishing book.

And like managing a production system. But anyway, I think the things that really, I wish I probably spent a little bit more time on is like in the observability space, like, especially how not just in green software, but like the traditional monitoring metrics and logging really isn't doing what it's supposed to do in the modern software system management, right?

As our system gets more intricate, there's a lot more microservices. Sometimes like if you want to go from one hop, one request all the way for the request to come back to give you a response that can go through a hundred different systems, how do you know exactly where things have gone wrong? And I think I really wish I've spent a lot more time thinking how carbon and how environmental aspects will marry into this space and how do we actually make sure that we are not reinventing the wheel and once whatever metrics, whatever data we are ready, we can slot right into what the world of DevOps and what of SRE is already very good at doing, which is production system management, especially on how to make our system observable, if that makes sense.

Chris Adams: Yes, it does. So what I think I'm taking away from you is that we've got things like spans, and we've got ways to kind of understand the impact of a particular API request or something like that. But when you've got a distributed system, we don't have something like the equivalent to that right now for

carbon, for example. You can't track distributed carbon across all your systems to kind of sum it up.

Sarah Hsu: To find out exactly which system is the trouble one, like, I have a really good analogy. I was writing this the other day, like, you can think of, like, three different elementary data as like a murder mystery, right? Metrics will tell you when someone has died, right? And logging probably will tell you how someone has died, and traces will tell you where this person has died.

So we need to figure out how all these three things will match with, like, the environmental aspect. And hopefully we can have, like, traces that will tell you that's exactly where the bottleneck is happening within our system that, okay, system C.5 is the one that's emitting the most carbon.

Chris Adams: Okay, we're going down a rabbit hole here, but like, we already have all tools like Grafana and stuff like that that give that. Surely we can work out these numbers. This is like a problem that can be solved by,

Sarah Hsu: Yeah. Yeah. But we just need to make sure we are going in the right step. I mean, and not come up with things that ourselves, if that makes sense.

Chris Adams: yeah, that does, okay, all right,

Anne Currie: It is,

well, I'm going to say it is a bit, we'll just spend it, we'll blow all our time talking about this. We need another, we need another podcast to talk about the similarities and differences between carbon metrics and other metrics, because there is a key difference, which we can't talk about now because we're going to run out of time, but we should, we should have that in another podcast. The key difference between carbon metrics and other metrics.

Chris Adams: Okay, all right, that's definitely a thing to dive into, because it's easy to get focused on carbon, and it turns out, yes, we're in a climate emergency, but there's other things we need to be thinking about as well. All right, okay, so we spoke a little bit about what's on your lap next, I suppose, and Sara, you mentioned that there's a baby on your lap, or that's one of the things that you have and you're coming back to. Are there any, like, what happens next now that this is out the door? Because, as I understand it, the book, Building Green Software, is available digitally for people, so you could get it through Safari. But I understand there was quite an interesting approach taken about making this available to a wider set of people.

Does anyone want to take that at all, to talk about the kind of like open aspect of this book? Because this was something which felt quite exciting when I, when I first heard about it.

Anne Currie: Yeah, I'm happy to talk about that. So at the moment, the book is, it's available on the O'Reilly Safari site. So anybody who's an O'Reilly subscription, or if you're a fast reader, you can, you can trial an O'Reilly subscription and read the whole thing. But I wouldn't necessarily recommend that because the book's very intense.

I think if you just sit there and read it end to end, your head will explode. But so it's available on O'Reilly. It's available to buy from all good, well digitally, it's available on the Kindle at the moment, so you can buy it from the Amazon site. And in two weeks, I think it comes out in physical form, so available from all good bookshops. So you can order it anywhere you like and read it in real life that way. Or if you wait a couple of weeks after that, until we actually have time to go around and set something up, it'll also be available under a creative commons license, so under a, it's a, it's a fairly restrictive one.

It's the O'Reilly creative commons license, which is, so you can't take it off and then write your own book, you know, you can't, it's, but you have to attribute this and it's non commercial and it's, but you can read it for free.

Chris Adams: So, source available. You can read it.

Okay, that's, wow, that's really, really exciting then.

Anne Currie: Yeah. That will be available. I'll have it a copy up on my Strategically Green website first, probably.

And then we will, we'll see where else we put it as well. But yes, we insisted on that because it's just so important, you know, it's saying, "we hope this is an important book and it's really important that people read it."

Chris Adams: Great, wow, that's exciting. It's really useful to have something in the, so it's not quite public domain, but it's definitely available in the same way that you can have source available licenses that you can still benefit from and apply there. All right, then. Okay, so we spoke a little bit about some of the things we're covering inside the book, about how you can find this, and when it may be available, and some of the lessons learnt along the way. I've got a question, I have to ask now, like, what comes next, now that we've done that? Anne, I'll put it to you, and then, if anyone wants to take the question after that. So, Anne, you've written a book, or you, plural, have written this book now. Do you just sit in your laurels? Do you just like wait for the royalties to come in or does something else happen after this now?

Anne Currie: If only, if only we could sit in our laurels and wait for the royalties... I don't think writing a book is something you, you ever, unless you're J. K. Rowling, you never really make a, maybe, maybe a film wouldn't be made from this book, but I suspect that's not the case. So, yeah. So the next thing I'm doing is a whole load of training around this, this stuff.

So I'm, I'm doing that through Strategically Green. So started to do some public training and, and one of the things that I'm doing in the public training is, it's focusing on the thing that I would have liked to have put in the book that I didn't. Which is that it's not all bad, you know, there's just enormous benefits.

And one of the reasons why we don't have a whole chapter of like, "Oh my goodness, mate, this is amazing. Why aren't you just stopping and dropping everything and converting your systems to run on renewables? Because it's, you're crazy not to" it's because I don't think a year ago when we started, 18 months ago, when we kicked this whole thing off, that was the case. It wasn't so obvious that renewable power was, was the win that it is becoming. I mean, if you look now somewhere like Spain and Portugal, I'll pick them rather than Scandinavia because Spain and Portugal were doing it the total new tech way. They're doing it with, it's all wind and solar. They're now even in the winter this year, they've had huge, they've had large numbers of weeks when power has been free for the bulk of the business day. So, you know, it's kind of like, this is the dream of humanity that, you know, through, through the ages that we would have effectively free power. And it's looking like that is a possibility, but we will need to change our systems to run on top of it because it's not all the time it's variable. And that's kind of the key message of the book.

But I wish we'd hammered it home a bit more, the wins.

Chris Adams: Right, I'm going to put the question to Sarah Hsu next, but just before Anne, I just want to check on that. When you're doing some research for this, we know that the power, the cost of power changes depending on how available it is. Are there any cloud providers who are making that visible to people yet? Because have you found this? It feels like it's the obvious thing to have to incentivize the use of green power, but it's almost nowhere so far. And maybe you, you might've come across this as well, or maybe the big providers might do something like this because they clearly are making significant decisions about this as well.

Anne Currie: No, I don't, nobody is, but I have spoken to people at most, apart from Google, who speaks to anybody, nobody speaks to anybody at Google, but I've spoken to, spoken to folk who don't necessarily know and have no ability to affect it, but they are aware that eventually we know that the clouds will provide dynamic tariffs. There's no doubt about that because everybody's going to have to provide dynamic tariffs at some point. So, you know, I don't believe that anybody does it at the moment, but I think there's no doubt that it is coming.

Chris Adams: Okay, so not from the big guys, but it's something available coming from somewhere. The one company I've found that is doing this so far, there's a company called TriBuild AI. They're doing this in, I think they're based in Texas, and they're strategically placing things, but the idea is that you can use the power, but not between 6pm and 9pm, when everyone's using power, and that's how they make it like a fifth of the cost of everyone else.

So we are seeing early signs of this, and like, there's examples everywhere outside of technology that we could learn from as well. Okay, all right then, so Anne, that's what you've got on. You've got the maturity matrix to kind of maintain, and the training that you have going on. Sarah Hsu, if I hand over to you. And now that the book's out the door, what do you think happens next? Or what's, what's on your plate after this?

Sarah Hsu: Well, I'm just speaking for myself, but I'm pretty sure all of us are going to be rock stars and go on a tour, go on a speaking tour and book signing tour. So yeah, I think Sara and Anne are doing QCon in April and myself, I'm not speaking this year, but we will be doing like a small book signing there. So it'd be great to see a few folks there.

Myself, we'll be going to Berlin for a conference and then hopefully we'll do some book signing there as well. And one thing I really want to do is I just want to find some observability for who is also really passionate about sustainability and just see what It's just really, really chat it out about like how we can do all this is within observability.

How do we actually make something observable in terms of carbon or like any environmental aspects if that makes sense.

Chris Adams: Yes, that does. If you are not already speaking to some of the CNCF TAG ENV folks, I'm really excited about some of the work they're doing, and they've recently presented some stuff at KubeCon specifically about the observability thing that it's definitely worth chatting about, actually. Okay, and so,

Sarah Hsu: Yeah, definitely.

Chris Adams: And Sara, I'll hand over to you now. What, now that this is out the door, what's on the plate for you, now that you're coming back into the world of, like, software engineering, as opposed to looking after the little one?

Sara Bergman: Yeah, out of the diaper. Well, I guess there will be still be diapers for plenty of time, but yeah, no, going back to work and then being a rockstar going on a speaker tour, like Sara said, so QCon London, which will be very fun. This is the second time only all of us see each other like in person. So very much looking forward to that.

Speaking at NDC Oslo later this year. Also, the Green Software Foundation has a meetup in Oslo, which is very fun. And next, next one of those, I'll be speaking as well. So that would be really fun to like see folk on my own home turf. And yeah, after that, who knows, you know, this was so much fun. Do we do a version two?

I, you know, we'll see. Right?

Sarah Hsu: I think we should, I forgot to mention, we've actually have the book translated to both complex and simplified Chinese. So that's something very, very exciting. I was telling one of my best friend, my best friend was like, "Oh, now your parents don't have an excuse to not read your book," because now, my poor mother will now have to read this book.

Chris Adams: Wow, I did not, that's, that's, well, it's more than a billion people. There's a, there's a readership to, to reach, and people who speak Chinese as a first language probably need to be thinking about the environmental impact of software as well, given it's the second largest economy in the world now, basically, so we've mentioned there's a growing body of resources out there for people to be looking at this. So we mentioned things like, say, some of the free training that's available from the Linux Foundation that people can pick up. And there's a book which we've spoke about, which is Building Green Software by O'Reilly that is going to be available from a number of different places. So Anne, if people do want to, obviously they know about the book, but beyond the book, where should people go if they're interested in what you were talking about or some of the things you're working on?

Anne Currie: Well, at the moment, LinkedIn is, I find, is the new place where all the green chat is happening. But yeah, yeah, LinkedIn. It was lovely whilst Twitter still existed as a thing, and I'm still there,

Chris Adams: drove it into a mountain, yeah.

Anne Currie: Indeed. It was, yeah, I'm still there. I still find useful things there, but it's not as active as it once was.

So LinkedIn is now my social media hangout.

Chris Adams: Okay, alright, and then Sarah Hsu, how about you?

Sarah Hsu: Similarly, I was never really on Twitter and I'm really glad I have persuaded Anne to move over from Twitter to LinkedIn. I also just can't I do want to quickly mention, we do have an email address that you can reach out to all of us. It's building.green.software@gmail.com. So if you have any feedback, any suggestions, or just want to say... please, please, yeah, just reach out to one of us.

Or if you want more direct response from one of us, reach out to us on LinkedIn.

Chris Adams: So if you're a retired engineer and you're going to tell people "you should be solving this all with nuclear," obviously, that's the way to, that's the place to send emails to. Okay, alright, please don't do that, actually.

And, Sara, for you, where should people look if they want to keep up with some of the things you're working on?

You mentioned QCon and a few things like that, but if there's a particular URL or website people should look at, then, now is your chance.

Sara Bergman: Yeah, I'm also, also on LinkedIn, missing Twitter. I still hang around, or X, I guess it's called now, and feel sad about what it once was. But no, LinkedIn is the best place.

Chris Adams: All right, then. Well, folks, thank you very much for sharing your time and sharing some of the insights you've learned along the way of building basically the first book about sustainability and stuff which wasn't written by men, because that's actually like about freaking time. That's very, very good. And yeah, lovely seeing you all again. Hopefully, maybe I'll see some of you in London if I get over there or possibly some of you see some of you in Berlin if you're coming over and maybe wonder if you might sign my copy if I can bring it. All right. Thanks, folks. This was fun. Really, really nice seeing you all again.

Sara Bergman: Thank you, Chris.

Anne Currie: Thank you.

Bye bye.

Sarah Hsu: Bye guys.

Sara Bergman: Bye.

Chris Adams: Okay, take care of yourselves. Hey, everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please do leave a rating and review if you like what we're doing. It helps other people discover the show. And of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundationon. That's greensoftware.foundation in any browser. Thanks again and see you in the next episode.

View Details

In this episode of Environment Variables, host Chris Adams engages in a fascinating discussion with Marjolein Pordon, a quality consultant at Praegus, about the exciting synergy between sustainability and low code platforms. They explore how low code tools not only streamline software development but also play a crucial role in reducing carbon emissions. Marjolein shares insights into the early integration of sustainability considerations in the development cycle, and together, they demystify the misconception that companies' unique needs necessitate custom software solutions, highlighting the efficiency and environmental benefits of leveraging shared components in low code environments.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Marjolein Pordon: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Introducing Flowty - Build low carbon, self-hosted Webflow sites - Fershad Irani [23:22] * Data Center Factsheet [29:36]

Resources:* Introduction to ESG [11:51] * ESG and Climate Change | Coursera * Mendix [14:32] * WordPress [14:39] * Zapier [14:49] * Creatio [14:50] * N8N [15:39] * Windmill.dev [22:42] * OutSystems [34:15]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Marjolein Pordon: With all the emails we send, inclusive, reply all, the, "yes, I'll see you in a minute." All those kinds of emails, there are 12 000 times from earth to the moon with a car on carbon emission. That's huge.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello, and welcome to another episode of Environment Variables, the podcast where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. When we talk about green software, we often talk about optimizing code we already have, or finding out ways to make the energy we use less carbon intensive.

So for the computation we do end up using, we end up with less pollution in the form of greenhouse gases and so on being emitted as a byproduct of our work. However, there's another way to look at this. If we accept that the most efficient database query possible is one that you don't have to make because you've designed a system not to need them,

then you can argue that the most efficient system can be one that you haven't had to spend loads of time, energy and money building, building an entirely custom version of, because you found an existing set of components that work well together. This is essentially the argument made when people make the case that a technology stack containing open source software can be more sustainable than a closed source one.

In that the cost gone into building the various components is shared across all the millions of people who would otherwise be duplicating all this effort, building their own versions of these open source, the components. But does this apply elsewhere as well, though? Low code and no code environments have grown in popularity over the last few years, and one argument in favor of using them is that by building the system, or building any system from a set of existing components offered in a kind of visual, low coding environment, you avoid the need to spend so much time, money, and yes, energy, building your own custom software in the first place.

This brings up all kinds of interesting questions. Does this just mean that we end up with more software in total, because more people are building their own software, rather than a relatively small number of professional developers? And are the needs of organizations so sufficiently generic that you can use low code environments for this kind of stuff, to avoid needing all that custom code?

And if you're stuck using providers who are moving slowly to transition from fossil fuel in their infrastructure, what are your options? With me to explore these ideas today is Marjolein Pordon, one of the few people I've seen talking about both sustainability and low code at the same time. Thanks for joining me today, Marjolein.

Marjolein Pordon: Thanks for having me, Chris.

Chris Adams: Okay, you're welcome, Marjolein. Can I give you a few minutes to introduce yourself and what you do? And because you're the first Marjolein I've ever met, if I'm mispronouncing your name, could you please just share the pronunciation so I can use it properly when I'm later on the call? Because I'm trying my best, but you're the first Marjolein I've ever met.

Marjolein Pordon: Yeah, Marjolein is a Dutch name and you're pronouncing it correct. It's like Mar and then Yo from the rapper, Yo Yo, and then a line, like a thin line. So, Marjolein, that's, that's completely correct. Well, I'm Marjolein Pordon. I'm, 38 years old. I live in the Netherlands and I'm a quality consultant for the company Praegus. Praegus is a test consultancy company, and we also have a branch that looks into low code. And one of our CEOs is very much into sustainability. So I'm really in my place there. She also thinks that we should move to an office with sun, sunlight energy, and wind energy. So it's not just me, but also in the company I work for that we have these standards and I'm now, I think eight years in the business and I really love working in IT, testing and things like that.

So yeah, I'm really happy to be here. Oh, and within low code, I've had a few assignments in low code and it got me the name, nickname Lady Low Code, because I'm so passionate about low code and talking on conferences about it.

Chris Adams: I'm glad you mentioned that actually. First, for the breakdown of Mar-yo-line, that's very easy to understand, but also having an alter ego like Batman is also very interesting and useful to have. And that makes it really easy to find as well for the website. That was one way that we came across you actually.

So, and you mentioned a couple of things that were quite interesting there. So, oh, let me just quickly introduce myself for people who've never listened to this before. So my name is Chris Adams. I am the executive director of the Green Web Foundation. It's a Dutch-based non profit focusing on a fossil-free internet by 2030.

I also work as one of the policy chairs for the Green Software Foundation's policy working group where we basically do work at the intersection of policy and green software. If you are new to this podcast, folks, we will share a transcript of everything and we also, we cover, we mentioned quite a few projects and we'll be listing those in show notes.

So we'll share links to that at the end of that. So if you're listening and there's something caught your eye, please do take a look out for that, because that's one thing that we have available. Finally, okay, back to the podcast. Marjolein, I think you're sitting comfortably?

Marjolein Pordon: Yeah, I am.

Chris Adams: Excellent. Okay, so you mentioned that you didn't always work at this intersection and you worked in a couple of fields where you might specialize, before specialize in this niche, and you said that they've kind of influenced your thinking today, like, could you maybe elaborate on some of that?

Because you spoke about, say, testing and stuff like that, and we know that some of the tools people use for testing end up being the same tools you might use for driving certain activities, driving a browser and stuff like that. So yeah, maybe if I just give you a bit of space to expand on that, then that might help listeners understand some of the connections here or how you got here.

Marjolein Pordon: Yeah, I started as a software tester in 2017. My boyfriend is also a software tester and he said, "yo, you, you would be perfect for it." I started on high code, traditional projects, worked there for, I think, a year or two. And then in 2019, I was available for new assignments and I get really obnoxious then because I don't like doing nothing.

So then a coworker said, "well, you can fill in for a week and a half, it's low code, it's easy. Just do your thing." And then it seemed to be not so easy because low code platforms have standards. You need to use them as required. And people didn't do that. So instead of a week and a half, I was there for a year and a half.

Yeah. So, and then I noticed that if you use low code well, the reusable components make the time to market quicker, but also your energy use lower. And the platform that I was working on then, also now doesn't refer to itself as a local platform, but a sustainability platform, because they say even more important than a quick time to market is that we even can go to market.

Because in the Netherlands, we see that the energy use is that high that companies are not allowed to be connected to the energy network. So that local platform said, "we need to change our way of working, because if we do not do that, we cannot make new apps. Because they're simply not the energy to do that, we'll be cut down.

So we need to do this something. And if other companies don't, then that's up to them. But we make the change because we see that it's necessary for the environment." And I really like that. So I got passionate about low code on the one side and sustainability became a thing. And then in 2022, I was asked for QA&TEST to speak there on green IT. And then I got in contact with professors in Spain and in Portugal, not only on sustainable green IT, but also on the connection with low code. And, well, it got me convinced that we really need to do something because it's, it's scary how much energy resources we use, but also hardware resources we use, because if we make quicker apps, heavier apps, we need new hardware, but we are losing also those resources.

So we need to change the way of thinking and low code, I think, is a good way to help us change the way we feel and think about software development.

Chris Adams: Okay, that's actually... so you said a couple of quite interesting things that I haven't heard people mention before. One of the first things you spoke about was this idea that, okay, given the fact that there's, there are limits that we need to stay inside, the thing we need to do is actually, if we're going to increase the kind of utility of the services we need to do, then we need to make them more efficient.

So we did, a couple episodes ago, we did one all about multi-tenancy, about the idea of like multiple people sharing the same platform and using it in a more kind of efficient way, rather than having the equivalent number of like multiple separate platforms which aren't used very much. And it seems like you're touching on some of those ideas there, because this is actually the first time I've heard groups actually take the kind of limit thing more quite seriously, because you often see folks talking about, "okay, well, we're going to make things more efficient."

But if you look at the large providers, say, Amazon, Google, and Microsoft, all of these providers seem to have plans to massively increase the energy use they're using. So this is actually quite a different approach that you've been laying out here. It's like, "well, actually, we're going to use efficiency to kind of book those savings rather than just use it to sell more stuff" basically. Okay. And that was actually quite cool. And the thing that you also mentioned as well was this idea about the testing aspects. Now, I think that there's a term that we spoke about before in the kind of preparation session for this. You mentioned this idea of like shifting left. So, there are things that you would do when you're a tester to make sure you can meet a set of standards.

And it seems like, there's maybe some ideas about applying those things as part of a kind of process, so that you kind of maintain a certain level of efficiency or a certain level of accessibility or sustainability as well. Maybe we could just expand on a little bit of that before we move to the next point.

Marjolein Pordon: Yeah, because if we look to, to testing, usually we come at the end of the development cycle. The things are made and then we test it and then we say, "well, we trust this to work or we not, and" then it needs some rebook. But what we believe as test consultants is the sooner we, the earlier we are connected, then we can think ahead.

We can look to the requirements, but, and not only about the product, but also about the sustainability. Because if we create awareness with the developer. How to make his application more energy efficient, it's better to be done before he starts building. Same with the product owners and the designers and the architects.

They are the ones that should design the system to be energy efficient. And if we all work together and if I as a tester know what they have done, then I can also check that. And it's going to be important because at least in Europe, we have the ESG legislation. And what I hear a lot is that small companies say, "Oh yes, but it's only for the big companies."

Is it? Because if you supply to a big company, you're part of the chain.

Chris Adams: Yeah.

Marjolein Pordon: and you need to also document and let know that you are efficient. And it could be that you lose some big clients because you do not have the things that they need for the legislation.

So

Chris Adams: Yeah, I see.

Marjolein Pordon: So, in the whole chain, we need to shift left.

We need to use sustainability as a nonfunctional. And it works broader than just environmental sustainability. Because on the marketing part, we all know that, especially the youth want a better world. If you want those as your clients, and they're gonna grow up, they're gonna work in companies, you need to be green, then you need to show that you care for the world. So, it's not just that you save the planet, but you also save your brand, you save the way people look at you, and you make sure that you are there in a few years.

Chris Adams: I see, okay, so you're referring to like, essentially retaining talent and actually attracting people who are basically looking around and thinking, "hey, we should probably be doing something on this climate thing." And if a company is not kind of living those values, that's going to make them think twice about even, "should I join this organization?

Should I choose to work in this field?" And so on. Okay, thanks, Marjolein. Okay, so we've spoken about low code and no code, and you mentioned that there's like one, you're working for one provider. Maybe it might help to just get a bit concrete, because it's quite a wide ranging term. So when we talk about things like, say, low code, maybe we could talk about some of the kind of better known services, so people get an idea of what they might look for.

So what is, like, a low code system in this case, or who are the companies that do this kind of stuff, perhaps? If you could talk about that, and then maybe we might see if there's any open source equivalents that might be useful for developers who are listening, or people who might want to take some other steps into this field.

Marjolein Pordon: I'm not connected to a particular platform. I have worked, I think, with five platforms, but as an independent tester, what we see is you have different kinds of low code. So some are in the workflow management, you have CRM systems. Webpages, ERP systems, all based on reusable codes and those can be modular.

So like Mendix likes to call drag and drop.

I have a component, I drag it and put it in. WordPress works the same way, but then you build a website. Those like Workflow and Aden, I think is a one, and Zapier,

Chris Adams: Mm.

Marjolein Pordon: and for CRM you have Creatio, and all that I mentioned are open source tooling. And I think that's important because like you said, if you share that knowledge and share those, that code, people don't have to make it their own and they don't have to invent the wheel again.

That's I think important because you don't have to know everything. You need to know where to get it. But also, the energy efficiency and the environmental impact is way lower if we reuse code.

Chris Adams: Okay, thank you for that. So to reiterate, so when we're talking about low code and no code, we might be talking about, so you mentioned a few platforms that people may have heard of. So one is Zapier, which is very, very common that will basically plug into an existing software as a service and then let you make a transform.

And then, and there was another one you mentioned, which was N8N, which is a little bit like a kind of open source, well, open source like equivalent. I'm not sure if they're technically using an open source, it's more like source available, but the general idea is you can run it on your own servers, so you can have a similar idea of pulling information from one place and having little bits of javascript or something like that you run there, with the idea being that you have multi-tenancy, lots of people using the same things, because you'll need a little bit of code rather than having a whole running one.

And you also mentioned that Mendix, which is a more visual option, and, okay, and some of them which are more specifically tied to an existing, say, enterprise system or something like that. Okay, thanks for that. Okay, so we spoke a little bit about, in the intro, some of the arguments people use about where low code might fit into this kind of, into this world of green software and reducing the total resource requirements of, of anything like this, and we've spoken about the idea of lots and lots of people using, say, shared low code.

Shared components in a centralized service. Now, this implies that lots of companies have problems which are similar enough to each other that you can actually solve something like this. And when I've spoken to people in various organizations, they often, one, a common kind of theme is, "oh, our stuff is so unique that the only way we could possibly do this is by hiring a really, really expensive specialized developer because only they, only they could possibly capture the uniqueness of our organization." And this seems to suggest that's not the case. Maybe we could talk a little bit about that, like, is it that companies are over indexing on how unique they are, or where does this fit in, or are there some parts that you can do, but there's still places where you might need a specialist, for example? Maybe you could kind of share a little bit about that, actually.

Marjolein Pordon: Yeah, well, it might not be a popular opinion, but I feel that companies need to convince themselves they're unique because how else are they going to stand out? And what I see with companies that embrace low code is that they say, "well, we choose to look for the components we have in common with other companies. And if we build those components, those modules, those parts that we need in low code, we have time left, we have money left, we have expertise left to build those few things that are customized." So we all know software projects takes ages, deadlines are never met, but what if we use those components that are alike, because every company has parts that align. If I sell something, I need a cash register.

I need a website, all those things align. And if I need a small part that's not aligned that I want different from my competitors, then I can build, let that build by that said expensive developer. But that developer only has to do that little part for maybe a week or two weeks. And the rest is built in low code.

It's energy efficient. I save money. I save time. And I invest for just those parts that I really want to stand out in. And it can also mean that you think that you're just like everything and you build everything in low code and what you save in money, you can add to invest in your company, add new products, do your marketing. So there, the, the low code embracers, I feel say, "yes, we are unique, but we use what we have in common to do in low code and what we do not have in common and stand out, we invest in that."

Chris Adams: Okay, I can follow that argument now, actually. And there's maybe one question I have for you, is basically how these platforms are built, because usually, like, rather than paying to have an entire server or something like that, you might pay for kind of per use, and this is like an argument people make with serverless computing is like if you're paying for the requests or you're just paying for the amount of computation on a kind of per second basis, then you have an incentive to reduce the amount of computation you're using because you have it linked much there, there's a much clearer incentive for you to do this.

Are, is this common? Do you, are there, is it fairly common for, say, low coding tools to bill for, like, provide granular billing in terms of, like, a request made or a kind of run or a workflow? Like, what are the units that people tend to use when they're looking at something like that?

Marjolein Pordon: The bigger platforms I noticed have trouble or are not quite there yet to do that. But there are smaller platforms who say, "well, this is the way we do it." And I think that that's creating of awareness. What does my system do? Because I pay for it. And we all know money is a big, big incentive to say, "Oh, wow.

Why am I doing this?" And when I did my, my talk in 2022, I did some research and what I noticed is what we do in social media every day. And I had a thing that if the miles from earth to the moon with all the emails we send, inclusive, reply all, the "yes, I'll see you in a minute," all those kinds of emails, there are 12 000 times from earth to the moon with a car on carbon emission.

That's huge. Every single day by every mails we send and that are sent. 12 000 times, so 6 000 times to the moon and back again every single day. That's huge. When I knew that I was going through my newsletters, which one am I reading? Actually reading. Not reading? Sorry, I unsubscribe. And that's only maybe a hundred emails in the year, but still it's a hundred less. So that was for me an eye-opener. But if I had a bill every month of a hundred euros because of emails that were polluting and that I wasn't even reading or even opening,

Chris Adams: Then you're going to think about that,

Marjolein Pordon: then the awareness would even bigger. So I think that's it. Yeah, so I think that the platforms that are doing that billing are really good. Because that's the best way for awareness.

Chris Adams: Okay, all right, thank you for that. That makes sense, and there are a few cases that, a few of them, I do believe, expose some of these metrics to you like that. At climateaction.tech, one of the communities I run, we use N8N that provides some of this for some of these things, and I've seen similar things with windmill.dev, which also gives some of these, exposes some of these numbers. So we spoke a little bit about the efficiency part. There's also one thing that came up, is, okay, if you're using one platform, for example, there's going to be there'll be things that you cannot change because they are kind of with the provider's decision.

For example, if you're, like one example I can think of is, there's a service called Webflow. This is a kind of low code tool for designing websites. And they run on AWS, who for the last few years have been less ambitious on climate in terms of greening their own supply than say Microsoft or Google, based on like the things that we see in the public domain, for example, and I know there was one example, there was a project called Flowty by a chap called Fershad Irani.

One thing, one thing he basically did was he looked at where you could do this, and because the thing that gets built is maybe a, say, a static website that's created by Webflow, he was like, well, if you've got this, maybe you can move this to a greener provider, for example, and, or maybe you can apply some kind of digital sustainability techniques to reduce the size of the page and do things like that, right?

Now, this was one example of like a low code service, which was like, if you're going through maybe Webflow, for example, you're tied to kind of infrastructure which where, the people providing that are not as ambitious as some other groups, for example, so you're kind of stuck there. There are cases where there are options.

So you can say, "well, I like what you're using, but can you move to another provider?" Or, "If you don't do this, then I will move to another provider" themselves. Maybe you could talk a little bit about like what your options are if you are using some of these tools. Because one of the things I've heard people say about no code or low coding tools is like, "yeah, they're great, but now I'm stuck inside this specific environment where I have no other way of moving away from that."

Maybe you could touch on what are your options if you do want to ask your provider to improve the sustainability further down in the stack, for example?

Marjolein Pordon: Well, what I noticed is one of the big platforms, Mendix, has made it a big issue. And that's because a lot of their clients pushed them and then the majority counts. Then they need to do it because they don't want big clients to walk away. Again, they are part of the chain of big companies, so the ESG legislation is probably also haunting them, which is good. But yeah, vendor locking is a big issue in low code because for example, I have an application built in Java, C#, whatever. The developer that I have or the service that I use or the company that I use, I don't like, we have issues, we part. And I just hire another Java developer, but if I do not like the platform, same with if I wouldn't like Excel or if I wouldn't like Word, everything that I did in there, I need to migrate. And it's not easy. I mean, I could open things in Google Docs, if I went from Word to Google Docs. But still, I could have issues with the outline, with the layout, things like that. So migrating from one platform to another is not easy. And the integration with platforms, like if I had used one platform and then I think, no, I don't want it, but the application can stay there, but I built something new in another platform. The connection is, is really hard because I always say, Lego wants you to use Lego and not K'nex.

So, and maybe you can connect K'nex to Lego, but it won't be easy. It won't be good on usability. So yeah, the vendor locking is definitely a thing. So before you start with a local platform, wherever you need it for, do your research search on, "is this the platform I want now and in the future?"

And not only on, "does it work for my company," but also "what legislations are coming, are they sustainable, what is my client group wanting?" Things like that.

Chris Adams: Okay, so there's not just, so there's, you're talking, there's almost like some, a case of about alignment you need to be checking for, but also kind of influence you might have as well as actually just saying, is this really convenient for me right now, for example. Okay, all right. That's actually quite helpful.

The one thing I can share with you when I was looking through this that other listeners might find interesting, especially if they are developers, there's, we've come across some tools which are open source. They provide kind of low code like environments, but they also allow you to kind of drop down into your preferred programming language.

One thing I've really been quite impressed with is one organization, one project called windmill.dev. So it's an open source, kind of low code platform, but it's more like a... it's a platform where you have visual ways of working, but there's also a way that you can drop into pretty much your own language, or use any kind of docker container.

And that, because the actual platform itself is open, that's one thing, but also the fact that you can drop down into languages that maybe developers might be familiar with, means that you, that reduces some of the lock in to an extent. And I think that's actually quite a promising path to go down, because yeah, you, have that separation that we know in other, in other kind of sectors.

Having separation of different layers does allow for you to have more options on the table. Okay, so can I, if I can, can I just come back to one thing that you spoke about before? Because I was really surprised, and actually quite impressed by the whole thing about saying, "well, okay, we're going to use this as a, as a absolute limit in energy we can use.

So the only way we can do this is by increasing, if we want to grow, then we need to make more efficient use of this rather than just say, we're just going to keep growing as fast as we can, and we're not really going to think about the resource requirements." So we spoke about this idea of, and this is one thing, an ongoing discussion in green software, which is about basically growth and the idea of the rebound effect.

Are you familiar? There's a term called the rebound effect, which basically refers to this idea that if you make something more efficient, you can increase the total usage of this just because it's become more accessible to more people. And one of the key things around tools like low code is that yes, you're democratizing access to computation, but it also increases the number of people who might be making systems as well, which can have some similar effects.

So maybe you could talk a little bit about the conversation and how you've seen that evolve in the Netherlands specifically, because that's somewhere where you have seen, like moratorium on new data centers being built, which has meant that you've had to, it's forced some of the conversations that are probably not happening quite so quickly in other parts of the world.

And this was, yeah, you brought this up at the beginning of the podcast, so it feels like it might be worth just spending a bit more time looking into that.

Marjolein Pordon: Yeah. Because if you look at data centers, we have, I think, three big ones in the Netherlands. And the one I think in Lelystad uses as much energy as the whole of Amsterdam. That's huge. One data center takes up the same amount of energy as the main city of our country. And that's huge. That's crazy if you think about it, because we cannot build at the houses we need at the moment because of the nitro legislation, because there's not energy, there's not enough water, and those data centers use water and energy of a complete city. So if we do not have that data center in the Netherlands, then we could build a complete city of Amsterdam. Think of all the houses we could build. So this is quite a discussion in the Netherlands. Arjen Lubach is a guy who makes, is a television presenter, and he makes those kind of reports on this.

So also to make us aware, because they are built for a part with our money from the taxpayers. So we are aware that it gives jobs, a data center. We need it and that it's good for Google and AWS to be here, but they're not energy efficient. And well, one of the politicians said, we need them to give back because they're here in the Netherlands,

they use, okay they pay for the energy and for the water, but they need to give something back also for sustainability. And what we now are looking into is that they heat water to cool down their data centers. But we could use that water to heat cities with city heating. So then we, then they should make sure that there are pipelines to the city next to the data center. And then the warm water from the data center can flow through the houses and heat them. And then when the water is cooled down, it can go back to the data center and then you have the rebound effect and you can reuse the hot water to heat the houses and the cool water can go back to the data centers. And data centers said, "no, no, that costs too much money." And we are in the Netherlands now working on a legislation that will make sure they have to do that. If you want a data center in the Netherlands, then you need to build it, and you need to build the system to heat houses. And I think that's good because then you're cooperating, then you're working together and making sure that we need the data centers, but they can give back and work together so that we can still have a better environment because if we go on like this, they had, I think, requirements for 2030 in the Netherlands. Well, we're not going to meet them. And then they said, "well, no, but we'll make them in 2040." Yeah. And in 2030, you'll say 2050. We need to do something now. And I think that by making this happen, saying to a big company like Google, "fine, you have your data center, but these are the requirements or else." It's just necessary to do this.

Chris Adams: Okay, that's a very different take that we've seen in other parts of the world when discussing this actually. And what we can do is we can share some links to some of those points because I haven't heard those stats and those numbers presented in that way before actually. Marjolein, I just want to check up.

So we've spoke, we've covered quite a lot of ground. We spoke about like low code and things like that. If people do want to, if they found some of this interesting and they are, they're looking to take some of their first steps into low code, into the set field. Could you maybe just like suggest a few places where people should be looking to either get either learn in their own time with some like training or if there are any particular projects that you would want to draw people's attention to for this?

Marjolein Pordon: Well, for the low code part, most applications have their own playground and learning environments, which are quite good. So I would start there on the low code part. There are not many general courses on low code, but I'll check them after we're done with the podcast and then I'll, we'll add them to the show links.

Chris Adams: And if there was maybe one platform people might work with or start with or is there one that you would suggest people take some of their first steps with for example or something like that if they're coming in to begin with they just want to start kicking the tires and trying it out, for example?

Marjolein Pordon: Well, I would start with like a Mendix or an OutSystems or things like that, where you have a lot of information and a community behind so that you get the hang of what is low code, what are the standards that you need to work with. And if you have done like one or two of those, then you see the common grounds and then the other platforms will be a lot easier.

Chris Adams: I see. Okay. All right. Well, Marjolein, thank you very much for that. If we're just coming to the end of our time now. So if people have found this interesting and they want to follow what you're doing, where would you suggest people look? Is there a website or is there maybe a pro, is there like, where, where are you online for people to follow your updates and see what you're, see what you're doing going forward?

Marjolein Pordon: I'll follow LadyLowCode at my tag at Instagram and Twitter is @LadyLowCode. LinkedIn is Marjolein Pordon and my website is www.ladylowcode.com.

Chris Adams: Brilliant. Okay, well, Marjolein, thank you so much for giving the, making the time to chat with us today. As we mentioned before, we'll run through this to make sure we've got show note links for all the things that we discussed here. And yeah, have a lovely week, all right? Take care, Marjolein.

Marjolein Pordon: Thank you, Chris.

Chris Adams: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundationon. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode!

View Details

In this episode of Environment Variables, host Chris Adams delves into the fascinating topic of the rebound effect with Vlad Coroamă, founder of the Roegen Center for Sustainability. They discuss how improvements in efficiency can sometimes paradoxically lead to increased consumption, using examples like teleworking and online shopping to illustrate the point. Through their conversation, they explore why this happens and what conditions make it more likely. Their insights shed light on the complexities of balancing technological advancement with environmental sustainability, offering valuable perspectives for anyone interested in building greener digital services.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Vlad Coroamă: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Assessing the Potential Energy Savings of a Fluidified Infrastructure | Computer [14:40] * Digitalisation and the Rebound Effect - by Vlad Coroama (ICT4S School 2021) [22:45] * A Methodology for Assessing the Environmental Effects Induced by ICT Services | Proceedings of the 7th International Conference on ICT for Sustainability [32:20]

Events:* ICT4S 2024 [41:36]

Resources:* Roegen Centre for Sustainability [03:00] * https://pythonspeed.com/articles/software-jevons-paradox/ [05:36] * The Coal Question | Online Library of Liberty [06:34] * Khazzoom–Brookes postulate - Wikipedia [10:02] * Sustainability in Computing Education: A Systematic Literature Review * https://miro.com/app/board/o9J_lET2Yco=/?moveToWidget=3074457359170346418&cot=14

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
Vlad Coroama: When there is rebound, but if your digital service makes the activity sort of more affordable or simply more desirable, and it will be consumed more, but it will have changed in such a way that the footprint of the new activity, the modified one, is much smaller than the original one. And then although you might have rebound, the overall balance will be net positive.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello, and welcome to another episode of Environment Variables. Where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. When we talk about green software, the notion of efficiency comes up quite a lot. Take two forms of efficiency explicitly called out by the Green Software Foundation, software efficiency and hardware efficiency.

In the first case, you're talking about how much energy is needed to perform a given amount of computation. And in the second case, you're talking about how much hardware might need to be created by extracting material from the environment, refining it, then turning it into electronics that we run computation on.

In isolation, it's quite hard to argue against efficiency, and we can point to literally years of data showing how increases in efficiency in computing have blunted what might otherwise be eye-watering increases in the amount of energy consumption and other resources we have gone through in absolute terms.

Thing is, efficiency has second order effects too, because making things more efficient can make them more accessible too. Increasing the number of people who can use them. And we can point back to published work in 1865, observing this happen with coal-powered steam engines. So the common term for this is the Rebound Effect. And joining me today to explore what it means for greening digital services is Vlad Coroama of the Roegen Center for Sustainability.

I first came across Vlad's work when at a green cloud procurement workshop in 2019 held by the European Commission in Brussels. And over the years, I've had his writing and presentations about the rebound effect and digital sustainability, some of the most incisive and accessible work on the topic, on the subject.

Before I embarrass him further though, I think it might make sense to give him a bit of space to introduce himself. So Vlad, thank you so much for joining. I've been looking forward to this. Can I give you a few minutes to introduce yourself before we get into the meat of it?

Vlad Coroama: Hi Chris, many thanks for your kind intro, of course, for having me on your program. So I'm Vlad, the founder of the Roegen Center for Sustainability, which is a small company based in Zürich, Switzerland which tries to do a research, actually, more research than consultancy in the field of computing and sustainability, or if you want more from a, more from a deployment perspective, digitalization and sustainability.

Actually before that, this quite recent and before that for my entire life, I've been an academic and I've worked in the fields of computing and sustainability and also the more technical one of smart energy for about two decades now. And with both these hats on, so both with the more sort of hands on engineering system developing hat on, and with the more theoretical hat, what my work, which of course in the beginning, it was not so clear where the path leads to, but it became more and more clear that I want to understand how we can both make computing more sustainable, which is if you want perhaps green IT to use a general term, but also to see, and perhaps in my view, more importantly, to see how we can deploy computing or digitalization again from a deployment perspective, to induce environmental benefits across our societies and economies. So in other sectors, sometimes that it's often called Green by IT and these indirect effects, as you said, it's not only about direct effects, this is very much about indirect effects, are, or can be, so much more powerful than the direct footprint. And unfortunately, it's not only the positive effect. So it's not only how can we do, you know, society and economy more sustainable, by the way, society, societally sustainable as well. We'll talk mainly about the environment today, but much of what we discuss applies to societal implications as well, but to come back, so it's not only positive effects.

We also have, unfortunately, this indirect detrimental effects to sustainability, both societal, I mean, we've seen elections and so on, right? But also environmentally. That is, computing or ICT can induce more energy and material consumption, increased emissions, increased pollution, and so on in other sectors.

And with this, I think we sort of arrive at the topic of our discussion today, which is rebound.

Chris Adams: Indeed. Yes. Thank you very much for that, Vlad. So, just if you're new to this podcast, my name is Chris Adams. I am the executive director of the Green Web Foundation. That's a Dutch-based nonprofit focused on reaching an entirely fossil-free internet by 2030. I'm also the, one of the policy chairs of the Green Software Foundation's policy working group.

And here's a quick reminder, we're going to be covering a few papers and a few projects and links and websites. We have show notes at the end of every single episode, and there'll also be a transcript. So if there's something you miss, we will have that available so you can kind of catch up with this or basically submit pull requests if you see things you need to correct. All right, Vlad, are you good to go? I think, should we start with this? Okay, then. So we spoke about this. The topic of this is Greening the Rebound Effect. And I've touched on what the rebound effect is, but for the uninitiated who want to learn more than what I just said, what is the rebound effect?

And maybe you could tell us a little bit about where it comes from and whether it's a new thing.

Vlad Coroama: Okay. Thanks. So as you said in the introduction, your introduction, the very first time that we know this has been mentioned, it was in 1865 by the British economist, William Stanley Jevons, who wrote a book, The Coal Question, it's called, and it was about what we today call rebound effect, we called it such back then.

And by the way, this is a very cool thing, as a computer scientist, you seldomly get to cite, you know, a paper older than 20, 30 years, so it's really, it's really nice when writing a paper, you know, to cite something from the 19th century. So what Jevons noticed was that the more efficient steam engines and other, you know, coal using machinery was becoming in the 19th century.

At first glance, paradoxically, the overall coal consumption was not decreasing, but increasing and increasing at a very larger rate. So this is not necessarily counterintuitively, but yet it requires an explanation why. And of course the explanation is that the amount of engines was increasing because

the more coal, the more efficient machines were becoming, and by the way, some of these machines were steam engines that were helping in the very coal extraction. So coal extraction itself was becoming more efficient and thus cheaper. So both the running the machines was becoming cheaper and accessing coal was cheaper.

And this means you could deploy the coal for many more machines doing the same stuff that had been done before and for entirely new applications. And this is basically what we now call the direct free buffer, which means a good or a service becomes more efficient because the energy is more efficient or some other material that flows into it.

So it is more efficient to produce that good or service, thus it becomes more affordable. And thus, as we know from neoclassic, since Adam Smith, basically the demand for it tends to increase. So that's the first phenomenon. And this, by the way, lay dormant for over a century and late seventies, early eighties of the 20th century, of course, due to new researchers, Khazzoom and Brookes,

Chris Adams: Ah, yeah.

Vlad Coroama: we rediscovered the phenomenon in wave of the two oil crises, was the context.

And basically they talked about the same, about the direct rebound effect. And then this developed also to what we now would call the indirect rebound effect, which is actually an umbrella term for a variety of mechanisms and phenomena. But all have in common that something becomes more accessible in a way.

Some resource is being saved or is being used more efficiently. And that resource can be energy, but it can be any material. But it can also be immaterial stuff, such as time, and this we call time rebound. So if a technology saves us time, we'll do something with that time that likely will also require energy and produce emission.

Or if it saves us money, as before, we might not spend those money on more of the same good. But, and this is called the income effect, and this is another type of indirect rebound effect, we might use the disposable income to, you know, do something else that in itself might be energy intensive and, you know, responsible for lots of emissions.

Chris Adams: Okay. So, so we've got the Jevons. So there's Jevons paradox where it initially started with, and I believe you spoke about Khazzoom and Brookes. I think it's, is it called the posh term, the Khazzoom–Brookes postulate? Something like that. It's like the kind of term you'd use at a cocktail party to impress people.

And then you've also described, there's a few different flavors of rebound that we might talk about, and they might have different degrees of magnitude. And this is something we're going to, we can talk about a little bit later. So in time, you know, if I'm, if I save a bunch of money by buying a bunch of things at, say, a supermarket, a cheap supermarket, I might end up spending a bunch of money either eating out or buying, getting coffee, you know, posh coffee and stuff like that.

So that's, those are the, some of the rebound effects you're talking about. Okay. All right. Thank you for that potted history there, actually. And I didn't realize that it was so much based around the seventies, because presumably that's like relation to the oil crisis and when people suddenly started caring a lot more about efficiency.

Right?

Vlad Coroama: Yes. And actually they saw that and then also a more fuel efficient cars came around also in the U S and, but still the overall fuel consumption, not maybe short term during the, you know, the crazy months of the oil crisis, but over several years, the oil consumption, the petrol and so on was still increasing.

And that's how, so for a similar sort of trigger as Jevons, a century earlier, they started looking at it, how does this happen? And what they saw is people drive their cars more.

Chris Adams: I see. Okay. Thank you for that. And, so when we're talking about things becoming cheaper and more accessible and more widespread. It's not a huge leap of the imagination to think about things like electronics getting cheaper or more widespread, even cloud computing becoming cheap or more widespread.

So I guess maybe it's worth me kind of moving to this. So if we're gonna talk about things like the rebound effect or things like this, or why efficiency gains matter in the context of building digital services, maybe I could actually ask like, why does this matter when we talk about digital computing?

And why does it matter in a world where we are seeing more laws being passed now and a kind of influx of new kind of legislation or people setting new norms about this?

Vlad Coroama: So it, it matters, as you say, of course, this happens within computing as well, or within ICT, let's say, I think it's Koomey's law that, that says,

Chris Adams: Is the network halves every 18 months or something, isn't it?

Vlad Coroama: Yeah, it's that basically we are, or a consequence of Koomey's law, a consequence, not directly Koomey's law, is that we use all our gains for more computing and not for, you know, less energy intensive computing. And this of course makes sense. But the problem I think with computing or what does it mean, the, the big challenge of computing, but also environmentally, what can become an issue is that it's general purpose technology and that it induces efficiency, not only within computing, but also, and crucially outside it.

So we, when we talk about the rebound effect of, again, computing/ICT/digitalization, choose the term that you prefer... we have to distinguish between the rebound within ICT itself, more computing, perhaps, you know, more cloud, whatever, it's more affordable. But crucially, I think also the rebound outside this in all the other sectors that digitalization makes more efficient.

Chris Adams: I see. So there's, so in the context of digital, one thing you're saying is that, yes, there is, obviously we should be mindful of an efficiency argument, but because if you just only talk about efficiency rather than consumption, you can lose sight of the full picture and. If you take a second to step outside, the efficiency that you might see at a kind of digital level could also have like

absolute increases or decreases accordingly. So you should be, so we need to take, we need to be looking at the two of these basically.

Vlad Coroama: Yes, exactly.

Chris Adams: Okay, cool. Thank you for that. That's actually, okay, that's quite helpful. And I suppose when we talk about efficiency, it's worth looking at some of the numbers, for example.

So we have seen, say computing get quite a bit more efficient, but we've also seen, basically, we've also seen, for example, some of the hyperscalers, we've seen hyperscale companies like say Microsoft, Google and Amazon, it's not like they've stayed the same size and they haven't grown.

We ;have seen them growing, even as things get more efficient. So these are one of the things where we need to be somewhat aware of, yes, the absolute figures in this as well as the efficiency part here. And we've spoken about how, there's, digital can have an impact on the outside world, and you might be talking to things like, so like transportation examples or like ride hailing, things like that is what you're referring?

Maybe you could expand on some of those. Cause I think these are the things that I've seen you talk about quite eloquently in other places, actually.

Vlad Coroama: Yes, because there is the hope, right? And very often we have the claims that ICT or digitalization, let's say now, makes so much of the world more efficient by coordinating it better, by, you know, finding patterns, by we all know how Google did its cloud more efficient and so on. But then there are many other fields outside.

And in all of them, I see a pattern of how in the beginning everyone says, or a lot of the voices say, "Hey, great, you know, now we have your efficiency. Now it will be so much better." It's a sort of a techno-utopianism, if you want. I will give two-three examples. The one I will start with this one, I'm writing now actually about the rebound effects of teleworking.

And I've, so I've been reviewing many studies and it's very funny because the very early studies, teleworking has been around long before sort of the World Wide Web made it into the homes. Since the 70s, they started talking about this. And the first papers have titles such as, you know, 'Traffic Reduction by Telecommuting' and then similar things.

And then through the work of Jack Niles, it was, and especially Patricia Mokhtarian in the nineties already, they started to understand, "oops, wait, wait, wait, there is also lots of rebound effect." And today's papers have titles such as, you know, 'Does home-based telework reduce household total travel?' So lots of questions marked there.

You know, does telecommuting promote sustainable travel and physical activity? Does telecommuting reduce commuting emissions? And so on. These all, and I have many more, but I will not go into them. But so the phenomenon that happens there is that, yes, teleworking in first instance, of course, if you don't travel to work and travel is energy intensive, much more so than, you know, the little bit of energy that we consume now to have a call, it saves energy in the sum.

But then, because you have more time, because you are more flexible, you start, and because before you used to do other things while going to work or coming, you used to have multi purpose trips. So you, I don't know, dropping kids at school, you know, going to the gym, doing grocery, whatever. those other reasons still exist.

So you will still undertake other trips and much more so than you have subtle effects. If you only need to commute, say, twice per week to work, you might be very tempted to move much farther away from work, you know, in a nice countryside where the kids can play, you know, in nature and safely and so on.

And then you only commute twice instead of five. Well, four or five times per week, but for much longer distance and perhaps no, you can no longer do it by public transportation because you're not urban anymore, but you have to do it by car. And that's a classic. And this became more and more clear. So teleworking is not clear actually now whether, you know, the net effect is a positive or negative.

And I will not go into this detail for others, but we have this for e-commerce or slash online shopping as well. Again, lots of enthusiasm environmentally in the beginning, and then you see that many other things happen. You know, you, all of a sudden you order much more. It's so easy to order from the couch at 11 pm, you know, you don't need to go to the store. So all the consumption increases, or now more recently with AI, with autonomous vehicles. And this is perhaps the last example I want to give, and I think you've heard this before because it's a favorite example of mine. Also in the beginning, we had lots of enthusiasm, you know, how the cars will like coordinate with each other.

And then, you know, they, at some point we won't need traffic lights anymore. So then don't need to brake and waste energy and then reaccelerate. But this is all peanuts. What actually will happen is that, you know, they will substitute, autonomous vehicles will substitute a lot of public transportation because it will be so much more convenient to be driven by car and be able to work in the car or, you know, read a book, discuss whatever. So use the time efficiently.

Chris Adams: Okay. So you spoke about these, there's quite a few examples then of the rebound effect resulting in basically first in like direct efficiency leading to increases in usage in other ways, with some kind of actually quite vivid examples there. And that's, that feels like a nice segue to talk about, okay, we have this idea around rebound.

And there's different kinds of rebound that can take place. But as I understand it, there are certain conditions that make rebound more likely or increase the effects of rebound versus, making them somewhat smaller, for example. Maybe we could talk a little bit about that because I remember hearing about the kind of like vivid example of autonomous driving.

Like you mentioned, there was, yes, it increases the, it lowers the threshold of you doing things to the point that, you know, there's there's a famous study about someone sending autonomous cars to just pick up a sandwich they left at home because it was so easy to do now. And that's obviously not going to be a sustainability win.

So maybe you could talk a little bit about when you do see rebound and what conditions make it more likely to happen versus maybe when it's not so likely to happen, perhaps.

Vlad Coroama: Yeah, there are, I do not have general rules to provide an answer. So I cannot tell you this precise, you know, class of applications or yeah, digital services are more likely to rebound than the other not. But I can give you a couple of hints or perhaps examples, and the easiest is to start with that, with the example of the vacuum cleaner that you mentioned earlier, and which is of course outside digitalization, but I think it's very nice to understand the phenomenon. When the bagless cleaners emerged to, Dyson was the first on roads to invent them.

They also became so much more efficient. So they used to consume 1.5 to 2 kilowatt of power, and now they are 4-500 watts. So a factor of it's like 20 to 25%, a factor of four to five, reduced power. And the question is, do we vacuum much more? So it is of course, cheaper to run them. Do we vacuum much more?

Probably we do it a bit because, you know, they are also more convenient. They are cordless very often and so it's easier to grab them. But certainly this rebound is relatively small and not, you know, 400% it doesn't overcompensate with certainty, because, well, you only need so much to vacuum your house and it's probably also not the most people... the favorite activity for most.

So one of this thing is when there is something like, when the demand is satisfied,

Chris Adams: Ah, like an upper limit.

Vlad Coroama: not have rebound, you need to not have the rebound mechanism. And this mechanism being often, not always, again, it can be with time or transaction costs or other things, but often it is monetary.

You save money and then you, you know, consume more of that good. And in this case, if the demand is satisfied, then you don't need more. So, for example, smart heating in a home, to come again now back to computing, if you have smart heating, I mean, we used to have our homes up to the seventies, even at 13, 14 degrees centigrade in winter.

We don't do it anymore. We all have whatever 19, 20, 21, wherever we feel comfortable and we don't need more than that. So, a smart heating system will make our, our heating more efficient, then we'll save 10%. And that can be financially quite interesting. We'll not use those money to hit more because there is no need for it.

I mean, we might perhaps, you know, let a bit more fresh air in and thus waste a bit more energy, but it will certainly not compensate the savings. So that would be one such example where at least a directory bound. It is, is unlikely,

Chris Adams: Ah, I see. I'm really glad you mentioned the vacuum one because I remember watching your talk just after I bought a cordless vacuum cleaner myself, and I remember saying like, "okay, there's an upper limit to how clean my flat can actually be." And like, yeah, it's a lot more fun to use, but yeah, I, it doesn't make me... making me slightly more efficient at vacuum cleaning does, it didn't double how much I enjoy vacuum cleaning, right?

Well, I might enjoy it more, but there's an absolute upper amount of vacuum cleaning hours I'm prepared to invest into my flat, for example. Okay. So that's, so there's this upper limit of satisfaction that if you have something like that, that's maybe one kind of hint that you might be looking for, for example, and we might be able to kind of take some ideas into another domain domain for that.

Vlad Coroama: And if you want, I can give another such hint. So when there is rebound, but if you sort of, if your digital service makes the activity sort of more affordable or simply more desirable and it will be consumed more. But it will have changed in such a way that the footprint of sort of the new activity, the modified one, is much smaller than the original. And then although you might have rebound, the overall balance will be net positive.

And again, a short example outside of digitalization is LED lamps, right? There is certainly, once you have LED lamps, there is certainly a rebound in the, in a sort of light rebound, in the amount of light that you're using. You will, because you know, they take six watts and not 60 anymore. You are not so concerned with like turning it off anymore.

So there is some light rebound, but in terms of energy, the rebound is really small because even if you leave it like twice as much, you will still save 80 percent and not 90 percent, but still the net save will be... and the same in digitalization. We did, for example, a conference for it in 2009 between two continents.

And that conference happened at two sites simultaneously in Nagoya, Japan, and in Davos in Switzerland. Of course, it was a seven hour difference, so there was just a four hour common slot in the Swiss morning and the Japanese afternoon. And why we did this? Because for a conference, the main environmental impact are flights of participants to the conference, and in particular, intercontinental flights.

So the hope was to save intercontinental flights. And according to our survey afterwards, we have indeed succeeded to save some, around 80 intercontinental flights of people who would have flown to the other side of the world. And we induced much more, around 200 intracontinental flights. But you know, a short haul flight has such a smaller footprint than a long haul flight that although we had many more participants

and many more flights. Because those flights were much shorter, the overall impact was still positive. And again, we only talk direct rebound here. I like to stress this point. The system boundaries, as they say in environmental sciences, the system boundaries of indirect rebound are basically the words. So it is very, very tough and we do not have yet the right tools to profoundly assess the, you know, the overall impact of digital technologies, unfortunately. And this is one of the areas I'm most interested in.

Chris Adams: I see. Okay. Can we just dive into that a little bit more before we move into the next topic? So you spoke, we spoke a little bit about say, forms of rebound where there's an upper limit where there is, it's like me having a more efficient vacuum cleaner is one thing. And then you mentioned this other thing where there is like,

where you're somehow, where the savings end up being kind of almost somewhat circular. So if I'm, maybe I can reduce, say the cost of cloud computing, you mentioned that in many cases, because I've made it cheaper, I would then recirculate those into doing more rather than actually reducing the total energy use.

Is there anything, have you, maybe you could expand a little bit more on that part, because when I think about things like, say, AI, or I think about some kind of, some things related to cloud computing, we can totally see this, and there are very much arguments basically being made right now, that say, "Oh, well, all you need to do is focus on your cloud bill going down by half," for example, "and then that will be, and that will achieve your savings."

Well, that's what you need to care about." And it sounds like, if I was to focus a bunch of time into halving my cloud bill, I'd then have a product manager or my CEO say, "well, okay, look at all this, look at all this money we've saved. Let's reinvest it into doing more so we can do, so we can have more of a competitive advantage in our particular field," for example.

Vlad Coroama: Yeah, of course, if you want... reducing your impact means always reducing your overall impact and not becoming more efficient. So in a sort of narrow view of what you asked, if your manager came to you and said, "hey, let's be twice as efficient," the answer should be "no, let's overall consume less." This being said of course, it's again, it's very difficult because AI in particular, and AI is the most uncertain domain, as you very well know, or certainly one of the most uncertain how it will develop in terms of energy consumption.

And so it might go through the roof or it might not, you know, and it will depend on so many factors, but it also has, it brings about, and I keep coming back to the indirect effect. Sorry for that. But, you know, you cannot forget them. So I hear very often the argument of sobriety, of digital sobriety.

And of course, it's good because to achieve various, you know, goals, whether they're achievable or not, or any goal, any limit we want to achieve, of course, all sectors have to go down. But then AI can use substantial societal or environmental benefits when it's environmental benefits, and if you can really put your finger on them, then it's easy.

Then you, then it's a no-brainer. Of course, it's worth spending, you know, the additional data center to train our models better. Also, by the way, the energy consumption in our devices for a model inference. Because, for example, I have now a paper under review where we measured a bakery chain in Germany and they deployed AI to predict the demand for bread and thus to reduce food waste and the results show, so we made a sort of a benefit-cost analysis.

And the benefits, energetically speaking, are so much larger than the costs of deploying that AI system, training it, inferencing and so on. So when there is, then it's a bit of a no brainer. Unfortunately, you sometimes have, you know, societal benefit at an environmental cost. And then it again becomes harder because then it's a scientifically non-answerable question, then it's an ideological question, right?

"How important?" Or a value-based question. But to come back to actually your question, because I think I went perhaps a little too far away from that, I keep, I keep bringing the indirect effects because I think they are so underrepresented in the discourse, both academic, but even more so societal.

So your question was about the efficiency of, or could you say it again? Sorry.

Chris Adams: Yes, so the question I'm putting is, say, if I want to reduce emissions, it's very easy for me to just talk about, "look at how much more efficient I can be" if I'm a developer, I often think that, you know, I've, I'm incentivized and I am rewarded by making things more efficient. It feels like, if I just focus on halving that cloud bill, for example, there's a risk that they'll just bring that cloud bill back up again, for example, or bring the environmental impact back up again by using some of the savings to do new things.

So the thing I would need to, things we'd kind of need to be able to do is basically have this notion that, okay, we do need to be on a kind of glide path downwards in absolute terms, for example. We can't just talk about emissions intensity, because this is a common thing that you see being, that's coming up in quite a few places.

And this is something that organizations tend to report now a bit more as a way to avoid talking about absolute figures. But it feels like if we're going to do this, we need to look at absolute consumption, just as much as efficiency. And efficiency is one of the strategies you would use to reduce consumption in total, in absolute terms.

Right?

Vlad Coroama: Yes. Yes. Absolutely.

Chris Adams: Brilliant. Okay. Thank you for clearing that part up. I...

Vlad Coroama: Well, it was more you clearing it... But yes.

Chris Adams: This is part of what we're now doing is we, running through some of these to make sure that I understand it and i, when I'm doing this, I'm basically standing, this is helps me explain it to other people as well. So this is a, yeah, this is totally okay.

All right. So we spoke a little bit about rebound. There's a few different flavors of this that we had. And you touched on this idea that if you just look at one aspect, then you can miss some of the kind of wider systemic issues and systemic impacts. And this feels like a nice kind of segue to talk about some of the other work that you've been doing, because it's actually where I came across some of your other work about trying to quantify the environmental impact of a service across multiple areas, basically.

And I found this really helpful where, when I first read it in 2020, because it found, it provided a somewhat kind of rigorous way to help address the fact that a lot of the time people will overstate either the savings, overstate the damage being done in this, in these areas. And I think the name of the paper was, sorry, it's a bit dry.

It's Methodology for Assessing the Environmental Impacts Induced by ICT Services. But one thing that was really nice about this is you would say, "well, you need to think about how much more efficient something might be, but you also need to think about what kind of take up that might be for something."

So, and all of these things here. So. Maybe I could actually talk to you a little bit about this because it's very, very common to see very, very kind of extraordinary claims about efficiency or extraordinary claims about savings under perfect circumstances. So maybe we could talk about like, when you look at this stuff, are there common mistakes or common kind of omissions to look out for when you see people talking about the savings delivered by maybe a new service, for example, so you can help develop some kind of intuition? Because this is one thing I think we don't really have the language to talk about this right now. And I think one thing that your papers did was actually introduce some helpful terms or some helpful language to talk about some of this.

Vlad Coroama: Yes, in all honesty, I... first disclaimer, we didn't provide a cookbook recipe how to do it and how to arrive at a net impact. Again, system boundaries are the word and we don't yet have the tools for that, but this being said, you can try avoiding the most common and sort of low hanging pitfalls if you want.

And perhaps the most common is that, that you read is, you know, a juxtaposition or direct footprint of a service and the benefits in fitting uses. So direct footprint, which is by definition, it's inherently negative from an environmental perspective, as almost any human activity, and the other side, the indirect benefits.

But then conveniently, and I'm not saying that this is necessarily purposeful, it can be out of naivety or, you know, but it is convenient for getting the indirect negative impacts. So you always have, so I think that's a helpful way of thinking about it. You have the direct footprint, negative by definition, and then you have indirect effects, which are both positive and negative. Ideally, you would try to cover them both. The very sort of high level indirect ones, which are systemic, you cannot cover. But you can at least take care of the direct rebound, for example.

Chris Adams: All right. Thanks for that. So you spoke about, so there's leaving omissions from here. There's one thing I've seen that in a few places, so I've seen like, say, caching services basically say, "well, look how much, look at the savings you've received," for example, without telling you the full amount. And this is something that I think Uber have released.

They've shown, there's now a calculator to see how much cleaner your ride would be if you use an EV car versus another one, but you don't see the absolute numbers, for example. I mean, what's wrong with this? Like, is this a thing that... is this a good idea or should, or if you were to do this properly, like, how would you make this more representative, for example, when you see examples like this?

Vlad Coroama: Well, I don't know those particular calculators. I haven't used them or seen them. But from how, what I understand about them, it's very often a question of baseline or of the counterfactual. What is your counterfactual? If I hadn't used this, you know, for example, green taxi service in your example, what would I have done?

If the assumption, if the baseline is, I would have used, you know, a very inefficient internal combustion engine-powered car instead, then, of course, depending also a bit on the electricity mix of the grid, usually it will be positive, right? The overall impact. But the thing is, it might have replaced public transportation or no trip at all.

And then it's a rebound effect. So if I am keen, you know, I am taking a taxi and you know, it just tells me, "Hey, if you now take the green one instead of this," then I would say it's probably a reasonable assumption. We have some production issues, so from a life cycle assessment, of course, it's a bit complex, than it's probably pictured, but in essence, it's probably not incorrect.

But overall, what happens is that if a taxi ride is cheaper, or if I have what is called a moral hazard, so I have a clear conscious, "oh, I'm going green so that I can take it," and then I'm taking one that would not have existed in the counterfactual, then of course the net effect is there.

Chris Adams: Okay. So that last part is like, I get an Uber or I get an electric taxi and, so I sort of, to a restaurant and I then decided to eat a big fat steak, as an example, like as a way to kind of balance these out. Like there's maybe an indirect, there's a direct saving, but systemically, I still have created more of an emissions. Like, I'm not going to try and do the calculations between steak and a drive, but you get the general idea.

Okay. So that's where some of that comes in. You mentioned this thing called a counterfactual. And I think this is actually one thing that might be quite helpful because we've seen a number of papers and reports being used to talk about how, you know, you can achieve sustainability through AI and we've seen them written in, say, in the early 2010s or even the early 2020s.

And then there is often a lot of interest in talking about how good something could be, but there seems to be less, historically, we've been less good at tracking whether those savings have been delivered. Is this something that maybe you could talk a little bit about that? Cause I remember you write, I saw recently you wrote a little bit about the, this kind of reporting, the fact that there's a kind of gap in how we talk about this and the following through part, maybe you could just follow, just expand on, on this and why you need this, this extra information to kind of see if things are working basically.

Mm

Vlad Coroama: Yes. So for AI, I think it's a bit too early to tell, we have not yet seen like a series or I'm not aware of any, a series of studies or even like one old study that made some predictions and the authors didn't come back to it to say whether anything was delivered on. And I think it's not also a typical, like, computing thing that we do lots of predictions. And as the old adage goes, "predictions are difficult, particularly about the future."

Chris Adams: Yeah.

Vlad Coroama: Yeah So first, you know, when our predictions were right, we might like to go back and highlight this that we were right already back then. And otherwise we might conveniently forget that we made those predictions.

For the computing domain generally and not AI, because again, AI, I think it's a bit too young for that phenomenon to be seen one way or the other, but for computing generally, there is a track record of various, both companies and sort of lobby groups of the IT industry or of the telecom industry doing sort of predictions and then continuing. One very known example is GESI, Global E Sustainability Initiative that published every couple of, every four to five years, starting 2008.

They publish a series of studies. The first one was called SMART 2020, then SMARTER 2020, then SMARTER 2030, and so on. And there are predictions, the first two ones are called SMART 2020 and SMARTER 2020 because they're where to the year 2020.

Chris Adams: Ah, I see.

Vlad Coroama: And and they predicted many gigatons that would be saved through digital technologies.

I think the first one was 7 point something and the second study around 9. 1 or 2. And that's, that's quite a chunk of the sort of fifth of CO2 equivalent that the humankind puts into the atmosphere every year. So that's a very substantial chunk. And if that would have been true, it would have been amazing.

But now, well, 2020 is past, heh, and we published newer studies, but they didn't look, you know, how did this stand up to the test of time?

Chris Adams: Wow. Okay. That's, that feels like quite a gap that we probably should be trying to close. If we're going to be talking about, we're doing research in this and seeing what is going to be effective as time is ticking down. Right. Vlad, that's actually, I really want to dive down in that rabbit hole, but we're coming up to time.

So I'm going to have to be a good boy and try my best to stay inside the time we do have. Vlad, we've covered quite a lot of interesting areas and dived into quite a lot, and I've shared a couple of links. The show notes have series of links to the papers and things like that. If people do want to continue this work or continue following what you're up to, where should people be looking beyond just the show notes of this podcast for example? Is there a website that we should point people to, or do you have a online presence you would direct people's attention to?

Vlad Coroama: Well, anyone, if, I mean, you can post my, a link to my LinkedIn account, if anyone wants to contact, I'd be happy to, you know, to engage in conversation and continuing discussions, this is what I do. So other than this, there is no value that is specifically say on rebound effects of digital technologies.

I wouldn't know of any, but there is, for example, the ICT4S conference. So the ICT4Sustainability, that, that conference that started back in 2013 and where indirect effects of ICT are quite a powerful presence. This year's edition will be end of June in Stockholm, Sweden, and I'm co-organizing with a couple of other researcher.

So, with Mattias Höjer at KTH, with Tristan Brehmer in Lancaster, Charlie Wilson in Oxford, and Dan Schien in Bristol, we are organizing a workshop on this very topic, indirect effects of... called wait, I'm no longer sure what acronym stands for, but something with indirect something. So a workshop on assessing indirect effects.

So there are a couple of venues that are scientifically dedicated to this, but I, there is no unfortunately, no like, you know, portal where everyone has the topic.

Chris Adams: Like Institute of Rebound. Yeah. Okay. And yourself, I understand that there's the organization that you work for. The Roegen, is it Roegen Center of Sustainability? That's the one. Yep. So that's roegen.ch is the place people would look to if they want to see any future publications and research in this field from you.

Brilliant. Well, Vlad, thank you so much. I've been looking forward to this and I have to admit, I'm a bit of a fan boy. I've really enjoyed a bunch of the papers and things you've been publishing over the years, and I really hope you continue to do them because they come up with really nice examples that I can help explain to other people.

So thank you once again. And yeah, hope you have a wonderful week. Take care, Vlad.

Cheers. You're too kind, Chris. Thank you as well. And by the way, thanks for your great work that you and your foundation are doing. So thanks for that as well. And thanks for having me. Cheers.

Cool! Thank you. Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode!

View Details

In this episode of Environment Variables, host Chris Adams is joined by Rachel Tipton, a full stack developer at Open Climate Fix, to delve into the intersection of AI, green software, and electricity infrastructure. Rachel emphasizes the increasing demand for electricity due to factors like server centers, EVs, and electrification efforts. They explore the concept of carbon awareness and its implications for software development, shedding light on the complexities of optimizing energy consumption and reducing carbon emissions. Through Rachel's journey into coding and her work at Open Climate Fix, listeners gain insights into the critical role of technology in decarbonizing the electricity grid and mitigating climate change.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Rachel Tipton: Linktree | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* FOSDEM 2024 - Quartz Solar OS: Building an open source AI solar forecast for everyone [2:23] * Quartz Solar [15:09] * Starting a non-profit research lab to help fix climate change ASAP | Jack Kelly [22:52] * Recapturing early internet whimsy with HTML | MIT Technology Review [42:05]

Resources:* The Tech Generalist | Rachel TipTon [04:06] * Women Who Code [04:08] * Subak [14:09] * GitHub - openclimatefix/Open-Source-Quartz-Solar-Forecast [15:09] * Real Decarbonization: How Oil and Gas Companies Are Seizing the Low-Carbon Future | Tisha Schuller [41:29] * html garden [42:36] * https://sceneries.site/#home [42:49] * https://github.com/search?l=&p=1&q=user%3Aopenclimatefix+label%3A%22good+first+issue%22&ref=advsearch&type=Issues&utf8=%E2%9C%93&state=open * openclimatefix (Open Climate Fix)

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

**TRANSCRIPT BELOW:

Rachel Tipton:** I think it's really important that people are aware that our electricity infrastructure is going to have to handle a lot more electricity, whether that's going to be like server centers, like computers in different places, but also like EVs. If we're going to electrify everything, we're actually going to be using much more electrical energy in the future because it's going to be replacing those carbon-based fuels.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello, and welcome to another episode of Environment Variables, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. When we talk about green software, it's common to start talking about energy efficiency, i.e. how much energy you need to perform some computation, or even hardware efficiency, i.e. how much physical hardware is needed to perform that computation. One idea that is less easy to understand is this idea of carbon awareness, an idea based around the fact that depending on where you are in the world or what time of day it is, the amount of fossil fuel being burnt to power the grid we rely on can change, which means the energy could be greener or less green.

This is because beneath the stack of technology that makes up the internet, there's an entire energy system that is at least as complex as the internet. And if you have visibility into that system, there are ways you can operate your systems at the level above to take advantage of these changing conditions, often to save on carbon emissions, and in some cases to save on cash too, as the price of energy can often change based on the amount of cheap renewable energy being fed into the grid that we draw electricity from.

As I mentioned before, this is an idea that takes a bit of getting used to, and when you hear it from publicly traded trillion dollar companies whose own reported emissions have only grown in the last few years, you may be right to be skeptical about carbon awareness. Now at FOSDEM, the largest open source conference in the world, in February, my guest, Rachel L'Abri Tipton at Open Climate Fix presented a fascinating talk about solar nowcasting, something we'll cover later.

But crucially, as someone who recently switched careers, both into software engineering and into working with grid operators, she seemed a good person to talk to, to learn more. Hi, Rachel. I've given you a bit of context about how we met. But I figured, can I just give you the floor to let you introduce yourself before we start?

Rachel Tipton: Hi Chris, thanks for having me on the show. I enjoyed listening to the other environment variable episodes

in preparation for the show and I think that I'm a convert. So I'm Rachel Tipton, I'm a full stack developer at Open Climate Fix, OCF, that's the shortening of Open Climate Fix, is a non-profit product lab, and we're developing renewable energy forecasts to decarbonize the electricity grid. We'll get more into that later, but I'm really happy and excited to be here speaking about my own coding journey today and my time at Open Climate Fix. In addition to speaking at FOSDEM, I was also part of organizing the energy dev room program that I spoke in, and that was organized by LF Energy.

So I was volunteering for them and I ended up submitting the application for Open Climate Fix to speak. So I then asked if I could present some of the slides

that they I had a plan for us to speak with, because I thought that we should be talking at the conference. I also write a blog called the Tech Generalist.

I only have about three articles in it, but that's something that I've been doing since I started my coding journey. And then I also participate in Women Who Code events with the London chapter of Women Who Code.

Chris Adams: Cool. Thank you, Rachel. And when you refer to LF Energy, you're referring to Linux Foundation Energy, right? That's one of the organizations that was, okay, got it.

Rachel Tipton: It's a small group within the Linux Foundation.

Chris Adams: Okay. Thank you for clearing that part up. Okay. So if you're new to this podcast, my name is Chris Adams. I am the executive director of the Green Web Foundation. Which is a Dutch-based nonprofit, basically focused around the idea of a fossil-free internet by 2030. But I'm also one of the policy working group chairs in the Green Software Foundation Policy Working Group.

I'm also one of the regular hosts of this podcast. Okay. And just a quick reminder, everything we talk about on this show, we're going to link to in the show notes, and there will also be a transcript provided. So if there's something that you missed the first time, there should be something available.

And because this is a software engineering podcast, we also have this transcript and the links, the show notes in markdown form on a GitHub repo that we'll be linking to. So if there's something you missed, or if there's something you feel that you need to be corrected, we do welcome pull requests. All right.

Okay, Rachel, I was going to ask if you're sitting comfortably, but I realized that you're standing where you are in the world. So I guess, should we start? Does that sound okay to you?

Rachel Tipton: Sounds great.

Let's go.

Chris Adams: All right. Okay. So we've teased the audience with a few kind of geek catnip terms, like solar nowcasting and so on. But before I dive in, I wanted to ask. I know that you grew up and studied in America, but I think you, I think you mentioned that you're calling me from France and you haven't always been a software developer.

So could you maybe expand a little bit about that before we dive into the nerdery?

Rachel Tipton: Yeah. So I'm actually speaking to you, Chris, from Olsene. It's a small village in Belgium near Ghent, for people know where Ghent is, that's the point of reference. I grew up outside of Chicago in a state called Indiana in America, and I've lived and worked in France since 2011. So I moved to France in 2011, and my time is split between Lille, which is a city in the north of France, and then this village in the rural area of Belgium. So we have a big garden and it's quite springish outside today. So we've got a magnolia tree that's in full bloom and it looks really nice. And we've had a lot of rain this year in Belgium, so our basement is flooding. Everybody's basement is flooding here. We've had twice as much rain as we usually get.

Chris Adams: Wow. So firsthand experience of changing climates. I guess. Yeah. You, you can't deny some of that then. All right.

Rachel Tipton: No, no, not at all. Yes. I think it's important to say that I'm a writer and a maker and for most of my 20s. I made my life decisions based on being able to have time to write and have time to make art. Some of that writing is out in the world. A lot of that writing is probably in some place in manuscripts, but that's like who I am at the core. And so I didn't study computer science or physics or engineering like some of my current colleagues, but I studied English literature and geography. I did have a stats course in my geography study. So that was kind of like the beginning of my exposure to data.

And I got out of university with critical thinking skills and really good writing skills, but no clear career path.

So I'm an interesting person. I have lots of interests, can talk about many things, I read voraciously, but really up until I decided to shift into coding, I hadn't felt like I had a career of some sort. So I had been, when I decided to try coding, I'd been working as a freelance technical editor and writer alongside teaching English full time at a university in the north of France.

I was also teaching at business schools as well. And I had ended up in France because I wanted to learn French. So that was part of, you know, "I want to be a writer. I think learning a second language would be great." Now that I have, you know, I spend part of my time in Belgium. I'm in the Dutch speaking area of Belgium.

So of course, I've also...

I speak Dutch now to like a intermediate level. So I think it's that language learning part of myself that actually made it quite easy to start learning coding languages because I understand syntax and I understand patterns within language and that

like, I really love grammar.

Like I love doing grammar exercises and I feel as though solving code problems are to some degree beginning to understand the grammar of a coding.

Chris Adams: Oh yeah. I see

Rachel Tipton: Remember we have a coding language and then beginning to understand like larger data structures is like beginning to understand like paragraphs that lead to arguments that, you know, that you can build something with your code structure in the same way that you do linguistically with language.

I know not all coders approach coding in that way, but that's the aspect of myself that perhaps made me attracted to learning how to code.

Chris Adams: No, I could totally see that. Like I live in Germany and when I came from England to Germany, one thing I picked up was, well, the way that you can just like bash words together to make longer words. When I first came here, I was terrified of how long all the words were. Then you realize they're just like one word linked to another word linked to another word.

It feels like, "Oh, this is just like jQuery. It's just like chaining," you know? And then when I realized that I was like, "Oh, okay, this makes a lot more sense." So I totally see where you're coming from actually on this, Rachel. So yeah, I'm also glad that it's not just me thinking about this. So yeah, that's reassuring.

Rachel Tipton: Yeah, syntax is really, really exciting. Okay. Yeah. Let's see, like in my story, in the, it was the middle of the pandemic when I decided I need to make a change. I think a lot of people had some sort of... I've talked to people who've had a moment of, "Oh, I need to shift something fundamentally in my life," and for me, it was my job and my career. I loved the process of teaching English at the time. I loved my students. I'd even been able to develop a, like a creative writing class for, at the university where I was teaching. So it was really great to get to teach poetry and short story writing to my students, but everything else outside of the teaching was really draining.

And even though I had time in the summer to do my writing, I was completely burnt out, which I think a lot of people who teach have experienced burnout before. So I was also very, very tired of a myth that I had for myself of being like, needing to suffer to be an artist. I think that was like a holdover from my twenties.

I've talked to other artists who have this.

Stepping into the

Chris Adams: artist stereotype thing.

Rachel Tipton: It's the starving artist stereotype. And I think I bring it up because I think it's false. And unless you are a well funded suffering artist, then it's hard to live that artist's life. And so

for me, I was also looking to make a decent living so that like the environment in which I was making art was a little bit more just like financially stable. And then I didn't feel as though I was like giving my heart to my job and not getting anything back from it. So

yeah, that was the place where I was. So, a friend mentioned coding and I started to just started to research it. Like I contacted two people that I knew who worked in tech and one of

them was really encouraging.

He was like, "you know, the tech space needs more women. You can do it. Like, you'll figure it out. Like JavaScript is not rocket science." I trusted him and then somebody else had mentioned boot camps and this particular friend is a business analyst. So I just asked her to put me in touch with coders that she knew. And so she connected me with

two female coders and then I've talked to them and like through those discussions, I started to be exposed to words like front end, back end, full stack developer, and I had no idea what those words meant. Yeah.

That was like three years ago. It was just a lot of jargon, but I had also, as a technical editor, I had already worked in spaces where jargon was used and I know that jargon means stuff.

You just have to listen to it long enough and eventually it's meaning will clarify itself. It's like being a

Chris Adams: I'm glad you mentioned about jargon thing.

Rachel Tipton: Mhm.

Chris Adams: Yeah. Because I, I think it's very easy for people to basically say, well, I'm not going to, you know, you can rag on jargon, but in many cases, it's actually a very efficient way to get something across once you've established a context. So I totally understand.

Like when you're using the term "MEAN stack" or 'Jamstack' or something like that, the fact that it means something is way, way, way, way, way faster than us having like another five minute discussion explaining what each letter means, for example, and things like that. So, yeah, I know where you're coming from there.

Totally.

Rachel Tipton: Yeah, it's really, jargon is useful for the insiders, for the outsiders it makes it seem like it's much more complex

than it is. As a technical editor, I specifically had worked for a society of doctors who basically wrote papers on blood diseases, so it's like all of the papers were on bone marrow transplantation and I was editing it.

And there's so much jargon in that space around like treatments and diseases, but with time I eventually understood what they were talking about, just in basic terms I was able to actually write about it and talk about it. And so I had the same approach to the coding space. Like from that experience, I was able to apply that to being in a tech space and be like, "this is just like being with the doctors who, you know, thought that they were really

Chris Adams: Yeah. It's not special. It's just new. Yeah.

Rachel Tipton: Yeah. Yeah. It's not special. It's just new. And I think if you show up with like a beginner's mindset, I like the idea of like the beginner's mind that's completely clean. You're just there and you're curious and you're learning. It's a really great experience to just move forward with that like confidence and humility at the same time.

Chris Adams: Cool.

All right. Thank you. So that gives us an idea of a potted history of where you were and where you came from and how Python or JavaScript might be a fourth or fifth language in the context, rather than just like a first or a second language in that sense.

Rachel Tipton: That's how I'd see it. I don't speak Javascript or Python, but I can read it. Yeah.

Chris Adams: Okay.

Rachel Tipton: Yeah.

Chris Adams: Like Latin, I suppose. All right. Okay. So that's some of the background that you had and you've been working with Open Climate Fix for the last few months or so. So that means like messing around with like Postgres or Python and like working up and down a technology stack, for example, and trying to figure out how to use computers for climate wins.

I found Open Climate Fix really interesting because Dan Travers, who was, he was actually one of the advisors and mentors for our organization a few years back when we were going through an Accelerator Progress program with the Green Web Foundation with Climate Subak, an organization. But I really like what they do and I really like the open approach.

So maybe you could just share a little bit about who they are, what they do, because I think that'd be quite helpful context in some of the discussions about computers, forecasting and how some of this fits and why you'd even care about any of this.

Rachel Tipton: Yeah. So the. Company Open Climate Fix was founded as a non-profit product lab five years ago. Like we just turned five, I think, what did it say, late February. So it was founded in 2019 by Dan Travers, who you've mentioned, and Jack Kelly, who worked for the Google DeepMind project. And yeah, the idea of Open Climate Fix is that we connect people who are doing ML research with the energy sector to help decarbonize it.

And the initial product that we've developed is called Quartz Solar, which is like a short term, like we've mentioned solar nowcasting, but it's a short term forecasting service. And I've tried to make this as simple as possible to explain to someone on the outside, but basically what we've done as like. The way, the place we've implemented the court solar forecast is with the National Grid ESO in their control room. So in the UK, there's funding that's called, I think it's National Innovation Allotment that an organization like National Grid can use to collaborate with an organization like Open Climate Fix to develop technologies that will

Chris Adams: I see.

Rachel Tipton: reduce carbon emissions.

Chris Adams: Can I just check with you? Sorry to interrupt. You mentioned the national grid. So, and you also mentioned this term ESO. And maybe it might just very briefly, just to kind of give people who may not be grid specialists, what those terms mean. So national grid is the grid operator for all of the UK.

They maintain the UK grid, although they're actually, the company is actually active in more than one place. But this ESO term, maybe you could just unpack some of that cause it might be a bit more helpful for people.

Rachel Tipton: Yeah. So when we say National Grid ESO, we mean the electricity system operator. And what that means is they're responsible for operating the electricity system. So the grid that is getting electricity from where it's generated to people's homes. And they need to make sure that the electricity, that the amount of like electricity that's demanded by homes, businesses, everywhere, and the amount that's being generated is balanced on the grid.

Chris Adams: Gotcha. Okay. All right. Back to where we were. Yeah.

Rachel Tipton: Yeah. From my own learning journey within Open Climate Fix, there's so much that's happening around the grid, but the basics is that, for example, when I turn on my electric tea kettle, the grid is aware that it's giving me power and then it'll be shutting off that power at some point. And like power grids are balancing, are doing these balancing actions and balancing decisions are being made very quickly. And that's how a power grid works in very, very general terms, which is beyond, of course, my expertise, but it's what we work with at Open Climate Fix, which I find pretty cool. So the product that I work on is the Quartz Solar web application, and it consumes data from several APIs, and those APIs are serving a solar forecast. And so National Grid uses the Quartz Solar app, and I'm using this just as an example. There's other, we have other customers that are also using the Quartz Solar application, but National Grid uses it to make like real time balancing decisions. And so what that means is that they'll see how much solar energy is being generated on the entire UK grid.

And they're able to determine whether or not they're going to be using like electricity that's coming from fossil fuels being burned or electricity that's coming from solar.

Chris Adams: Oh, I see. So the idea being here is that because they, if they've got better information to this, then, you... so things like fossil fuels may be polluting and kind of not great in climate terms, but because they're dispatchable, that you can turn them on, they have a degree of controllability. So this helps you kind of balance some of this.

And maybe this is actually one thing that you, maybe we could expand on some of that in a little bit more detail, because you spoke about that some of this is providing some forecasting to reduce the amount of uncertainty so that you don't need to have so much kind of backup fossil fuels ready to kind of ramp up, for example.

And I think when I saw your presentation at FOSDEM, A, the control rooms just look, look exactly like you'd imagine a control room in a James Bond movie to look, but also the, there was this massive honking gray picture of a, some kind of gas turbine. Maybe you could like talk a little bit about that and how that relates to some of this, because I think how, like you mentioned, we just see power going in and on, but there's a whole set of complexity under the stack beneath us that we're not really aware of.

Rachel Tipton: Yeah. So the, the purpose of spinning reserves for a power grid is that you always have turbines that are running. Then that might be a gas powered turbine or a coal powered turbine, but they're at the ready in case energy is needed. So one of the reasons that a good solar forecast is important is that a lot of these turbines are running on the grid and they're just sitting there at 50 percent capacity, and they're also, when they run at 50 percent capacity, it's also 50 percent efficiency.

And they're not generating electricity for the grid. They're just kind of at the ready in case they need to be spun up or spun back down.

Chris Adams: Oh, I see. Okay. All right. So that's not a million miles away from how, like, if you want to have a computer running, for example, even inside a cloud system. Right. You still need to have a bunch of computers, which are still there and they're still idling and they're still generating, they're still generating heat and using electricity and so on, but they're not necessarily doing useful computation.

So the same idea also works at the kind of one level down with like a honking gray coal-fired power station or gas. So even if it's not generating power, it's still emitting just because you need to have some of that capacity ready for it to respond. Ah, okay.

Rachel Tipton: Yeah. And the the benefit of like having an accurate solar forecast is that you'll have fewer of these turbines that are running at half capacity. And you'll be able to make the decision, okay, we don't need, let's say you've

got 20 of them running, this is not at scale, but there's 20 of them in random places running ready to support the grid. You can make the decision if you have a very accurate solar forecast that, "oh, we'll have, let's say 50 megawatts of solar energy that's coming onto the grid. So really we can turn those off." And if they're, if you're confident with your solar forecast, then you can confidently make that decision and you'll be

Chris Adams: I see.

Rachel Tipton: yeah, you'll be saving carbon emissions and then also the balancing costs of the grid, cause you're not burning fossil fuels at that point.

Chris Adams: Okay. So it's a bit like say if I've got a cluster of machines and I just know that I'm not going to have this much capacity, I can just like auto scale down a bunch of computers and presumably like with a cloud provider, they would switch that off. We would assume they would switch it off or something like that.

But that's kind of what it did. It almost like removing it from this pool of reserve capacity. That's what some of this is doing. And you said one other thing as well, is that just like how computers have like a area where they are, have optimal efficiency. It's the same thing with say some energy plants, right?

So they might not be a very efficient, say 60%, but if they're 80 percent capacity, then they're more efficient. There's a little bit like that, that you, you referred to as well, right?

Rachel Tipton: Yeah, exactly. I won't add any more to that. I also think of it as like, when we work like, for example, a part time job sometimes takes as much energy as a full

time job, but a full time job might be working more, like, it might be more efficient in terms of, like, bringing in income. Like, if you have to go to your part time job every day, you

still have, like, that get up and go in the morning, go to the job.

Chris Adams: Even though there's only that much. Yeah. I mean, even though you only do that many billable hours, you've still got the commute and all the other things, huh? That's actually a really useful comparison. I didn't really viewed it in that, in that way, but that makes it feel quite a bit more intuitive. Okay.

And so this sounds cool. Open Climate Fix has been doing this kind of work for a while. And when I look at the kind of GitHub repo full of OCF's work and speaking to various people, I know there are, there's a very, very kind of high nerd count over there. So presumably there'd been some calculations around like the annual savings or what you could achieve with this.

Because I understood that when I first, when I first saw kind of Jack doing some of this, Jack Kelly, I remember him writing these blog posts saying, "oh, I'm, I'm leaving Google. I want to work on climate change. I'm trying to figure out where I should spend my time." And I think one of the, I remember reading a post where he basically said, "well, I think this is the most effective thing I can do using my specific set of skills."

So presumably there's some number about the savings that could be delivered or that are being delivered by something like this, right? Cause it's been going for a while. Yeah.

Rachel Tipton: Yeah. So, our back of the envelope calculation, which is what we call it, is the back of the envelope calculation, is that the operation of our solar forecasting live service, Quartz Solar, in the National Grid Control Room, saves about or decreases like UK carbon emissions by 000 tons per year.

Chris Adams: Wow. That's not bad for a team of... You're not really a big team, are you? There's like

Rachel Tipton: No, we're around, well, around 12 people. So less than 10

people.

Chris Adams: Wow. That's, that's pretty impressive.

Rachel Tipton: For me, getting to work on a project like this that can like say how it is impacting carbon emissions or decreasing carbon emissions in a large scale way, not just by like using electricity from like solar in my home, but actually seeing that like the energy transition requires that our infrastructure changes and how we operate our infrastructures.

Yeah.

I

Chris Adams: Cool.

All right.

Rachel Tipton: Yeah, it's impressive. I don't know what percentage of UK CO2 emissions that is per year, but that's the amount that we're calculating.

Chris Adams: All right then. Okay. Thank you. So, so just to record some, some kind of, okay, forgive the term grid choreography, you can actually achieve some of those savings like that. All right All right. So, okay. We've spoken a little bit about OCF and we spoke a little bit about some of the grids and how some of this works.

Now, I know that where one thing that, one thing that's kind of key in the Green Software Foundation is that there's a lot of open source code, because this is one of the ways to increase reach. And also in my organization, the Green Web Foundation, we have a similar kind of take on open. And like you folks, you literally have open in the name.

And if you're coming into, switching into a new field, it can be a bit scary working in the open to begin with. So maybe you could just touch on some of that first, before we dive into some of the specifics about this Quartz thing, because so far we've been speaking about open source and things like that, but there was a really, really cool demo that you shared that I...

I think we have to stop teasing people soon and dive into talking about.

Rachel Tipton: First I'll, I'll talk about our, our approach to open source and then the Open Quartz Solar Forecast itself. So the intention is to have as much of our code and data available to anyone who wants to work on decarbonizing the power grid or, I don't know, use the code for other as well.

Last year, we had some mentoring from someone who works in the open source space and they explained the concept of coding in the open versus being an open, like a thriving open source community. And right now we're in that space of transition of trying to offer a pro like a product or a tool, which would be the open source, Open Quartz Solar Forecast that people in the coding community can contribute to.

So I feel as though I started my coding career coding in the open. So someone can go to the, I think it's the Quartz front end repo on Open Climate Fix and see the code for our next JS app,

which is the Quartz solar app. But to actually run that app, you can see the API that we're using, but you'll have to like set up your own database to be able to use that.

So it's not readily runnable, I would say, but it's out there. So if somebody wants to take it template for their own application, they can use it. So I, what I've said is like the, the code for my career is out in the open, it's the good, the bad, the ugly. There's a lot of

commits where I'm just like fixing linting errors and that kind of thing. But it's also nice because then I can point to those repositories when I'm applying for other jobs, or people can see that I've contributed to

an open source project and I personally love the community aspect of people collaborating on code. There's something really beautiful about that collaboration to me and that the community ownership of the code itself.

And so, the idea of Open Climate Fix is that we're providing code that other communities can use or creative people, smart coders who want to certainly implement like an ML model, we're showing them how to do that. Like if you want to implement a large deep learning model. Yes, an individual might not necessarily have the, the data infrastructure to do that, but they can see how we're doing it. And we're giving them those tools. Could be something interesting to add, the energy sector was like one of the first sectors to digitize, I think like in the 70s and 80s. And so some of it's like digital infrastructure is a little bit dated, let's say. Like the

images that you saw of like the control room.

It looks like older digital infrastructure. And so there's this other element to the, like, intention behind Open Climate Fix's work, which is to provide like an upgrade to that digitization for the energy sector. I don't know if that's clear, if that makes sense, but that's one...

Chris Adams: That does make sense. Cause we did an interview with some folks from Electricity Maps and they, they provide like universal APIs across bunches of countries. And some of the things they had to do, I think when I was speaking to Tony Van Sweet, who were telling me about it, I think it's in Singapore.

They need to, because they can't get actual data. They need to basically use optical character recognition on a image that gets updated every five minutes to pull a data point out. Because you just have a system that was designed a certain way and that's how it's been like that for however long. So yeah, I totally understand where you're coming from with that.

Okay. So we spoke a little bit about this and you spoke a little bit about working in the open and about how there's a difference between coding in the open and having like an actual open source project that kind of gets people involved and things like that. I figured, can we talk about the demo now and some of the things you shared at FOSDEM because that was super cool.

Rachel Tipton: Yeah. I ran in this morning to see like what the, if I had like a solar panel at my house, like what the solar generation would be. So what we presented is it's called Open Quartz Solar Forecast, and we have a repo for it on the Open Climate Fix GitHub account. And basically what it is, it's a, it's a solar forecast that is site specific. So if you have a latitude and longitude coordinate, you basically plug that in to the, the model itself, it's a Python package. So you install the package and then you run the function. I think it's like run forecast and you put in your, the lat long coordinates for your site, as well as a timestamps, which will be like

the initializing null of the forecast, Like right now. And then. It generates a forecast, we call it the 15 minute forecast resolution. So you'll have data every 15 minutes out for 48 hours for your solar forecast in a specific location.

Chris Adams: So when you were presenting this, so you mean you're, you're speaking to me from Belgium and you presented this in Brussels, but the national grid is based in the UK. So the, the coverage for this is, it's not just one country. It's, could you maybe talk a little bit about that? Cause that was the thing that really surprised me.

This is why I didn't realize it was possible, actually.

Rachel Tipton: Yeah. So to explain a little bit about the site specific forecast, it was initially developed by using, we had like a thousand different sites around the UK that the model has been trained on. And the idea is that it takes in numeric weather predictions, like those are the inputs, is the actual local PV data, and then also numeric weather predictions. And it'll create a solar generation prediction for that specific site. For like the machine learning nerds, the actual model itself is a gradient boosted tree, which is like a bunch of decision trees making decisions together. That's the extent of my talking about the model itself. It's been trained on UK data, but it can be applied then to any other like, lat long coordinate in the world.

Chris Adams: Yeah This was the thing that was really cause I think you were presenting with, I think it was Zach, Zach Watts, who,

wow, his hair is way longer than his profile photo when I saw him in person I was like, oh wow, so I can use this in Germany, or you can use this in India, you can use it somewhere else.

That was like super exciting for me because the idea that you could just run that on your own laptop to do that was, yeah, pretty freaking cool when I first came across that actually.

Rachel Tipton: And I like to see it as like a distillation of our, the technology and the research that's gone into developing a... like a solar forecast nationally in the UK down to specific sites that might be like a solar farm or like maybe an energy trader wants to have information on a specific site. And then that gets like crystallized down to four lines of code for someone that wants to generate a solar forecast for their home or any other like location. In the world, and it can be interesting because you might actually like run the forecast in a location to see if it would be useful to have solar panels there. For example, that could be a use case that you use.

Chris Adams: And there was one thing that I found quite interesting, is that we've got this whole shift to basically renewable energies. That's the kind of generational as it were. And we've also seen that I believe in various areas, like say subcontinental Africa, or even India, you're seeing an uptick in people adopting new forms of power, basically, or solar, for example.

And this feels like this is something that you could see these tools being applied in new other areas, which where there's, where you're seeing new sources of demand, new sources of load that needs to be served, for example. And like, essentially that you've got something a bit like a kind of, leapfrogging effect, like you mentioned before, like, okay, there's antiquated technology, but theoretically say in, I know India is actually one country where that you folks have been doing some work already, and there's a bunch of really interesting work using even just like kind of grid modeling tooling to actually see how you can get, get off fossil fuels.

This feels like some, it's almost like a kind of leapfrogging at that level over there. You've got the same access to, to these tools in other parts of the world as well now.

Rachel Tipton: And I think it's important to offer a tool that's easily usable and easily accessible, and then it could also be like connected to other sources of like, what are called, it's called numeric weather prediction. So it's not as accurate as our, like national solar forecast, which uses satellite imagery, but it is fairly accurate.

And I think in most cases, in many cases, it's like something is better than nothing. Balancing a power grid. It's good to have like a super, super accurate solar forecast, but having something that would give you an idea of like how much solar generation you would have in any location in the world is really useful.

Chris Adams: Okay, cool. Thank you for that. So you've explained this, so a Solar Quartz open source. We've got a link to that and we'll add it into the show now. So people who are curious or want to try running their four lines of code wherever they're in the world, just to kind of get their, their own forecast, they can do that.

If anyone has really enjoyed the episode we did about Wasm, there's an issue to see if there's a way to turn some of this into Wasm as well, because there's a bunch of Python and there's a bit of like using C++ inside it. But if you do know Wasm, there is an issue open that I opened because I figured, "well, browsers can do this.

So why not just make browsers able to do kind of solar forecasts?" So maybe that might be of interest to other people. So we spoke about this part here, and this is a chunk of this is talking about reducing the amount of spinning reserves you need to have. Like we're just going back to just some of the grid stuff and like back to this whole idea of like carbon aware.

The thing that you told me was that can most of these tools reduce the amount of spinning reserves that you might need for this. And that means that that's, you're kind of reducing the amount of generation you might need to meet demand. All right. Now that's, as I understand it, one of the key ideas around carbon-aware programming is, as you said, it's attacking the problem from the other side.

So rather than actually balancing out supply and demand by just creating new generation from fossil sources, there's this idea that you could, you know, balance this out by reducing the amount of demand you have as well. And I understand that this is not a new concept inside grids. Like people have been doing stuff like this for a while already.

And as someone who's has basically switched into technology and then also working with the grid, there's a bunch of things which are quite counterintuitive. So the question I have for you is that when you're thinking about like grid responsiveness and flexibility, are there any kind of rules of thumb or things you found counterintuitive that you might want to share with other people to kind of help them think about this, honestly, quite new and quite a bit of a complicated concept to kind of internalize?

Rachel Tipton: So something that was complicated for me to understand in all of these discussions is that we're talking about decarbonizing the grid, but there's not a lot of discussion around like minimizing consumption that's something to be aware of is that when we're talking about decarbonizing the grid, we are not necessarily talking about using less electricity or using less energy in general.

So that was something that was not necessarily hard to wrap my mind around, but I think it's an important point to just put out there because a lot of the conversations are around more developing grid technologies where we can connect more renewables, but that we would still be able to consume as much energy as we do, for example.

But in terms of like, what is it, carbon aware programming, I think that it's the way that I thought about this that was useful for me is that I have the use case of balancing a power grid and using a solar forecast to make those grid balancing decisions. And then for an individual or on like a smaller scale, if somebody has what are called flexible assets at their house, so they might have like a battery or a solar panel, they might have like a tiny wind turbine or something that's generating electricity, having a solar forecast in that setting is a little bit different than having it making decisions on the power grid, but it's still sort of a decision making and energy balancing tool that you might be using in your home. Not sure if that answers your question.

Chris Adams: That does help, I mean, because basically we're still trying to figure out a lot of the wording for this stuff. And we do, we know there's a shift from essentially having a grid, which is basically responding to load. You can have a grid, which basically always meets any demand by just creating more generation.

And there's this idea that now you could shift the use of power from certain places to where to a certain time. So like you mentioned for yourself, if you've got something like say, local generation of say renewable energy, for example, if you're able to store some of that, then being able to run off some, some of that, instead of having to draw from the grid later on at times of high carbon intensity, that counts as a climate win, for example.

And I think these are the things that we don't really have ways to really talk about yet. Or there are some papers exploring some of these ideas, but they're not particularly in the mainstream yet, I suppose. So I think this is something that we are trying to struggle with. And also when you see it coming from a number of large organizations, it does give this impression that, It can kind of almost allow people to not talk about absolute amounts of load.

And when we have seen massive new amounts of load coming onto the grid, especially with data centers, and we're seeing extremely aggressive projections and total energy use. You can see why people would be skeptical about some of these ideas, but I kind of feel that we're aware that this is happening outside of technology, that the idea of responsiveness to the grid is something that happens outside of technology as well, and has been going for a while.

And it's not like a totally new concept, basically.

Rachel Tipton: I think I have two things that I'd like to add to that. One is the idea that like, so there's certain technologies that will inform a user when renewable energy is on the grid. And so some people are using the grid in those moments when there is renewable energy, and I think that there is the potential for individuals to create change, not by just having flexible assets at home, but by saying, I'm going to demand energy and use energy when it's renewable on the grid, and then the grid operators and the energy ecosystem itself, I would hope would then respond by providing more renewables on the grid. I'm talking in vagaries, I feel like in generalities, but that would be one way to shift the, the type of electricity mix, I guess, as you call it on the grid. But then also from the other side that people, I think it's really important that people are aware that our electricity infrastructure is going to have to handle a lot more electricity, whether that's going to be like server centers, like computers in different places, but also like EVs, everything, if we're going to electrify everything, we're actually going to be using much more electrical energy in the future because it's going to be replacing those

Chris Adams: Yeah. Fossil fuel energy. Yeah. heat pumps instead of burning in a furnace, for example. Yeah.

This is one thing that I kind of like, just, I realized recently, actually, is now that lots of places which are taking on, for example, in Germany, right. We see a load of heat pumps being rolled out, especially, I believe you're seeing this in France and Belgium.

And these are places where we don't normally have aircon, right? And if you're listening in a place which uses aircon, the idea that like we've never really used aircon is kind of mind blowing. And now there's going to be a bunch of us with heaters, which can also cool things down. And like, like you mentioned, there will be a whole load of new energy being used because this is the only way that you can provide heat or cooling without actually having to burn fossil fuels.

So we are going to seeing a bunch of this. All right. We've totally gone down a bit of

Rachel Tipton: Yeah. Gone down a deep rabbit hole that we don't have time to elaborate,

Chris Adams: So I'm going to park that, but I'll share a couple of links. So we're just coming up to time and I just wanted to provide a bit of space to let you talk about like what, what's catching your eye that you would like to draw people's attention to.

So normally we talk about open source projects or maybe a magazine or a video or anything like that. Yeah. If there's anything that you would point people to who might have found this conversation interesting, what would you like direct people's attention to? Because yeah, now's your time, basically.

Rachel Tipton: So off the back of this particular conversation, there's a book called Real Decarbonization by Tisha Schuller, and it talks about how the energy transition is going to involve oil companies, Shell, BP, these large entities. And I feel like if people are involved in the energy transition, it's a really useful book to read, even though you might not agree with everything that she's saying and everything that she's talking about. One of the, the projects that has caught my attention lately, that's more, it's my artistic side. It came from an article in the MIT technology review called recapturing the whimsy of the early internet. And it's a movement called the HTML energy movement. I don't know if you've talked about it before on...

Chris Adams: Never heard of this. Wow.

Rachel Tipton: Yeah. So it's people who are making these HTML energy sites and they say, basically, they're celebrating the rudimentary character of HTML as a language, which I know a lot of people don't necessarily consider HTML to be a programming language, but they are pitching themselves as hidden gardens on the internet.

So I've listed a couple of links to those websites that are very, very relevant. Very minimalist in some sense, but sort of artistic places to poke around and see what is being offered. So there's one called HTML garden and then terrarium of many sceneries from the MIT technology review, which I find to be a good source of information about tech that I wouldn't necessarily be exposed to at my workplace.

Chris Adams: Okay, cool. So that was htmls.garden and sceneries.site. These are two examples of this kind of HTML garden or HTML energy sites. I'd never heard of that at all. Wow. Cool.

All right then.

Rachel Tipton: Might be a bit off topic, but they're kind of fun to explore.

Chris Adams: All right. Thank you for that. Okay. So if people have enjoyed this conversation and they want to follow on some of the work that you have, where should people look? I mean, Rachel L'Abri Tipton is a relatively strong name for Google, right? It's not like Chris Adams or, you know, John Smith, for example. So should we just be looking for Rachel L'Abri Tipton on LinkedIn or GitHub or where, where would you direct people to?

Rachel Tipton: Yeah, so I have my LinkedIn is Rachel L'Abri Tipton, GitHub is also Rachel L'Abri Tipton, and then I have a sub stack that I write, which is the Tech Generalist. So you can also find me there and I've provided just my Linktree for the podcast notes. So all of those links are in the Linktree.

Link tree Yeah. And then also wanted to just pitch a small pitch for myself. My contract with Open Climate Fix is ending at the end of April. So I'm open to new opportunities currently, whether that's in the energy space or other places, or just collaborating on projects. So if people want to reach out, I'm more than happy to talk full stack developer opportunities.

Chris Adams: All right. Brilliant. Well, Rachel, thank you very much for your time and explaining some of the inner workings of how. Basically grids work at a national level and yeah, I hope your basement gets sorted out with the flooding and...

Rachel Tipton: I hope so as well.

Chris Adams: Yeah. And have a lovely week. All right. This has been fun, Rachel.

Thank you.

Rachel Tipton: Yeah. Really fun. Thanks, Chris.

Chris Adams: Hey everyone. Thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again and see you in the next episode.

View Details

This week, Chris Adams is joined by Asim Hussain and Anne Currie for an engaging chat on the present and future of legislation around AI and Green Software. Our guests share their hot takes on various topics such as the usefulness of proxies in measurement. With backgrounds in climate and tech, and a future full of green energy, they share their insights into what we might expect, and hope for, from the future. Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Tom Greenwood: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Sustainability, a surprisingly successful KPI: GreenOps survey results [05:36] * Cost as a Proxy for Carbon – the inconvenient truth | Kainos [13:41] * Technology Carbon Standard [25:11] * Executive summary – Electricity 2024 – Analysis - IEA [32:15]

Events:* Carbon Hack 24: Where measurement meets innovation, and impact knows no bounds [44:51]

Resources:* Amazon.com: Building Green Software: A Sustainable Approach to Software Development and Operations | Anne Currie et al. [02:20] * State of Green Software [06:25] * https://stateof.greensoftware.foundation/survey/ [06:30] * GitHub - Green-Software-Foundation/green-software-maturity-matrix: A green technology self-assessment tool for organisations [14:48] * Why we should be intentional about the mental models we use for thinking when we think about digital sustainability |Chris Adams [23:52] * Options to make software greener without changing the code, and how to remember them | Chris Adams [23:58] * Nuclear? Perhaps! | Volts | Fanfare [37:37] * JRC Publications Repository - Energy Consumption in Data Centres and Broadband Communication Networks in the EU [38:56] * https://www.linkedin.com/feed/update/urn:li:activity:7165707074901934082/

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Anne Currie: AI is eating the world, and it's incredibly requiring of energy. But I'm also going to come back to something that all three of us have said previously, which is, "does it matter if AI uses huge quantities of energy but it's all green?" Then it doesn't matter. And it's not, and that energy isn't necessarily being used for other things, because nobody wants it to heat their home in wherever it is, the middle of nowhere, where we've put our data centers.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello, and welcome to another episode of the Week in Green Software, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. This podcast, Environment Variables, was initially set up as an example of what you might call pun-driven development between myself and Asim Hussain, back when we were both organizers at an online community called ClimateAction.tech. And, to be honest I kind of missed our chats, so I got in touch with him and asked if he'd like coming back on the podcast and talking about what he's been up to at the Green Software Foundation and I was very happy when he said yes. And likewise, Anne, our other guest today, she's been a fixture in green software for a while and has actually been working in the community working group as well as working on a book about green software called, unsurprisingly, Building Green Software.

It's nearly out, so I figured it was nice to kind of chat to her as well. So, that's what we're looking at today. Anne, Asim, lovely to have you on the podcast again. For people who've never listened to this podcast, can I give you the floor to talk about it? I'll go with you first, Anne, because it's alphabetical, and then I'll hand over to Asim.

So, yeah, Anne, the floor is yours.

Anne Currie: Hi, Chris. Thanks for that. My name is Anne Currie. I am one of the community co-chairs of the Green Software Foundation. I'm also the CEO of a training and consultancy company in green software called Strategically Green. And as Chris said, things that I'm doing at the moment, I've been writing the last year, I've been writing with, with two co-authors, also from the Green Software Foundation, Sara Bergman and Sarah Hsu on the O'Reilly book, Building Green Software, which will be out next month. So that's all very exciting.

Exciting. It's very exciting.

Chris Adams: Okay. Thank you, Anne, lovely to have you back. And Asim, I'll hand over to you as well, actually.

Asim Hussain: Thank you Chris. So my name is Asim Hussain. I am now a full time, the executive director of the Green Software Foundation. I'm really excited to be here again. What are the things I've been working on recently? Just keeping the Green Software Foundation running, has been basically my main activity. But the other thing I've been really heavily involved with is one of our projects which is called Impact Framework, which I'll probably mention a couple of times because it is completely on my mind 24/7.

Sometimes I'm asleep and I'm dreaming of it. If I'm getting my kids to sleep, I usually have the GitHub pull requests open and I'm reviewing them. So it's on my mind constantly. So yeah, that's me.

Chris Adams: Thank you, Asim. Last time you were on this podcast, we were talking about the wonders of fungi and the, the carbon fixing powers of mycelium. How are the mushrooms doing?

Asim Hussain: My mushrooms don't, I've not been doing too well. I seem to have lost my mushroom green thumb. My last attempt kind of really failed in a very moldy way, but I have some new ones growing them from scratch again. So I'm going to give that another go.

Chris Adams: Well? Okay, I guess. Do you say green thumb? I wish you green thumbs or brown thumbs, or what's the color correct color? For? For, for fungi? Yeah.

Asim Hussain: Well, you probably, you just like to have that, that mushroomy smell. That's the way you test it.

Chris Adams: I wish you lovely, mushroomy smells in your future then, Asim. Alright, okay. Hi folks, and if you're wondering who I am, as I mentioned before, my name is Chris Adams, I am the executive director of the Green Web Foundation, which is a non-profit based in the Netherlands, focused around meeting a fossil free internet.

By 2030, I'm also one of the co-chairs of the policy working group inside the Green Software Foundation and a regular host on this podcast. So if you're new to this podcast, what we do in this kind of format is The Week in Green Software, we look at some of the stories that we thought were interesting that we might want to share with other people to basically give an idea of what's happening in the field and in many cases, get lukewarm or hot takes from our guests on the day.

And I think that's pretty much it. We will share a link to every single story. And like we mentioned before, the transcript and the show notes are both available at podcast.greensoftware.foundation. But we also will link to a GitHub repo. So if there's a typo, or if there's a mistake, or there's something you'd like to link to, then you can also open a PR.

And we do accept PRs, so that we've got a useful record from other people who are trying to learn more about green software as well. All right, Anne, Asim, I'm assuming you're sitting comfortably, right?

Asim Hussain: Or somewhat, I bought a meditation chair recently. I'm sitting cross legged at the moment.

Chris Adams: Asim, I'm going to hand over to you for the first story because this is actually one thing that takes me back to some of our Climate Action Tech Days, the very, very early 2020s. So this is a story, Sustainability, a surprisingly successful KPI, this is the Green Ops survey results, we'll share the link to it, but the short version is, and the headline is basically, "if you want to save money in enterprise, turns out that sustainability as a KPI is more important than cost." This is one of the key findings of the recent GreenOps survey that was actually part funded by the Climate Action Tech Mini, Mini-grant fund that was running through this.

I find this quite interesting because it's, well, this is the first time I've seen a survey, which is actually scaled out like this. And I suspect there's gonna be some takes coming from this. So, Asim, maybe if I hand over to you first and then Anne, I'll let you come in and then we'll see what goes on from there.

Yeah,

Asim Hussain: Well, yeah, and this is really interesting. And I think it reminded me as soon as I read it, it reminded me of, do you remember when we ran the State of Green Software? We released it last year. We did a big survey with it as well.

One of the questions there, I, I, I still come back to it because I think it's very interesting. We ask people to rank in order of importance, cost, performance, sustainability, reliability, and security. So you actually, you couldn't just say, you have to actually literally drag and drop these things in the order of importance that you thought it would be. And I thought it was really interesting because the number one item that came out was security, which is interesting, but also very valid and it is, I suppose, you know, what a lot of people and organizations do you focus on. Second was reliability, which is, you know, understandable as well. Third was sustainability. And then came performance and the last, the very last item was cost, which was fascinating to me because to a lot of people, they would assume that cost is the most important thing. And there's something, I remember the researcher at the time, she talked about this concept. I think it was called onstage and offstage when you give information. Like if you're like, if you're on stage and someone asks you a question, you're going to say, "Oh yeah, cost! Yeah, cost is the most important thing to, yeah, we'd love, I love saving costs.

I love also, you know, getting promoted at the end of this quarter," but like off stage, and I think this is interesting, I think off stage, when you really ask people, when they know they're anonymous, when they know they can be truthful regarding what it is, I think this speaks to the fact that to a lot of people, sustainability is important and they do think it's more important than cost. And I think, I don't know how we can kind of get this circulated in such a way, and I suppose this article is doing a good step in that, like, how do we get this circulated in such a way that people understand, like, you know, this is important.

Anne Currie: One of the interesting things here is that all of these things are very aligned, aren't they? That being sustainable does cut your costs and it does improve your security because an awful lot at first stage of being sustainable is to turn off machines that you don't really need anymore. And those machines are your security holes. So, you know, there's a massive alignment between security and sustainability and resilience and sustainability as well. You know, the resilience of auto scaling rather than the resilience of hot backups or cold backups, it's more resilient and it's more efficient. So it's kind of like all of these things are highly aligned, but I guess it all comes down to that whole thing about extrinsic versus intrinsic motivations, isn't it? That people like to feel that they're doing good at the same time as they're doing other things.

Chris Adams: Well, there's actually, there's also a bunch of research that, I think the correct kind of term in psychology kind of jargon is this value perception gap, where everyone basically thinks that they're, they might care about sustainability, or they might care about fellow, they don't think everyone else does, so therefore they're going to self censor and say they don't actually care about this so much, or they'll talk about the thing that, as Asim mentions, makes them more likely to get promoted, for example, or something when they're on the stage like this.

The thing that we've done, Asim, I'm really glad you mentioned the State of Green Software report. I've shared a link to that and also the survey data that we had there. This story in particular, this GreenOps one in particular, the actual underlying data is available for anyone who wants to do any kind of research themselves.

And I think there's a couple of really interesting other things that came out of this, is that there was this idea about, if you look into the story, it talks a little bit about where people need to feel support for example like from the c-suite what are the kind of pre-determining things in order to you to provide some of the kind of cover for this there's a bunch of other stuff inside this that's worth a look actually so yeah I thank you both for like your actually quite warm takes today about this. This is quite cool.

Asim Hussain: But I think it's all about motivation and that's really what this is all about. It's not like what is actually the right thing for you to focus on in software. It's more a question of what am I motivated to work on? Like one of the things in the early days of this whole space is like, well, cost is important, but people aren't waking up in the morning going, "Oh, Today, I want to reduce, you know, annual turnover expectation by 0.02%. Like, and that's, what's motivating me today." It's important to whoever needs to do it. But what motivates people is actually, "I want to do something." This is important to me that, that actually reduces some of the emissions of my software. And I'm going to work a lot harder on that than I am on reducing costs by 0.

2%.

Chris Adams: Yeah I guess maybe some people are, I don't know, I mean, maybe we'll come to the day where someone says "do you know what? I just really like returning value to shareholders." Like, that is what, maybe that's a thing. I mean, they, presumably they... but, yeah.

Anne Currie: Well, I'm going to come in with hot take number two, actually, because I had a very interesting story this week, which is very related to this and that security being the number one motivator. If people actually acted on good security practice, it would massively cut carbon emissions. The going through and closing off all the machines that you really know you need to, if you did a proper security review and you close off all your old machines that you weren't using anymore, that would be a really good security move, would also massively be more sustainable.

But not only that, I heard a very interesting tale this week from a company that wishes to remain anonymous. They did a security review a couple of months back, which, which was about identifying and turning off effectively, well, not zombie services, but services they knew they didn't need anymore. And as part of doing that, the security team identified a machine that was running at 100 percent CPU. So they thought, "well, hang on a minute, that's been hacked. You know, someone's binding Bitcoin on this." They handed it back to the ops team and said, "what's going on here? Sort it out." The ops team took a look at it. It turned out it was running a load test that had been, that, that had been turned on three years previously and never, never turned off.

So the security review identified the problem as fundamentally a cost problem, but, but more than anything else a sustainability problem. So if you do security reviews, it's actually one of the best things you can do for being greener, because you, you just stop doing stuff you shouldn't be doing.

Chris Adams: And I think I'm going to need to share a link in the show notes to the meme saying, You cannot have a cluster if, if you don't have a cluster, because that seems to be a kind of reference to some of this here. Okay, thank you very much for that, Anne. Just for people who are curious, as a bit of context, this survey was actually carried out by a gentleman called Mark Butcher, I believe, who works at a firm called Posetiv.

The actual process of why this was funded was basically by donations from members inside a community who just put some funding in. And there's a couple of other mindy grants that are ongoing now. There's one to create a sustainable AI manifesto, and there's another one which is a playbook for becoming a climate-conscious product manager.

So it's kind of nice to see some of this stuff. I'm looking forward to more things like this being created because you don't need that much money to get some really interesting results and things coming out there into the kind of, I guess, the public discourse. All right, cool. Anne, Asim, are you comfortable with us moving to the next story?

Asim Hussain: Yeah.

Anne Currie: I am.

Chris Adams: Alright, okay, so the next story here is a blog post from Kainos.com. I believe they might be members of the Green Software Foundation, I forget, but this one is basically, the headline is Cost as a Proxy for Carbon, the Inconvenient Truth. And I'll just share a kind of quote from the paragraph, from the piece.

It says, "Many technology related articles and major cloud service providers promote the idea that cost is a proxy for carbon emissions. This suggests that optimizing and reducing your cloud costs can lead to increased sustainability. But is this entirely true? While there is some truth to this statement, it is critical that limitations to this approach are well understood."

So I guess now I should, while I've got access to two experts, I'm going to kind of put it to you two. Anne, when is cost a good proxy for carbon? And when is cost a bad proxy for carbon? Because I've understood that you might have some opinions on this as well.

Anne Currie: I have very strong opinions on this, Chris. I think that at some stages, it's an excellent proxy for carbon. And at some stages, it's gone beyond. It's not really a great proxy anymore. So it depends is the answer. So I'm going to, I'm going to pull in one of our new projects at the Green Software Foundation that I'm the lead on, which is the Green Software Maturity Matrix, which is about the fact that there are kind of, we're all at a different stage.

Most of us are at stage one. We haven't really started down the road of becoming green in our, in our systems. And at that stage, cost is actually a pretty good proxy. If you can halve the number of machines you have, or you can turn off stuff that you're not using, that's a really good way of cutting carbon. But as you get towards the end, you become quite sophisticated and you're doing really clever stuff with tuning and demand shifting and demand shaping. It's not quite such a good, a good measure anymore, but you know, just use your, we all went into tech because it's clever and it's interesting and it's complicated and it's... just use your brain.

Just everything that you save money on is not, is clearly not going to save you carbon and everywhere that saves carbon is not always going to save you money. But as a rule of thumb, if you're turning machines off, that's good.

Chris Adams: Okay. All right. So basically, if you have fewer machines, you have fewer emissions. That's the kind of broad strokes approach that you seem to be out talking about. Now, Asim, I see that you've added a note here that you've seen examples of resizing, reducing emissions, but increasing costs. So maybe you could talk a little bit about that.

And then I'll maybe come in with some takes at my end as well.

Asim Hussain: I've got, yeah, I've got some other hot takes on that as well, actually, but yeah, I have seen, I have not seen many. I have not seen many. So I think I just wanted to point out that, but I don't think that's necessarily, and the absence of information, or what is that statement?

Anne Currie: The absence of information, evidence of absence is not,

Chris Adams: Absence of evidence is not evidence of absence, right? Yeah, yeah.

Asim Hussain: There's a certain absence in our podcast here right now. The, but that effectively, like I have seen some examples of people like when, and where they've tried to do some sort of downsizing and they've happened to have just enough measurement infrastructure in place, which is usually the problem, to actually like determine, Oh, actually, Oh, wow.

That actually increased the cost. Cause you know, sometimes you can right size, but the machine you move to actually costs more and overall just ends on a bit more money, but the actual emissions is less. So it's rare, but I think that's more a statement of we're just not measuring this. But I think more importantly, I think cost has two problems as a proxy for carbon emissions. Number one, and the same, this is the same problem you have with carbon emissions, it's the same issue. A, it's a lagging indicator. Like if you're developing a piece of software, you only know the cost of it after you've rolled it out and you've done it and you've moved on for a month onto the next project, and then somebody goes, "by the way, that's like slightly more expensive than we were expecting."

Like, "Oh, I suppose, but do you want me to stop working on this other project now?" And I'm like, "no, no, no, you carry on that project." It's a lagging indicator. It's like after everything's happened. And I suppose that also means it also has all the other problems that you have with using carbon as a proxy for driving action to reduce carbon emissions, like If you like the, the issue with looking at cost is like someone saying, "well, I'm spending like 3 million on this database and 4 million on this other thing." And you're like, "well, I don't know. I'm, I developed an application. What is my costs?" And so like you have this problem of really it's the problem is more how do you actually get information to the people at the coalface so that they can make decisions to actually reduce the emissions directly? And I think that's the challenge with cost is that you can't, it has all the same problems as carbon in trying to get information to people to actually, so they can know what to do. Because you can tell a department what their cost is, you can tell a department what their carbon is, but can you tell developer X on team Y the impact of a choice they're going to make? Is, I think that's really where we want to get to.

Anne Currie: And I think we're saying exactly the same thing there in a slightly different form. You're saying that it's not a good measure when it comes to tuning what developers do, and I totally agree with that.

I'm saying that generally for where everybody is at the moment, a lot of the good tuning comes at, comes from ops teams rather than development teams. And for ops teams, cost is not so much of a leading indicator. It's actually quite close to what they're doing day to day. So it's a really good metric if your ops team are the one who are doing the tuning to reduce carbon. Not perfect. As you say, it's a terrible, you're better off with performance being a metric if you're doing the development. Yeah.

Asim Hussain: No, you're right. We're talking about different audiences. Yeah. So yeah, to the, to an ops team who are, whose job is to deal with the software after it's deployed, yeah. I suppose it's not a lagging indicator. It is their main indicator.

Anne Currie: But I think that we're in agreement that it's a great proxy for ops teams, but not a great proxy for dev teams.

But it's, but as you say, also, it's not even always a great proxy for ops teams, because often the best thing you can do in terms of operations is to move the whole, your whole shebang to somewhere with a greener grid, but that might well not save you any money.

Asim Hussain: True.

Chris Adams: Google have some interesting stuff inside this and that. They've got some region pickers which do expose some of this. You can prioritize late cost and carbon. And like, if you cared about carbon, you might move things to Switzerland, for example, compared to running it in, say, other parts of Europe or, say, even America, for example.

So there's stuff like that, that I think you can actually do. But I think when I read through this piece, there was a couple of things that kind of outline on this, like, yes, this can be a bit more complicated, because this kind of assumes, like, if you have this cost as a proxy thing, in many cases, you might have like a commitment to maybe a 50 or an 80 percent discount on your cloud bill, if you've agreed to spend a bunch of cash now.

So now you've got totally different incentives to be doing what you're doing. And like, when we start talking about different instruments that people use to essentially affect the cost of cloud builds, it can be a bit harder to talk about. And there's also this other thing that, let's say you're looking at something like, we don't know which services have particularly high margins versus low margins, which ones lose money versus making money.

Broadly speaking, in 2024, you might assume that for the same amount of work, doing something with, say, a serverless platform like AWS Lambda might be more expensive for the same amount of requests as a dedicated box, for example. So, if you looked at that, that might assume that it's that much more carbon associated.

There's questions there, and like, as Anne mentioned, when you start looking at the edges, you can definitely find all these different edge cases which make it harder to really kind of use. But as a rubric, as a kind of starting point, it may be better than having nothing, basically. And it's not like technology is immune to us looking at easy to measure numbers and assuming that's automatically the truth.

Asim Hussain: Now that is definitely one of the things I would say. I kind of came hot on cost then for a second. But like, what I would say is that in the absence of anything else, which is by large the problem that we have right now, it is one of the best measures that we have. But like, I think we need to move the world forward to better measures eventually. But it is the best that we have right now. If you don't have anything else.

Chris Adams: If we had actual energy

Asim Hussain: If you had actual, yeah,

Chris Adams: right? So quickly, it's a commodity.

Anne Currie: It wouldn't. Because even if you've got energy, you know, I would say this, it's still very hard to do a like for like comparison. It's not like performance. Performance is a really good measurement for performance. You know, it's like seconds. How many seconds did it take to do that thing?

I mean, you can put it on different sized machines, different speeds. There are even issues there. But as we all know, you know, sometimes the grid is green and sometimes the grid is not green. So even carbon measurements, you could be running exactly the same thing. Everything can be under your control, but unless you're doing demand shifting and shaping or work shifting and shaping, as now seems to be the more common and correctly, then the name seems to be shifting from demand shifting and shaping to work shifting and shaping, which

is a much better word for it.

Chris Adams: New to me as well, actually. Okay.

Anne Currie: It was, cause I used to complain all the time because

demand is

Asim Hussain: Did you start changing? Did you start changing the words, Anne?

Anne Currie: I, it wasn't. I, in the book, it's all demand shifting and shaping. And I do say it's a really terrible description because the demand hasn't changed. As far as we're concerned, the demand comes from users and the users still have demand and we're attempting to meet the demand that they have. We're not intending to shift that. But the name, I think the words demand shifting and demand shaping came from the grid.

And as far as the grid is concerned, we are the users, not the end users. So what they're talking about is our, as the tech industry, our demand is shifting and shaping, which it is. So there's some confusion about who's the end user in this scenario.

So I have seen some people start to use work shifting and I wish I'd known that they were going to because I've just written a book in which I didn't use those terms.

Chris Adams: Ah, well you heard it here first. Alright, what I'm going to do is I'm going to add a couple of show notes both to basically your book, Anne, and a couple of blog posts. I've written one post recently, a while ago, called Options to make software greener without changing the code and how to remember them, which essentially I'm taking some of the papers I saw at Hot Carbon and trying to translate them into kind of layperson's terms.

So that might be a bit easier, because I think that I agree with you. Demand shaping and demand shifting. These are ideas that have come from the electricity sector that aren't as intuitive to developers, actually. And maybe, I think we've probably got enough there because we've got a few more stories to run through.

Are you comfortable if we move to the next one, folks?

Asim Hussain: I am yeah.

Chris Adams: Okay. All right, so this one is introducing the tech carbon standard. So if you go to www.techcarbonstandard.org, this is a website for, not a standard per se, but a proposed standard from an organization called Scott Logic who are based in the north of England.

This was actually revealed at the state of open conference in February, and the TLDR is the Tech Carbon standard is developed as an approach to classifying an organization as technology estate to enable consistent analysis and benchmarking of its technology carbon footprint. The standard takes inspiration from the globally recognized GHG protocol and its emissions classification in scopes 1, 2, and 3.

And although you can't see this in the audio format, we've shared a link to it. It's basically a diagram, more or less highlighting where you might think emissions take place. Both in the view of the GHG protocol, which is like pretty much the de facto standard for reporting carbon, but also mapped to the kind of bits of software that you might have.

So there's a notion of upstream emissions, where you might be kind of purchasing cloud software, for example, there's operational emissions, which might be talking about you running servers on premise, or something like that. And there's downstream emission, things like end user, and like network transfer, and stuff like that.

So, this is, this is something that is kind of new, and I, I found quite interesting, because Asim, I know that there are very deliberate decisions behind the SCI, the Software Carbon Intensity spec, which has been put forward by the GSF to not try to tack too closely to the, to the GHG protocol.

And it might be worth just to see what you folks think of this, because I think this is quite interesting. And the idea of it being entirely open for other people to use and riff off, I think is quite helpful actually. So maybe I'll hand to, I'll hand to Asim first and then to Anne actually, because Asim has some very, he's got some things he definitely wants to say about scoped emissions.

Asim Hussain: I'm coming in hot.

Chris Adams: Yeah.

Asim Hussain: No, I'm not coming in that hot. No, I think it's, I think it's good. I think, look, the GHG protocol was built from the perspective of an, an organization that does manufacturing that, that is what it has been based on. That's why if you're a manufacturing organization, it makes complete sense. Your scope one, your scope two, and your scope one is, I don't know, should we summarize it for people? That the scope one is kind of, if you've got. If you've got an oil drum in the back garden and you're just burning oil. And I don't know many manufacturers that do that, but that would be your scope one emissions. Scope two is the emissions from the electricity that you purchased. And scope three is from all the things that you bought to build the thing, the physical thing that you sell. So it makes a lot of sense from that perspective, but for our world, it's really problematic and especially scope two. Like if you say the word scope two, it's almost meaningless in our world.

Because if you, if I say scope two as a proxy for electricity, well, it's not because if you've got an on premise data center and if you're running your software partly on your own servers and partly on the cloud servers, and you said scope 2, your energy usage, your scope, this is, I can't even explain it, it's so complicated, like your scope 2 is the energy, but only your application can choose, but only on the hardware that you own. The energy that your application uses on the cloud providers falls under Scope 3, Category 11. And so, like, it's really hard to kind of figure out, well, what is the energy? It's like, you have to kind of have this thing. And really, when you say those words, it's so contextual, when you say scope two, it's not what it is to you. It's what it is to the audience that's sitting there and it means different things to different people. So what I do like about this is the attempt that they've got to kind of really look at them and you know, they've got upstream emissions, operational emissions, downstream emissions. When you say operational emissions, it will mean the same thing to everybody you're speaking to, and it's not context specific. So I think it's good from that perspective. It clarifies some of the stuff. So I think there's some good stuff here. I do. Yeah. I think it's some good thinking. I think my advice is to get into detail, when you click on servers and storage, the only description is the energy consumed by on premise servers and data centers. And I suppose we all know there's a lot of, there's a lot of meat behind that one that you've got to, you've got to flesh out. But yeah, I think my rant on scopes is over. So I'll pass it on to other people.

Chris Adams: Thank you for sharing that particular point of view, Asim. Anne, I suspect you might have something to share as well here. So yeah, what did you think when you saw this?

Anne Currie: Well, I always think all work in this area is great. All discussion we're doing around this is great. Fantastically great. But I always think about taking it back to my Maturity Matrix projects on the GSF Maturity Matrix project. You need to do different things at different times. So this information is useful to you in different things at different times of your journey.

So for most of us at the moment, we're not doing anything at all. Just, you know, you really don't need that much data. You know, your scope one, scope two, scope three are not immediately critical to most people who just need to turn off the machines they're not using anymore, right. Do a bit of right sizing.

Have a think about what they're up to. Start to think about, are they in green regions? What are the future? What platforms are they choosing? Are they likely to be aligned with the green future? To start with, where most of us are at the moment, you don't need a great deal of data to really make a huge difference.

So it's absolutely fantastic that they're doing this work. And that we're doing this work. Everybody's doing this work. We don't want to lose sight of the fact that for almost everybody at the moment, we don't even need data. We just need to start to, to use best operational practices.

Chris Adams: All right, so you don't need, you don't need to wait until you have data. You're, or don't, sorry, don't need to have all the data, is what you're saying, because I don't think you're saying you don't need to have data to work on this. It's more like you're not, okay, all right, I think I know more or less where you're going with this.

Okay, one thing that I'll share with this that I thought was quite interesting was, this is the first time I've seen someone really outline scope one, actually, like burning fuel for generators and things like that, because this can add up, and there's also steps that you can take to basically, reduce the environmental impact of running generators themselves, actually.

So, you know how most of this stuff runs on diesel, basically, right? So, diesel is what you'll be burning in a data center, most of the time, if you're not running on electricity. And, this will be tested quite a few times a year, for example. There's a thing called, I think, Hydrogen Treated... oh God, what is it again?

There's a specific treatment for diesel, which basically is a way to remove all the kind of bits of dead, long dead animals and plants from it, which essentially make it less harmful for people nearby to be breathing it. And that can actually come from biological sources like, or biogenic, as in things which are non-fossil, for example, there are non fossil sources of HVO diesel that you can have, which is one way that you can reduce some of the footprints on this. And although it's only a few hours in a given year, maybe 100 hours in the 9 000 hours that you do have, that's very dirty stuff and it has a very kind of localized impact on people.

So it's kind of nice to actually see that called out for the first time. So I found this quite helpful and it was when I first came across it and I'm glad to see it open for a bit of work on. Alright, shall we move to the next story, or Asim, you've got something you want to share?

Asim Hussain: Just a hot take.

Isn't it funny that like these buildings, which contain some of the most advanced technology that human beings have ever created in the history of our existence, maybe, that are completely chock full, that are huge, just in case they go down, we burn dead animals to, to power them.

Like we, if, if we can do that with the technology inside the buildings, we can do something with the technology that powers them.

Chris Adams: I think, okay, alright, inspiring.

Asim Hussain: heard any of that. I don't

Chris Adams: we've got one more story, and then we'll wrap up a bit. So, we're going to link to the IEA's recent report. So the IEA is the International Energy Agency, and they made some headlines earlier on this year with their link to the electricity report.

Basically, they talk about what's happening over the next 10 years with electricity. And one of the headlines was they were saying that electricity consumption from data centers in terms of like AI and the cryptocurrency sector could double by 2026. So I'll just use the quote that I pulled from it, which was "electricity consumption from data centers, artificial intelligence, and the cryptocurrency sector could double by 2026.

Data centers are significant drivers of growth in electricity demand in many regions. After globally consuming an estimated 460 terawatt hours, in 2022, datacenters total electricity consumption could reach more than a thousand terawatt hours in 2026." So that's a doubling in essentially, what, two years?

This is particularly interesting because this is way higher than their previous figures that they used to have which were around 200. So Something's changed with these numbers for them to be that much higher. And I figured I'd open the floor to either of you about this because this has got a lot of pushback from the data center industry.

But there's also people who work in the energy sector saying maybe there's something to it. So Asim, maybe I'll ask you what's your view on this one?

Asim Hussain: Well $7 trillion worth of chips cost a lot of energy to power. So, you know, like I think AI is a lot bigger than we think. And I'm not saying that in a way that is in any way negative. I think it's just, we have to accept this is the future that we're living in. This is the current present that we're living in. I strongly suspect that some of these numbers are taking that into account. The growth in AI has been significant. We all know on this call that the previous dirty secret of data centers where most of those servers were idle. In a future of AI, those chips are not going to be idle. They're going to be running at a hundred percent.

So like, I think we've spoken on this call previously about, you know, various previous reports that talked about, you know, given the current trajectory by 2040, the tech sector will be like 14 percent of global emissions. I wonder if anybody's doing any analysis to revisit, well, now, given what we now know about the complete, AI will take over everything. It is taking over everything right now. How does that look now? Where will we be in 2040 with the current growth in AI? Will tech be half of all emissions? And will we just be sitting there, you know, being carried around by robots and being fed by little tubes like that robot show? But I think, I strongly suspect that they factor that in. And, and I wonder if it's an underestimate.

Chris Adams: Okay. All right. So that's what you got from executive director of the GSF, but that's not his official opinion. Yeah, yeah. Anne, what about you? Where are you on this one here?

Anne Currie: Well, I think Asim's right that, and those numbers are probably right, that AI is eating the world, and it's incredibly requiring of energy, but I'm also going to come back to something that Asim and I have both said previously, all three of us have all said previously, which is "Does it matter?" Because AI is a really good example of a workload that works well with the fact that some places are much, have much more potential to generate green power than others. It's a latency insensitive workload that could be running in Greenland, not that Greenland has a massive data center industry at the moment, but it could do. It could be running further away. But, but also I think it feeds into something that I was reading that almost comes full circle with the discussion we were having earlier about data centers and how they're used and whether or not they're used well.

I mean, the ideal at the moment is we'd start building data centers as places where there was water for cooling and green energy for powering the data centers. And then you have to worry about the embodied carbon, but you don't have to worry about the, you know, if AI uses huge quantities of energy, but it's all green, then it doesn't matter.

And it's not, and that energy isn't necessarily being used for other things because nobody wants it to heat their home in wherever it is, the middle of nowhere, where we've put our data centers. But we need to have a think about data centers more generally. Something that comes up quite a lot is water use in data centers.

So at the moment we can't necessarily put data centers that could run on solar in places where it could run on solar because there's a lack of water, but there was an interesting, I read a very interesting article about that and I shall, I'll send you the link to that about PUE driving companies to overwhelmingly cool data centers with water, because that doesn't count against the PUE score. But in fact, if you're in a place where there's tons and tons of electricity, green electricity, you could be cooling your data centers by using aircon and that would be not a hit on, on water, but it would make your score, your incredibly important PUE score,

because we're focused entirely on a metric, which is not a great metric, is forcing up water use. So, yeah, it takes us full back to the full circle of metrics are useful, but do not overly lean on them, or it can be worse than if you had never had them to start with.

Chris Adams: Okay. All right. Thank you for that, Anne. This actually makes me think of a recent interview between Jigar Shah, who is the head of the US loan program office, and David Roberts, who runs the podcast Volts. It's a really, really interesting one. It's particularly talking about nuclear in the specific, but I'm going to share a link to it in the show notes because it gives, it basically has the person who's the head of the loan program office saying "we have data centers speaking to us. They're expecting this kind of load. And the figures there are extremely high." And they're actually not that far away from the numbers I see here, which was surprising for me. Because the IEA, A had much lower figures before. But there's also another document that we can link to, which has numbers which might not be exactly the same as these figures here, basically.

We'll add a few more, because this discussion about how much power is actually being consumed and how much is going to this is very much a relevant one, especially when you think about, okay, if we've got this much energy, are we going to use it to meet demands of AI or are we going to use it to decarbonize the rest of the world?

Because there is a finite amount of green energy that you can actually deploy in a given amount of time and space. And this is something that we tend not to talk about right now. And maybe this is something that we need to touch on a little bit later. And this might be a nice segue to the next story, which we'll just kind of wrap up with.

One of our last ones. This is a piece of datacenter research from the European Commission, basically. Actually, we mentioned a gentleman called George Kamiya. George Kamiya was leading this research with another gentleman called Paulo Bertoldi. This is essentially energy consumption in data centers and broadband comms networks in the EU.

And the thing that's interesting here is this is country by country information for both data centers and for networks. And it's worth a read if you want to have some numbers to talk about this. And there's a really interesting chart that we'll also add to the show notes. Anne, I'll hand over to you first because you have some things you want to share about this and then Asim, I'll hand over to you if that's okay.

Anne Currie: It's a really fascinating report with a lot of interesting data in it that we haven't seen previously. So I thought that the main takeaway from the report for me was that generally speaking, most countries in the world, that the percentage of energy use by data centers and by telecoms is fairly consistent.

It's kind of like data centers are around one and a half, two percent of electricity use within the country. The only time where that really isn't true is in places where there are lots of data. They are the data center for the world. There are a dis disproportionate number of data centers in that country like Ireland, for example, Denmark, the Netherlands, and it, it'll be interesting to see whether or not those are the places where all the data centers are in future, because I would like to see the data centers in places where there is an awful lot of green Power that is not used, Chris, as you were just saying, in any particular location, you don't want all the green power being sucked up by AI, you want it to go into other things as well, but in places where we could build data centers and there isn't a great deal of other use for the green power, and it isn't competing on a local grid, I hate the whole thing of use your data center heat to heat municipal pools, because that's immediately saying your data center is somewhere where it is competing with folk, with people, for their energy requirements. Data centers should be in the middle of nowhere, which is terrible for people who work in data centers, so I'm sorry. But, that's what the robots should be doing, running data centers.

Chris Adams: Okay. All right. Asim, I'll hand over to you before we wrap up and then come to the last story. Go for it, mate.

Asim Hussain: Well, I don't, as we were speaking, I just realized that I, what, why? What is it about? I know, I've known for a long time that Ireland has, I've known this statistic for a long time, but I don't know why. What is it about Ireland? Is it a tax haven type?

Anne Currie: It's a tax dodge, I think.

Chris Adams: So you're talking about context. So for context, you cannot see the chart, but we're looking at a chart with country by country figures, which shows the energy used in terawatt hours by data centers, the energy used by the telecom sector, and then the share of national energy use. And for most countries, it's between 3 and 5 percent or maybe 1. 5 percent and 4 percent in most cases, except in Ireland where it's hovering around 19 percent or 20%. So you got close to 20 percent of all the power used in Ireland to run data centers, which are predominantly a set of hyperscale data centers. And if you read through the report, you'll see that figure was around 10 percent in 2019.

So in the last few years, you've seen a doubling in usage here. And the other kind of outliers you might compare to are Denmark, which is around 5 percent of total energy usage and the Netherlands, which is a little bit over 5%, but in particular it is very exceptional in that it's multiples larger than everyone else right now.

That's from what we can see so far, one of the largest sources of Load Growth inside the sector, inside there. And there's also, what we'll do is share a link to a actual consultation from the CIO, the Irish Grid Operators, where there's some really eye opening responses from both academics and from data center operators, basically saying "we should be doing this, and we shouldn't be doing this," and some of the charts are pretty eye opening. Yeah, that's, you're right, as Anne mentioned, Anne, you spoke about was Ireland has been considered one of the places with very low tax, and as a result, large corporates love it, basically.

Asim Hussain: Is that what it is? If it's a low tax? I mean, cause then. The solution is to reduce the tax in areas where it has greener energy or something like that? I think there's

Chris Adams: Do you think that's the case?

Asim Hussain: Well I don't know and if it is, I mean we have to look at this whole situation

Chris Adams: They're just the prescription of reducing tax in the one place that has very, very low tax compared to maybe increasing the tax there so that you have a bunch of companies that need to choose based on carbon. I think that there's different prescriptions you might use to solve this particular problem if you see that as one of the problems that we have here.

Asim Hussain: Well no, I think it's just acknowledging the fact that if that's the situation and it was being driven by a low tax. You're right, maybe tax is the solution if tax is the problem.

Chris Adams: If you look at Luxembourg, Luxembourg is the other place with extremely high percentage of data center usage, which is actively courting data centers, which doesn't have particularly clean energy. And that's also one of the high ones. And it's also known for not being the place with the highest tax in the world.

So there's this idea that essentially low tax increases the amount of data centers you're going to have in a particular place, especially if they're large hyperscalers. But that's not necessarily means that you're going to have green energy there all the time. All right, Anne, over to you.

Anne Currie: I was just going to say, in the long run, hopefully, the solution to high prices is high prices. The solution will be that green is much cheaper. So, hopefully, the actual cost of electricity going down will overtake the tax breaks and things that are currently distorting the market. We really want data centers to be in places where the electricity is cheap. That is the, green will be cheap. So...

Chris Adams: Okay, thanks, Anne. All right, then. Okay, last story, because we're just running a little bit over on time. The last thing we're going to link to was actually this carbon hack thing. Asim, given this is like taking over your life, I figured it might make sense to give a bit of space for you to talk about what on earth you're doing and why people might go to it.

So, why do people care about carbon hack and why are you working on this thing? Because that might, yeah, justify your existence, Asim. That's maybe the way to think about it.

Asim Hussain: Just to save me. So this year we're running CarbonHack. It's running in about three weeks actually now. And the thing that I'm really excited about it is that the main topic of running is a framework that we've been building here called Impact Framework. Which is many things, but it's a tool to help you measure and really be very transparent regarding your software emissions.

A lot of the stuff we've spoken about today is this question of, is something a good proxy, is it a good measure? What is it? Oh, and what impact framework is, it allows you to, through a set of plugins, build a bespoke calculator, which can take observations that you can make about your software system and turn them into impacts like water, energy, carbon, things like that. But the most important thing about it, and it's something I don't really talk about enough, but it is that everything is stored in this thing called a manifest file. Everything. So the future I want to see is a future where somebody's not telling me what the carbon emissions are, because what is carbon? It's somebody giving me their manifest file, and it has all the coefficients, all the models, all the inputs, every assumption they've made in that calculation is that manifest file. And if I don't like it I'll change it. I'll adjust it. I don't like your model? I'll change your model. I don't like your coefficient?

I'll change your coefficient. And I can rerun it and I can judge what your emissions are. That's the real power of it and that's what we're doing with CarbonHack. We've got a bunch of prizes. One of the things we really need for Impact Framework to grow is a lot of plugins. Everything I just described is aspirational.

We need plugins to help compute web, to compute AI, to compute all these other, all these other things, to compute water. And that's a large part of the hackathon this year, is to encourage people to build plugins for Impact Framework. So I encourage you to go to hack.greensoftware.foundation and you can find out more information on it.

And I'm also giving, if you go to that website shortly, I'm also giving a lot of training and workshops on Impact Framework over the next couple of weeks. So if you want to learn more about it, just learn how it works, there will be lots of training sessions coming your way shortly.

Chris Adams: Okay. All right. Thanks for that. So, hack.greensoftware.Foundation is what people look at if they want to take part of this distributed, online, weeks long hackathon that doesn't involve you having to be awake for three weeks. You can do it in your own time, right?

Asim Hussain: Yeah. Yeah.

Chris Adams: Okay, cool. Alright then. I think that'll take us up to the end that we have, actually.

So, Asim, Anne, it's been lovely chatting to you again. I missed you, actually, so thank you for coming on for this. Like I mentioned before, all the show notes and all the links will be on software.greensoftware.Foundation. So if you go there, that's what you can find. And there'll also be a link to the transcript of this podcast, plus the links in markdown format.

So if there's a thing you see that's incorrect, or if there's a thing that you think we missed out, we do accept pull requests and you'd be contributing to the greater knowledge or the greater good for people to explore green software themselves. Thanks again, and yeah, let's do this again sometime soon.

Asim Hussain: Yeah. Thanks, Chris. Great to see you again, Anne.

Chris Adams: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again and see you in the next episode.

View Details

Chris Adams is joined by special guest Kate Goldenring, Senior Software Engineer at Fermyon. Together, they ask the real questions “is serverless computing the greener choice?” and “if so, under what circumstances is this true?” Tune in for an illuminating conversation on the current state, news, and future of green computing, digging into the topics of cloud computing, soft allocation, WebAssembly, and more.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Kate Goldenring: LinkedIn | X

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* https://github.com/Green-Software-Foundation/podcast-transcripts/pull/1 [09:00] * PLATYPUS [09:30] * Sysdig 2023 Cloud-Native Security and Usage Report [13:40] * XFaaS: Hyperscale and Low Cost Serverless Functions at Meta | Proceedings of the 29th Symposium on Operating Systems Principles [14:03]

Events:* Carbon Hack 24: Where measurement meets innovation, and impact knows no bounds

Resources:* tag-runtime/wg/iot-edge.md at main [04:24] * Bytecode Alliance [05:47] * Basic Alpine Climbing Course - Seattle - 2024 — The Mountaineers [08:09] * A greener, cost effective cloud with serverless WebAssembly [13:00] * Surprising Scalability of Multitenancy - Marc's Blog [22:34] * Introducing Spin | Fermyon [31:01] * Software Carbon Intensity (SCI) Specification Project | GSF [39:17] * Take it to the limit: peak prediction-driven resource overcommitment in datacenters [41:06] * GitHub - fermyon/spin: Spin is the open source developer tool for building and running serverless applications powered by WebAssembly. [42:36] * Fermyon Discord server [43:09] * https://hotcarbon.org/assets/2022/pdf/hotcarbon22-sharma.pdf [43:30] * Fermyon Technologies [45:56]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Kate Goldenring: It is very clear that you reduce operational emissions by not running your application when you're not using it, so by leaving the gym. But actually, by oversubscribing, we're also reducing embodied emissions by having higher density and not needing as many servers. And so, I think this whole concept can help us decrease our software carbon intensity.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello, and welcome to another episode of Environment Variables, where we bring you the latest news, And updates from the world of sustainable software development. I'm your host, Chris Adams. When we talk about reducing the environmental footprint of software, it's common to talk about making an application more efficient by using better algorithms or relying on languages that make more efficient use of resources than others.

However, the fact remains. That for most software in the world, most of the energy use comes from having millions of computers waiting for something to happen, rather than actively doing work themselves. So if you have software designed to let someone book a ticket, or buy a book, any time of day the transaction might only take a few minutes to complete, but the software still needs to be running 24/7 in a powered up state, constantly consuming resources to make that possible.

Now, common wisdom was that you need to design for peak amount of traffic you'd ever expect to see, and then just accept that paying to run all those servers all the time, waiting for something to respond was just the way it had to work. Serverless computing broke this assumption. Instead of paying per hour to have your software constantly running and available, waiting for responses, you'd design your software a specific way and pay to use it on a per request basis instead. When your software wasn't actively serving requests, it would scale all the way down to zero and you wouldn't be billed for these dormant periods. If an incoming request did come in, your software would wake up, serve them again, before going back to sleep.

And in aggregate, this would result in fewer machines needing to be run. Because computing resources were being allocated in a more efficiently across a large number of programs, running them only when they needed to do work. So that was the idea, at least. While we touch on the details later in this episode, there are definitely trade offs you need to accept when designing serverless programs.

And while the term serverless implies a lack of servers, there are still racks of kit required to run this infrastructure. So, is serverless computing the greener choice? If so, under what circumstances this is true, and what's the difference between a virtual machine, container, or even a WebAssembly runtime?

Joining me today is Kate Goldenring, whose work I came across when she answered a really specific, really detailed question I'd asked about serverless computing. In the Green Software Foundation discussion forums, when I was trying to make sense of it all, she responded with a really helpful answer, citing a number of peer reviewed papers, as well as linking to a really informative talk that she delivered at the Cloud Native Computing Foundation Sustainability Week a few days earlier.

So when I asked her if she'd be up for coming on the show to talk about some of the details of serverless computing, she agreed and I'm really happy to welcome her on to Environment Variables. Kate, welcome.

Kate Goldenring: Hi Chris, thank you for having me. So I am very happy that that forum existed and brought us together. I am a senior software engineer at Fermyon, and we're very excited about serverless WebAssembly. And so that's something that we'll be talking about throughout this and in general, to touch on my career, I started at Microsoft, where I was actually focused on edge computing solutions.

And I developed a project called Akri, which is a Cloud Native Computing Foundation, CNCF, sandbox project for managing IoT devices around Kubernetes clusters. So from the start, I was very into open source software and got to really kick off my career there, which I'm very grateful for. And I'm still in the IoT edge space.

I serve as co chair of the CNCF iOT edge working group and have authored a couple of white papers on edge computing best practices within that working group.

Chris Adams: Oh, Kate, can I just stop you just for one second? Did you say, so you were with Microsoft back then and you mentioned Akri. Now I think that was like a few years back. Was there a project called Deus that was floating around in Microsoft land there? Like they want a little bit like say, wow, that takes us 10, back 10 years or so actually.

Okay. So Deus was one of these platform as a service things, a bit like Cloud Foundry and stuff like that. Right?

Kate Goldenring: Yeah, and Deus was acquired by Microsoft and Deus Labs was how it was renamed. And it became this hub within Microsoft for its open source cloud native projects. And so Akri became a project under Deus, and then it was donated to the CNCF after that.

Chris Adams: Okay, gotcha. Thanks.

Kate Goldenring: Yeah, so a bit of an evolution in how open source worked within Microsoft as well, and I actually, while working on Akri and in that open source world within Deus, I learned about WebAssembly, and I got very excited, in part because I saw the potential of it for green computing and reducing the carbon intensity of software, and so I actually decided to leave Microsoft to join Fermyon, which is a startup in the WebAssembly space.

And I'm still in the open source world contributing to our open source tooling there. And we actually work with the Bytecode Alliance, which is an alliance, as it sounds, of companies such as Microsoft, Amazon, Adobe, Fermyon were involved. And it's all about building out WebAssembly specifications so it can do more in more places.

So that's kind of also where I am now within the weeds of the WebAssembly world.

Chris Adams: Okay, cool. All right. I'm, I'm glad you mentioned WebAssembly because we'll touch on that a little bit later about what it actually is and why some of that is relevant, but I should probably introduce myself too, for people who are new to this podcast. So my name is Chris Adams. I am the executive director of the Green Web Foundation, which is a Dutch nonprofit focused on reaching a fossil-free internet by 2030.

I'm also one of the policy chairs of the Green Software Foundation policy working groups. And I'm also one of the maintainers of a library called co2.js, which as you imagine is a library to help you work out the carbon footprint of various digital services. Alright. So, Kate, you're sitting comfortably, right?

Kate Goldenring: Of course.

Chris Adams: Okay, cool.

Before we dive into the finer points of serverless computing, I understand it's quite early. It's earlier for you than it is for me. So it's about 4 p. m. in Berlin, 7 a. m. or 8, 7 a. m. for you, right? In Seattle, yeah?

Okay. And as I understand it, when you're not in front of a computer, there are some upsides to living in Seattle.

So maybe you could tell me a little bit about that before we dive into the nerdery, because when you shared some stories here, it pleased me actually, and I quite enjoyed some of the kind of names of some of the groups you're, you're part of.

Okay,

Kate Goldenring: Yeah, I'm happy to be running advertisement for the city of Seattle. I absolutely love it out here. I am an outdoor enthusiast, and I was even before I moved here. But moving here kind of took that to new heights, if we're going to be a little bit punny about it. But when I, right, soon after moving here, I actually learned that I had some.

Some history with one of the mountains here, Tahoma is also known as Rainier. And I found out that my mom actually attempted to summit it when she was pregnant with me. And we did not make it to the top. I think you could probably blame me for that. But after hearing that, I was curious. And so I tried as well with a guided group and also did not make it to the top, but got to weirdly the same spot, which kind of continues this weird chain of events. But what did happen was that I really fell in love with the sport. And so I joined my local climbing club, which is called the Mountaineers. And now a few years later, I spend a fair bit of my week, three to six hours, probably helping instruct that course that I kind of kicked off this love with and teaching a cohort of students, leading trips and climbs.

So I definitely, when I'm not in front of my computer, am thinking about planning trips, going on trips, and definitely grateful to be in Seattle.

Chris Adams: Okay, cool. Thank you for that, Kate. All right. It seems we're going to continue this run of peak related puns with the next section as well, actually. So before we dive into this show and some of the things we'll be talking about, here's a reminder that everything we talk about, every project that we speak about will link in our show notes.

And the show notes are also published in markdown form on a GitHub repo now. And this is my point to thank one of the, one of the people from who actually submitted a pull request to our last set of show notes, Ross Fairbanks of FlatPeak. He made the first PR to the transcript where he helped us name, basically last week, we were talking about some of the specifics about,

how do I say, about a certain kind of attack, security attack that is actually named after an animal. We couldn't remember it, but it's, you need to know about this if you're going to do decent energy and carbon reporting. So we were asking, "can someone please name this?" And Ross was dutifully the person to come in and name, "yes, this is called the platypus attack," and not just that, it's one of these cool IT security vulnerabilities with a really, really nice looking website.

So we've now updated that. I will link to both the PR and this attack. So you now know when someone is telling you why they can't share information, you can say, "well, no, yes, we've heard of the Platypus attack and this is the mitigation for it." So yeah, that's like the depths of our nerdery that we go into.

All right then. So we've covered that. And if there are any typos or things that we mentioned that you don't see linked, you will be able to make a pull request and we will basically thank you in just the same way we thanked Ross. So you can get your 35 seconds of fame as well as you do this. Okay. And hopefully that should be a good incentive for listeners to basically help create a useful artifact for other people moving forward.

All right then. Okay. Kate, I tried to give a good intro into serverless computing. And when I saw the talk that you presented, you had a really interesting framing that I hadn't come across where you spoke about the value of a service versus the costs of making it available to people. And I figured this might be a nice way to kind of open up, because this is actually, I find it really, really enabling for me to think about kind of having websites available and how you even do that, or even why you might even have a website running in the first place. So maybe if I just like gave you the floor, it would help us set things up for some of the later conversation, actually.

Kate Goldenring: Sure. And I want to call out that I similarly had an epiphany when I discovered this concept and I actually found it within Mark Brooker's blog. He's a distinguished engineer at AWS and one of the original authors of AWS Lambda. And in this blog, he talks about how the cost of a system does not always equal the value you get out of the system. And in a cloud context, the cost of running an application on a piece of hardware is the amount of compute resources you need available for it. And so as you mentioned at the start, oftentimes we provision for the peak. So the traffic to an application is rarely constant. And when you're choosing how many resources to provision, you have to make sure there's enough of those resources of CPU and memory to handle a burst of requests. And so this means that we pay for the short term peak traffic that an application may get. However, when we think about the value we get out of a system, that's the long term average traffic. And you can think about this and even see this in payment models for serverless platforms, where you may be paying for average requests per month. And so the problem with this, when you're paying for the peak but you're receiving the average is that we have this gap and that can cause low resource utilization. And so we ideally want to close this gap and a way to do that is with multitenancy. And so multitenancy is running multiple independent applications in a shared environment. And if you increase the multitenancy of a system, so you throw a bunch of uncorrelated applications on the same hardware, where each has its own traffic ebbs and flows, the idea is that their peaks balance each other and traffic flattens. And this line gets as close to average traffic as possible. And so now we've had our costs equal our value and it's, we're all happy. But this is in some ways very idealistic. We're assuming applications are uncorrelated. We're also assuming that you have some underlying technology wherein when you aren't running your application, it is scaled absolutely to zero. It's using no resources. So this is where I get a little excited. Cause I do think we are coming upon a world where that can happen. And that is with WebAssembly, which can have these sub millisecond cold starts. And the whole goal of all of this from the context of green software is that we want higher hardware utilization, as you mentioned earlier.

Chris Adams: Okay. So what it sounds like you're saying is that this, like this idea of like multitenancy or maybe a little bit like a gym, multiple people using the same thing. This is actually a kind of a common theme. And this basically increases the average amount of use of the kit. So it's not sitting there just waiting to do stuff, essentially.

Right?

All

Kate Goldenring: Yeah. And just to point out a stat to kind of nail that home. Sysdig did a report in 2023, the Cloud Native Security and Container Usage Report, and found that 69 percent of CPU is unused in containerized cloud deployments. So we're really only using 30 percent of the resources there. And ideally we would flip that number and we would be constantly using 70 percent of the resources. And one of the ways to do this is with higher multitenancy and different technologies, and there's a really interesting paper from Meta about XFaaS, which is a serverless solution they now have created for private clouds that came out in 2023, and they found this phenomena that we talked about, the peak to average, and they describe it as the peak to trough, so not the average, but the lowest amount of requests at any given point, and found that it can be 4.3 times. So these peaks are quite high is the point of that. And the way they respond to it is by determining which workloads are delay tolerant. And so then they'll move the delay tolerant workloads to execute as a different time. And time shifting is a common thing and common recommended practice in green software.

So I also want to mention that this isn't always the way we expect it to be. Not, you can't perfectly fill a piece of hardware with uncorrelated applications and you might have to find some other techniques to balance out your request frequency.

Chris Adams: Okay. There's a couple of things that you mentioned that I just want to drill down on first of all. So you first mentioned this idea that most of the time, most computers are doing nothing, right, or they're waiting, like even with something like containers, which are considered a relatively efficient way to have lots and lots of programs running, more than two thirds of the time, they're just like not actually in use.

And this is at the kind of higher levels, like say when we talk about, say hyperscale providers, you might see people talking about, "Oh, we're really good. We've achieved say 30 percent level of utilization. And that's like 10 times higher than what you might have when you're using like a series of virtual machines or even like physical machines."

So there's a, basically a bunch of waste that this is designed to kind of get rid of, and I think the paper you referred to with XFaaS, they were, they basically said, "well, yeah, 30 is good, but we can go higher than that. If by, by doing some of these tricks, we've hit like 50 or 60%, which again means that many fewer bits of hardware to run this."

Okay. But you also touched on something there. You said that this was a private cloud, so there's certain assumptions. What about, about the softwares? Because it's the same company, they can trust each other's workloads and they don't need to keep these things as safe from each other as they, as other ones might, or there might not be the same, there might be the same priority compared to like, say, if you're running a cloud provider with lots and lots of different customers who don't necessarily want to share each other's stuff.

Maybe you could talk a little bit about this idea of virtualization and actually serverless and this idea of like isolation and why it's important. Because I think for a lot of people, they don't really, this is not something that you need to think too much about as a customer so much. You just need to know it's there, but when you're designing a system, there's actually quite a few things that you need to take into account for this.

And there's been different approaches that have been developing over the last, say, 10 to 15 years, for example.

Kate Goldenring: Yeah, I think we talked about how great it is to throw a bunch of different people's applications all together on the same piece of hardware. But that is a very scary statement to a lot of people to have their application running next to someone else's application. So there's this concept of isolation.

The idea that I will be okay with you running my application next to someone else's in a public cloud so long as these criteria are met. And isolation really just means that you know that your application won't be prevented from using resources because you have an application that's hogging them. And you also know that there's not another application that's going to access your application's data.

And we can actually look at the cloud as having gone through waves of this concept of isolation and keeping things separate from each other. And with each wave being motivated by a more finite mechanism of isolation, and also leading to a new type of cloud application that's come out of that wave and you hinted that kind of the start, which is virtual machines and that the advent of virtual machines, the ability to virtualize hardware with hypervisor technology has made it so that we can have multiple independent applications running on the same piece of hardware. And it didn't change the way people necessarily built their applications. It was still monolithic applications, but we could do more with the same amount of hardware now, and for context of time to start up and scale up, virtual machines take a few minutes to start.

So, if you wanted to scale up the number of virtual machines, it was a slower process. Next wave, you can think of as the wave of containers, and with containers, now we're virtualizing a smaller set of technology. We're virtualizing the operating system, and now we can run dozens of tenants on the same physical hardware. And this has brought about the advent of microservices, so I can scale up individual parts of my application instead of just scaling up the whole entire application.

Chris Adams: So could I just check, so you, so we spoke about VMs, virtual machines, so it might take a few minutes to spin up and down and then containers will be a little bit faster. Maybe Sub second or around a second. And both of these, like, these are, these are still an improvement on a physical machine, which can be weeks to get a new box set up, for example.

But the advantage of a physical machine is like you have like literal physical isolation, it's totally separate from computing. So that's the idea. And there are very different approaches you can have to separate this out. And you were talking about containers and VMs, and I understand there's a few other, there's a few other steps on this kind of continuum from a total separate machine to your share of a physical machine inside it in a VM or a container or something like that. Right?

Kate Goldenring: Exactly. And so we've gotten smaller. And then you can think of as the next wave being one of serverless. So being able to have even more applications on the same physical hardware. And this was really pioneered by the advent of the micro VM. And if you're familiar with AWS Lambda, the underlying technology for that is the micro VM, and with micro VMs now we, it only takes 125 milliseconds to start up a micro VM, and so it creates this opportunity to be able to run something only when you need it, which is a great, great future to realize.

The only issue with that number is that we, we know that a hundred millisecond is kind of the boundary of where you start to notice latency, and when you add execution time and network on top of this, this 125 milliseconds becomes a bit larger. And so the result was they had to pre warm these instances, so they had to get them running before you even needed them, so they have to use resources, even when they're not being used.

And that, that eats into our cost and value equation we had earlier. And so Serverless has these great opportunities, but hadn't been realized quite yet. And so the next way that I'm particularly excited about is powering and realizing serverless with WebAssembly, and achieving even higher density, and having those instant cold starts, and we're still isolated, just like a micro VM.

But instead we use a WebAssembly runtime to isolate your application using linear memory and WebAssembly also has a capability-based security model so that you only have access to resources you've been explicitly granted access to in the runtime. And so you still, through all these waves can have varying, but pretty solid levels of confidence that your workload is isolated, but we're getting into different levels and ways of computing and building our applications

Chris Adams: Uh, Ah, okay, thanks. Alright, so you spoke about this, this thing called micro VMs, which I understand was it, it sounds like basically an virtual machine, but smaller. And as I understood that, that might be, it's smaller because rather than trying to create totally virtual machine where you have all the kind of things that a regular virtual machine might have.

Like you can plug a printer in or plug stuff like that. It's just a much, much smaller service area. And as I understand it, there's a service called fly. io. They use Firecracker as one of their main options. Okay. I think I understand where you're going with that. And that, so that's an improvement on VMs and possibly has offered some of the kind of isolation benefits that some people have basically criticized containers for not having.

But then with like WebAssembly, this smaller thing, there's a, there are basically different approaches taken to make sure that other people's code isn't going to touch your code and vice versa. That's what you're talking about with things like linear memory and this capabilities based thing where you almost, you have to grant access to something first, right?

Kate Goldenring: Exactly. There's different methods to achieving isolation. And I also want to point out that we've been talking about one type of isolation, which is per-tenant isolation. So the idea that one tenant is isolated from the other, but there's also an even finer grained type of isolation that we can get in this latest wave of cloud computing.

And that is per-request isolation. So the idea is that my one request to my application should be isolated from the other. And in an ideal serverless world, you'd be able to guarantee statelessness across requests so that if my first request triggered a bug, It should at most affect that request. And the way you do that is by creating a new instance or a new isolation for each request.

And that's been really hard to do in the past when it takes 125 milliseconds to start up your virtual environment. But with WebAssembly, because it can start in a millisecond, you can actually create a new instance of your application for every single request on request. So you have an even finer interpretation of this isolation world.

Chris Adams: Ah, okay. All right. That helps me. Okay. So you've gone from like 125 to one, which is much, much, much faster. So that's the general idea that you have there. And I should probably ask. When you're doing something like this, I, I kind of understand the idea that if you are able to ramp up and down really, really, really fast, then you you can probably fit more peaks inside it because someone else's peak will end, will end faster than making space for someone else's peak to come in, basically.

So that's the general idea. I'm not that familiar with WebAssembly myself, and maybe it might be worth just talking about what that part actually is, because I'm a developer. I might code in Python or possibly JavaScript sometimes. Do I need to learn something new? Maybe you could just touch on some of that before, and then we could see how some of that fits in, because this sounds cool and something starting up 125 times faster also sounds good, as well as being much, much more efficient. But I quite like coding in Python and I'm getting a bit old, so I'm not sure if I want to dive into learning yet another language, if I can help it, basically.

Kate Goldenring: I definitely don't want to take Python from you. So WebAssembly, as its name suggests, was actually made for the browser. So the browser, most applications were built in JavaScript, and people were tied to their language of choice, say Python. And so WebAssembly was created so that you can build web applications in languages other than JavaScript.

It is just a target for a language runtime and a universal bytecode. And so you can write your application in Python and compile it to WebAssembly, and then you could run it in the browser. That was the whole idea. And because it was run in the browser, it got all these different characteristics, such as being isolated because the browser has a bunch of. public code running next to each other. And so you need to isolate it. And that's also why it's fast. But the result is that we have this portable bytecode that can be compiled to from a lot of different languages. And if you're curious which languages can compile to WebAssembly, there are different categories of the level of support a language can have for WebAssembly.

It can compile to Wasm. And also just to clarify, I've been using this word Wasm. Maybe as well, Wasm is an acronym, so a shortening of WebAssembly. So I might

Chris Adams: Ah, thank you. I was going to ask about that. Cheers.

Kate Goldenring: So their WebAssembly, it can compile WebAssembly. It can also compile to a WASI compliant version of WebAssembly. And if you've heard WASI before, that stands for the WebAssembly systems interface.

So it's a set of interfaces that describe how a WebAssembly module can have access to host resources such as IO, networking, et cetera.

Chris Adams: Okay.

Kate Goldenring: So different languages have better support for that as well.

Chris Adams: All right. So can I come in just, so can I come in just one second there? Because you've got me quite excited now, the idea that, okay, I don't need to learn a new language and me basically spending 10 years or 15 years, in my case, trying to get kind of basically some more competent Python. I don't need to throw that away.

And other people can, in whatever languages they use, they can also use that. And I think you said something quite interesting about, like, I know that under the hood, when I'm coding in Python, really something's being compiled down to some kind of like assembly. As for example, but I know that when I was using my, I'm using a MacBook right now, which has a Mac chip, and previously I had like an Intel Mac.

And then I had all these problems because there's different bits of, there's different architecture that these have. And I know that when I'm pushing code into say cloud sometimes. I'll be told that, "Oh, this doesn't work because you're not using an Intel machine." How does this relate there? Because it sounded like there was one kind of binary to like rule them all.

But I'm, I'm not, is it really like that? That sounds kind of quite helpful. And I'm, I would appreciate that, but that sounds a bit too good to be true, basically.

Kate Goldenring: I think it is good and it is true,

Chris Adams: Oh, wow.

Kate Goldenring: So, the thing about a browser is that it has to be able to run on all these different operating systems. So the code that runs in it needs to be able to do the same. And so WebAssembly, that .wasm file that you've compiled your application to, can run on pretty much the majority of operating systems and platforms.

So, Windows, Linux.

Chris Adams: I see.

Kate Goldenring: Et cetera. also like 64 architectures, ARM architectures, et cetera. You can execute that same .wasm file. And we're going back to like the people listening to this, who are passionate about green technology. This means there's no more cross builds. So if you think about how much your GitHub runners or whatever CI you're using, how they have to build everything for all these different

Chris Adams: all those

matrixes, like all for a version of Python that go, okay. All right. So you get rid of, wow. Okay. Yeah. Okay. I didn't know that hadn't actually picked up on that. And when you say this WASI thing, so if you are used to Linux or even Unix, there's this thing, idea of like POSIX compliant, right? Where

they're all going to talk to like a foster in more or less the same way. Is that kind of comparable? Was that generally the idea for that as well?

Kate Goldenring: People will definitely compare WASI to POSIX and I think there is some comparison there for sure. WASI is definitely different in that it is a set of interfaces. So, it's basically defining a contract or an interface between a WebAssembly module and the host, or even another WebAssembly module. And this is where we get maybe into something that is called the component model, which we don't need to dig into, but it's providing a new way of building applications so that these different languages can actually talk to each other within an application.

So you can imagine a universal URL library that's maybe built in Python, but can be called from Rust. And that's by adding a wrapper of the component model on top of a WebAssembly module, and they're all talking through these interfaces. And yeah, WASI describes a set of interfaces and actually. 0. 2 of WASI was just released, and that was a huge milestone.

It happened only a month ago, and that has promoted the standardization and the stabilization of these interfaces. So we now have a stable release that you can target with all of these interfaces and you can find them within the WASI repo, what exactly those interfaces are

and what capabilities it provides.

Chris Adams: Okay. So if I understand it, that's basically, so this, why is he thinking? Yes, it's a little bit like POSIX, but it's, it's, it's a bit more involved in that. Like it's, the idea would be that you could have that connect to maybe another system with a kind of predefined way. So rather than me having to kind of send a bunch of json in a serialized fashion, then you have to un serialize it, there's like predefined ways of these talking to each other.

Okay. I think I understand where you're going with that. And that does sound quite attractive. And that sounds useful to someone who's a developer or making some stuff here. Now, I understand that you are working on some of this yourself, and I understand that there is a, that you're, you're using one platform that, so I think when you showed me this talk, when you responded in this forum, you pointed to a talk with a platform called Fermyon Cloud, which does cover a sub, a couple of these languages that lets you run things in this new framework, Wasm thing, for example, could you maybe talk a little bit about,

about that part of what the experience looks like, cause I just, it has me quite curious and I assure you, we'll get back to other things, but that was, did sound kind of cool. And I just want to go down that rabbit hole for a second, if I may, actually.

Kate Goldenring: Yeah, and I think I've been painting this beautiful picture of WebAssembly, but it is still a fairly nascent technology. And so Fermyon is the company I work for, and we were really excited about simplifying the developer experience. So having someone come in and say, "Hey, I want to use this WebAssembly technology.

How can I use it?" And so if you're familiar with Docker, which kind of created that experience for containers. They created this Docker build, Docker run experience. We wanted to do that for WebAssembly with also the step of helping you even create that application. And so the open source tool for this that we've created is called spin and it is becoming the way to build serverless WebAssembly applications.

And so just with a simple spin new, you'll have templates that pop out for all these different languages. So we have 10 different languages that you can scaffold an application for. And there's SDKs for Rust, Go, Python, JavaScript.

Chris Adams: Ah, I see.

Kate Goldenring: Yeah, so now you've created this application, you've scaffold it, and then you can do a spin build and a spin up and run it locally. And remember, this is very universal. So whether Windows or Linux, et cetera, you can run it and then you can do a spin cloud deploy and deploy it to Fermyon cloud where we can host your applications and it's free and you can even share it with someone or if you use Kubernetes you can deploy it there.

So we're really trying to simplify the developer experience of using WebAssembly and also running it in your place of choice.

Chris Adams: Okay. You said a couple of things that caught my interest there. So first of all, yes, there is basically a tool, a little like how I might use Fly, Kotal, like to make an app or Heroku or basically some CLI to create a kind of harness for me to be developing in. And then I push to cloud, and presumably like Fermyon cloud, that's maybe a paid service or something like that.

But you said I can run it on Kubernetes, which isn't necessarily run by yourselves. And you, I think in the demo, you showed me, I think the demo I saw was running on Nomad, which is a service that we use as well, where I work basically. So. You're not tied to any particular platform and once something is in this kind of Wasm format, you could have it in a number of different places that do serverless.

You're not tied to like one ginormous provider or maybe two or three massive hyperscalers. You've got a bit of freedom in who you choose to work with in that scenario. Yeah.

Kate Goldenring: Yeah, and I think that is what is really exciting also about this wave of serverless is the cross platform agnosticity of your, your bytecode that you've created. So this same dot Wasm file ideally isn't locked into one cloud, so you can run it on Fermyon cloud, or you can run it on AKS's WASI node pools, or you can run it on other serverless platforms or locally and that same

application shouldn't be locked into anywhere because we're using the standard interfaces to run it. And so I think that's very exciting because what made Kubernetes so powerful was that people could switch from one cloud provider to the other. They didn't feel locked into their decision, and that's what was able to spread and kind of evangelize that kind of cloud computing.

And so I think the lack of vendor lock in is very powerful here.

Chris Adams: Okay. All right. So that's quite helpful. And this actually opens the door for some of the kind of, well, something we spoke about last week with on the last episode, there were some people talking about a company called Civo, I think Civo, who we talk about pools of resources, and we were joking about pools of resources in literal swimming pools, because they have a whole thing where they basically run computers

which generated lots and lots of waste heat, somewhere where the actual heat is useful. Because, the swimming pools would typically need to be, basically get the heat from somewhere. And they often do it by burning lots and lots of gas. So, the idea was by having something like a kind of, something which was kind of compliant in this way.

I think they run like a bunch of Kubernetes boxes somewhere, for example, and they don't literally put it in the bottom of this room for like some kind of piratical servers treasure chest. It's actually like, it's somewhere near, but this is one way of actually systemically thinking about some of the outputs from computing and basically doing it in a more kind of environmentally sustainable fashion.

It sounds like basically tools like this, or even serverless like that, you can run in these places. And that's actually one of the options.

Kate Goldenring: Yeah, I think, I think you're talking about Deep Green and that,

that work with, and we actually use Deep Green with spin applications. You have access to all these external resources cause they themselves are stateless, but you can still attach them to key value stores, SQL stores. And another resource we've provided is LLM inferencing on some GPUs that is powered by Deep Green.

And like you say, they're submerged in pools. And I believe. in vats of oil. And that captures first in the oil, then in the pool, like in a confined space. And that captures that heat externality and powers a pool. So I get very excited about the idea of capturing that externality of that compute. And yeah.

Chris Adams: Okay, cool. That sounds, all right. I'm glad you mentioned some of that because this is something we're trying to figure out because when, when we, if you listen to the episode last week, it sounds like we think that the servers are literally at the bottom of the pool. And obviously that that's not how it really works, but basically there is some way of using some of the heat from that.

Okay. All right. So I think I've got a good understanding of this, of where WebAssembly might fit into this. And I can see why when you make something, which is easy to run in lots and lots of places, then you can reduce the amount of hardware needed, but you can also reduce some of the impact that it might have by putting it in a, in a place that's more, I guess, sympathetically designed to like it's surrounding, for example, rather than venting heat into the sky, you're putting it, you're making use, you know, a sensible use of that heat.

Okay. Can I just talk about something else as well? Because. We've spoken about efficiency so far, mainly in terms of matching different peaks, going up and down and everything like that and averaging this out. So that's like one option. But I think that one thing I saw you speak about, which was a new concept to me, that I just want to like check if I understand it correctly.

You spoke about this idea of over subscription or soft allocation. So you've got servers and scaling them up and down. That's one way that you might make better use of the resources. But the other one, and I'm going to try and use a gym analogy, because I think that was what I thought of when you spoke about this.

You said like, if you go to a gym there's like more memberships that get sold than the amount of kit that's inside it. So if everyone all tried to like use the same machine at the same time, it would work and there'd be massive fights. But because people aren't using them all at the same time, you, people kind of, you can almost oversubscribe and oversell some of this.

And in the context of computing, you see something a little bit like this. So you might have like a physical server with, I don't know, let's call it say 32 gigabytes of RAM and 16 cores. Let's pretend it like a few years ago, right? And rather than only allocating 32 gigabytes worth of, of servers or programs and 16 cores, you do more than that.

You'd over allocate that. This idea of over subscription is a, is a common way to make better use of the existing hardware resources. Maybe you could talk a little bit about that because. I don't think this is something that people are that aware of. And in many cases, if you think about how you might allocate the environmental impact to a server to do some calculations, you might not be aware of how many other machines are really running on that computer.

It's not a one to one mapping in all these cases. I think that's my understanding. Maybe you could shed some light on that because this is something that I think a lot of people don't have too much exposure to.

Kate Goldenring: Yeah, I, I really like that gym analogy. And I think that idea is that say I haven't... that 32 gigabyte and 16 core machine and I deploy a thousand applications to it. If all 1, 000 got a request at the same time, some would be slowed, some would not succeed because there's not enough resources on that machine.

But I'm making a statistical bet here and it's informed. Usually you do some sort of understanding of traffic flows. That no, they're not all going to receive requests at the same time. In fact, I'm expecting only 30 percent to be running at once. I don't know. That's a random number. But because of that, you're able to over, you're over oversubscribing that machine. And what the result of this is, is that I'm using one machine instead of two or three, which is very exciting. And the reason, the only way you can do this is if you know that when it's not being used, it's not at the gym. So the key to this is that you leave the gym when you're not at the gym. And so you need a technology that does that.

Something that actually can scale to zero. And in the past, we've been oversubscribing already with technologies that at least scale down. And even microservices, when they're not in use, are scaled down. They're just kind of idly sitting there using less resources. And if we put this in a formulaic terms there, you were saying measuring is something that we like to do, and in measuring our software carbon intensity, the Green Software Foundation has that Software Carbon Intensity formula,

and that is a sum of operational emissions and embodied emissions, and it is very clear that you reduce operational emissions by not running your application. When you're not using it, so by leaving the gym,

but actually by oversubscribing, we're also reducing embodied emissions by having higher density and not needing as many servers. And so I think this whole concept can help us decrease our software carbon intensity.

Chris Adams: I see. Okay. And that degree to how much you're oversubscribing is like, that's flexible. For example, you might choose to massively oversubscribe and just accept that the performance might be a little bit ropey or in some cases, or you might be a bit more conservative in which case you're probably going to be using a bit more hardware, but you're going to have more of a guarantee that these things will work at their speed,

at the desired speed. And that was probably the approach that we've taken over the last 10 years, but there are new approaches available, like you're describing with Wasm and stuff like that. All right.

Kate Goldenring: Yeah, exactly. And I think when I talk about it being something that is hopefully it informs decision on how much to oversubscribe. We personally did load testing. So I had a fairly small machine, like eight cores, 32 gigabytes, and just a hundred gigabytes of disk and just threw as many applications as we could on there. Figured out what that density limit was and then hit it with a bunch of requests and a loader and a prober to try and figure out what are we comfortable with and setting our own limit there. And so I think everyone has to do that to kind of figure out what that, that important level of density is for them.

Chris Adams: Okay, cool. Thank you for explaining some of that. For those who are listening, we've linked to a couple of papers specifically about this. There's one by a gentleman called Noman Bashir, who has written a bit about how this over subscription thing works. And we'll also link to this paper. There's lots of reasons you might be ambivalent about Facebook, but the paper, this XFaaS paper is actually quite interesting.

And the thing that, one of the things that's interesting in the context of CarbonAware software is that, well, they, this idea that you might over subscribe and rather than that, you might also kind of offload to entirely separate data centers as another strategy to kind of keep serving things when maybe other parts of the kind of fleet of machines that are able to kind of pick some of that up, especially if they are maybe low carbon intensity because they're running a particularly green part of the grid, for example.

Okay. All right then. So we've covered quite a lot of ground and quite a lot of, you know, quite detailed concepts here. And we're definitely going to link to a bunch of papers for this. I wanted to just actually ask you about, about this, cause you mentioned a little bit about Fermyon and you mentioned a little bit about WASI and some of these tools.

If people are curious about some of this, where would you suggest people look? Because until I actually had this call with you, I knew there was a thing called Wasm. I knew like, it's this thing that I've seen in Pyodide as a way of like running Python in the browser. And I kind of understand that, but I didn't know where to start.

And it sounds like you don't need to be writing everything in Rust, so you can do things that you could write in, like, can you write in JavaScript, for example, to have something run that runs on a platform like this, for example?

Kate Goldenring: Exactly. You can use JavaScript. And if you want to try this out with Spin, Spin is on GitHub, but also Fermyon.com will lead it to you or developer.fermyon.Com as well. And. JavaScript works there, and we've simplified that experience by we have actually plugins to help you compile it to WebAssembly, and so you just install the plugin for that language, and then the spin build works correctly for you, and you can then immediately run it.

And so it really is hopefully making that experience easier. Simpler and, and getting you going and it is an open source community. So if you are an open source developer and want to contribute, we have a discord that you can join to join the discussion, or if you have an issue, put up the issue or even maybe grab one too.

So we're really trying to grow the ecosystem. And I think we have around 75 contributors currently, but we're always looking for more hands.

Chris Adams: Okay, cool. All right. We're just going to wrap this up. And I know there will be at least one person asking, how do I do some of this work and make sure it runs in a swimming pool? Not in a swimming pool, but in a kind of very, very green fashion. If you would be able to share a link for that for the show notes, I'd be very, very grateful because that sounds kind of cool.

And the idea of putting computers in lots of new places where the heat is useful rather than a waste sounds kind of exciting to me.

Kate Goldenring: Happy to do that.

Chris Adams: Okay, cool. All right then. So we spoke a little bit about... okay, this is like a kind of serverless that's somewhat flexible and quite resource efficient. And one thing that I think you demonstrated, which caught my eye was you were spinning up how many, it was like a thousand applications on your laptop to demonstrate that, yeah, you can run serverless in lots of places.

Can I just actually ask you a little bit, how about that came about because it was a pretty cool demo and it was lots of fun and I haven't seen nerds clap over for a demo for a while, but it was really, really nice actually.

Kate Goldenring: Yeah, so I hinted a little bit about the motivation for that, and that was to figure out how much we could handle in our cloud. So I was tasked with load testing our cloud and basically coming up with a number of, this is the size of our instances we use, and, and how many applications can we put on each instance.

And so, as you pointed out, I was using Nomad there, and we basically had a multi tenant version of Spin that had a listener for every single application that was deployed. And then just deployed as many applications as we could on my laptop, my poor laptop, until it couldn't handle it anymore and just cleaned it with a bunch of requests. And that was all in the vein of trying to figure out how dense we could go.

Chris Adams: That was really useful for me to know because I, until I'd seen that, I generally assumed that serverless almost always means either some massive, chunky Kubernetes cluster, or it's going to be some proprietary tool that, okay, I understand why they're, they're, they're necessary, but that makes you feel a little bit uncomfortable about, okay, this is my future is only one provider, for example, that provided a bit of freedom on that.

Okay. Brandy, if people wanted to follow your work, for example, where would you direct people's attention to? Cause we're just coming up to time and this has been lots and lots of fun and I've really enjoyed seeing some of your talks and some of the things you've been writing about. And I suspect there may be other, other ones as well, because yeah, this has been really helpful for me.

Kate Goldenring: Yeah. I tend to try to promote the interesting things I find or I'm putting out there on my LinkedIn predominantly and sometimes on X as well. And both of those are just my full name, Kate Goldenring, as the handle. But if you want to talk more specifically and personally about a question, I'm on the CNCF Slack, the Kubernetes Slack, Bytecode Alliance's Zulip, and then if you're just interested in following blogs about WebAssembly and Serverless, Fermyon, we have a pretty active blog on our, our website, so just.

permian. com, you can find it. And so, and that's where we can find more out more about those swimming pools that we have some GPUs running in.

Chris Adams: Okay. Kate, well, this was lots and lots of fun. I really enjoyed it. And I, if nothing else, I enjoyed actually reading all the papers and learning so much about this. So, Kate, it should be coming up to eight o'clock for you. So I should probably say, have a lovely day and thank you very much for that. Kate, I really enjoyed this and I learned a bunch of new things about serverless, scaling up, scaling down, gyms, swimming pools, and Wasm. Thanks, Kate.

Kate Goldenring: Thank you so much, Chris.

Chris Adams: Hey, everyone. Thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode!

View Details

We're gearing up for the return of Carbon Hack 24 happening from March 18 to April 8, 2024. This year we're focusing on the Impact Framework, aiming to innovate how we measure the environmental impact of software. It's a chance for engineers, designers, and creators to dive into challenges, ranging from plugin development to non-technical content creation. We're inviting students too, with special categories just for them. Join us to push the boundaries of sustainable software. For details on how to register or to become a sponsor, check out the link below:

Register at https://grnsft.org/hack/podcast 👈

Find out more about Impact Framework:* Environment Variables Episode 58: BETA Impact Framework

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
Asim Hussain: Hey everyone, Asim here. Carbon Hack is back this year. The hackathon will take place from Monday, March the 18th to Monday, April the 8th, 2024. Carbon Hack 24 is all about redefining the way we measure software to reduce its environmental impact. footprint. At the heart of this hackathon is Impact Framework, an open source tool that lets you compute and report the environmental impacts of software applications accurately.

It takes observations you can easily gather about running systems such as CPU utilization, page views, or number of installs, or anything else, and converts them into environmental impacts like carbon, water, energy, air quality, in an auditable, replicable, verifiable, and transparent way. With Impact Framework, if we can observe something, we can measure its impacts.

If you want to find out more about what the Impact Framework does, you can listen to episode 58 of Environment Variables.

Why the focus on measurement, you might ask? Well, we've learned that at the intersection of software and sustainability, measurement is the compass guiding our way. How we measure software's environmental impact is more than just a technical detail. It's the key to unlocking the magnitude of change we can achieve.

Here's the challenge. Alone or in small teams, participants will have the freedom to choose from a variety of prize categories, including Best Plugin. Impact Framework itself is just very, very simple. The power of Impact Framework is its plugin ecosystem. We've got plugins which take CPU utilization and turn it into energy. We've got plugins that take energy and turn it into carbon. We need more and more and more of these plugins to be built for my statement I said previously to be true, to take any observation and convert it into environmental impacts. We need plugins for that. So one of our prize categories is best plugin. We want you to build the best plugin you can build. If you submit your plugin idea on the Hack website, We actually nurture you, we help you, we guide you towards designing a plugin which has the best possible chance of winning.

There's another prize category called Beyond Carbon, which I'm very, very excited about. If you can build a plugin which outputs an environmental impact that's not carbon, for instance, water. You can submit your solution to the Beyond Carbon prize category. We really want to move the conversation beyond carbon this year. That's my personal goal.

This year, we've also got prize categories for non technical contributions. We've got a best content category. This is a category for people who would create the best piece of content, be it a how to video or a tutorial or a written booklet on how to use Impact Framework in any context, be it for a particular domain or in a generic sense, that's what best content is all about. How we're also expanding best content is if you're going to write a case study that uses Impact Framework to measure the impact of something and you write up that case study in such a way that it becomes a learning resource that also counts for best content as well.

We also want to encourage people to contribute to the framework itself. The framework is a piece of code which sits on the Green Software Foundation's GitHub repository. And if you can contribute to that code by going to our GitHub repository and picking up an issue and saying, I would like to work on this issue for the hackathon. Please go right ahead and we'll nurture you, we'll guide you, we'll support you because we want to make sure your contribution is accepted. But that is how you can submit the best contribution category.

And this year we're thrilled to open our doors to students. We have two prize categories for students. We have an undergraduates category. If your entire team is made up of undergraduates, you can then win a set separate accessory prize for undergraduates.

And again, if your entire team is made up of under 18s, we also have another prize just for you, an under 18s prize.

So how can you become part of CarbonHack24? It's as simple as signing up on our website at grnsft.org/hack/podcast that's grnsft.org GRN SFT. org forward slash hack forward slash podcast.

There you'll find all the details about the event registration and upcoming live sessions where I'll be talking every single Monday, giving you an overview of the hackathon, what's going on the latest information and just taking you some of the latest projects. This is your opportunity to be part of a global movement that's shaping the future of sustainable software.

We also extend a warm invitation to organizations that align with our vision to join us as sponsors. This is your chance to witness early stage innovations, connect with talented individuals, and showcase your commitment. If you're interested in sponsorship, visit the same link, which is grnsft.org/hack/podcast.

I'm thrilled about CarbonHack24. We're going to explore innovative ways to measure the environmental impact of software. Join us for three weeks of exciting challenges where engineers, designers, and content creators will use Impact Framework to measure software's environmental footprint.

We can't wait to see what innovations and solutions emerge from this incredible event. See you there.

View Details

This Week in Green Software, host Chris Adams is joined by Gabi Beyer and Brendan Kamp from re:cinq to talk about the recent initiatives to and consequences of the prolonging of the lifecycle of technology. The challenges of measuring carbon emissions in personal laptops and cloud services are discussed, highlighting the complexities of quantifying environmental impact, as well as companies reporting on these metrics. Tune in for a lively discussion on sustainable software development.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Gabi Beyer: LinkedIn | GitHub * Brendan Kamp: LinkedIn | GitHub | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* £200m Octopus backing to heat up pioneering Deep Green tech [11:36] * 2nd-hand phone market hurt by users sweating devices longer • The Register [13:53] * Google endorses Right-to-Repair law in Oregon • The Register [17:24] * Chromebook expiration date, repair issues 'bad for people and planet' [18:16] * Google promises decade of updates for newer Chromebooks • The Register * Fit for 55 - The EU's plan for a green transition - Consilium [20:07] * The anti-greenwashing rule: Proposed FCA guidance | South Africa | Global law firm | Norton Rose Fulbright [20:18] * Baselining Software Carbon Emissions - A Use Case by UBS | GSF [20:54] * Perf-icient Measuring of Laptop Energy Consumption and CO2e | re:cinq [21:48] * ABN AMRO Embarks on Hybrid Cloud Transformation [24:54] * GitHub - re-cinq/cloud-carbon: A open telemetry exporter to calculate the carbon emissions generated by your cloud infrastructure [25:46] * Amazon claims it was the world's largest buyer of renewable energy in 2023 [26:41] * How much power do hyperscalers use, and how much would it cost to go fossil-free 24 / 7 ? | Chris Adams [27:57] * https://github.com/Green-Software-Foundation/real-time-cloud/issues/20 [30:59] * Tripling the lifespan of servers: why we retrofitted 14,000 servers | Scaleway [35:39]

Events:* Carbon Hack 24: Where measurement meets innovation, and impact knows no bounds [39:52]

Resources:* Civo.com [07:26] * Leaf.cloud [08:06] * What Is Embodied Carbon? And What Does it Have To Do With Sustainable Software? | re:cinq * GitHub - re-cinq/cloud-carbon: A open telemetry exporter to calculate the carbon emissions generated by your cloud infrastructure * https://github.com/Green-Software-Foundation/policy-wg/issues/59 [24:19] * Projects | GSF [26:16] * The Week in Green Software: Code Green and Clean Power | GSF [31:15]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

TRASNCRIPT BELOW:

Brendan Kamp: Transparency, right? I mean, this is the key for the cloud providers, I feel, at the moment, is just become more transparent about some of the, this data so that we can do the work to calculate, but just give us the data to do it, right?

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host, Chris Adams. Hello, and welcome to another episode of Environment Variables, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. We don't shy away from diving into the details of sustainability in software development in this podcast. But if we want this to be a field that has widespread adoption, we need to make sure there's space for people entering the field from the wider digital sector, rather than being a specialist place that only really accepts people who have a PhD in green IT already. And it's also good to know about what's happening in the wider world, too. So last year, we started a new format of this podcast that we call This Week in Green Software, which was a sort of roundup of stories and links related to. Yes, you guessed it, Green Software, often with members of the Green Software Foundation coming in to share some of their stories that caught their eyes. It's New Year, and this is our first This Week in Green Software episode. And today, I'm joined by two members of re:cinq, one of the latest organizations to join the Green Software Foundation. So, I'm joined by Brendan Kamp and Gabi Beyer of re:cinq. Hi folks!

Brendan Kamp: Hi, nice to be here.

Gabi Beyer: Hi. Hello.

Chris Adams: Cool. Alright, so, I'm not normally sure who to give the floor to first in introductions like this. So I'm just gonna go for like, alphabetical sort here, which I think places Brendan slightly ahead of Gabi in this one, right? So Brendan, are you okay just introducing yourself and what you do at re:cinq?

Brendan Kamp: Yeah. First time I'm ahead of Gabi in anything, so I'm happy. So I'm Brendan. I'm a founding engineer at re:cinq. So I've mostly in my career worked with platforms and system level stuff. I did a small sense of developments on apps and I've recently just started learning about green software. And so I've started a blog forum called thegreencoder.io to capture all the learnings and things that I've been doing.

Chris Adams: Cool. Alright, thank you for that Brendan. And Gabi, I think you're next in the sorting order, so yeah, over to you.

Gabi Beyer: Yeah, so I'm Gabi. I'm also an engineer at re:cinq. I've done a bunch of different types of engineering over my years from Linux to platform to now doing green coding and optimization engineering. And recently we actually, Brendan and I both got accepted to do a talk at KubeCon, so we're excited for that.

Chris Adams: Oh wow, congrats! I need to check. Where is KubeCon taking place this year? Because I, I'm a little out of date when it comes to knowing where that massive conference moves around the world.

Gabi Beyer: Yeah, it's in Paris.

Chris Adams: In Paris? Oh, wow. That's not that far from Berlin. Maybe we'll see you in person in that case.

Gabi Beyer: That'd be great.

Chris Adams: Yeah, congratulations.

All right. Okay, so thank you for that, Gabi. Brendan, during our intro call, just to get to know each other and figure out what we're going to talk about, you mentioned that you're joining this call from the Netherlands. But you haven't always lived in the Netherlands. And you even mentioned living on a farm at one point before. So before we dive into the world of like your life with servers, maybe we could talk a little bit about Brendan pre-cloud or some of that first, before we dive into the nerdery.

Brendan Kamp: Yeah, perfect. Well, so I've lived on a couple of farms. The first one in South Africa, I was born on a farm. And then a couple of years ago, I think it's about six years ago now, we moved to Germany. Didn't enjoy Germany, so we decided to, mid pandemic, do the only option of going into the middle of nowhere, Norway, and living just on the edge of a fjord in Norway for a couple of years.

So yeah, and now jumping back to Amsterdam to get a bit more into the fray of things again.

Chris Adams: So let me just get this. So South Africa, very, very warm. Germany can be freaking cold, but also kind of warm. And you thought, "nah, this is too warm and temperate for me. I'm going to go all the way to Norway," where you're like, "ah, this is maybe a bit too cold." And now you're back in

Brendan Kamp: Too cold. Yes. A hundred percent. Definitely a weather thing.

Chris Adams: Well, I could sympathize with that as someone who's been living in Germany for the last 10 years and seeing a kind of recent cold snap, but also it getting chuffing hot over the summer, or comparatively speaking for Germany, at least. All right. And Gabi, when we were chatting about this inside the CNCF Slack, which is the Cloud Native Computing Foundation, Slack, I think, I saw your profile photo and I saw that you had a bike, but you also had a adorable dog on there. I guess there's a story there too, before we dive into the world of servers.

Gabi Beyer: Yes, that is Bruce. He is famous among all of my friends, and he is 13 now. He, I'm from Seattle, and he came with me to the Netherlands. And yeah, he is enjoying cycling around the city just as much as I am.

Chris Adams: Oh wow, so he's got a little dog passport and doggy visa and stuff like that, right?

Gabi Beyer: Whole European passport.

Chris Adams: Oh wow, that's cool. All right, thank you. And hello, Bruce, if you're listening, I suppose. All right. Okay, so thank you very much for giving us the time and introducing yourselves. Folks, if you haven't listened to this podcast before, my name is Chris.

I am the executive director of the Green Web Foundation, which is a Dutch nonprofit focused on an entirely fossil-free internet. I also work as one of the chairs of the Green Software Foundation's Policy Working Group, which basically does stuff related to new legislation, figuring out how to interact with new laws being made, and also creating some kind of fora for people who are basically trying to figure out how to deal with green software at a kind of legislation level. We also do a bunch of other things at the Green Web Foundation, but I'll maybe mention those as we discuss. All right, then. So, Brendan, Gabi, I assume you're sitting comfortably, right?

Gabi Beyer: Oh Yeah.

Brendan Kamp: Ready.

Chris Adams: Okay, cool. All right, just before we start, sorry, I almost forgot. While we talk about this, we will mention a few stories.

We will link to all of these in a transcript and some show notes at the end of this podcast. But we also will have these as a markdown file on GitHub. So if there's a mistake for anyone who's listening to these, or there's something that you didn't quite understand, you can totally submit a pull request to improve it.

And we will thank you in the next episode for your diligence in helping capture knowledge for future listeners. Alright, okay then, I guess we can start with the news stories, Gabi, the first one, I think we spoke about this before, this is one that I might let you kind of talk about first I suppose. This is Deep Green, which is the company based in the UK who put servers I think at the bottom of swimming pools, or in swimming pools where they use the waste heat to heat the swimming pool so you don't need to burn gas to heat the swimming pool, but that also has a nice effect of cooling the servers themselves. They've been doing a bit of work with a cloud provider called Civio, and I found out about this through, there's a serverless provider called Fermyon who are doing some really interesting stuff with scale to zero servers. And I think a bunch of this stuff seems to be running on Kubernetes. I imagine this, between the two of us, Gabi, you might have some exposure to.

I've got to ask, first of all, have you used any kind of serverless tools in the first place like this? And do you think this is a trend that we're going to see more of, this idea of the cloud not just being in gigantic data centers, but in some cases at the bottom of swimming pools where the heat is actually being used in a productive way rather than being vented into the sky?

Gabi Beyer: Yeah, I think that it's a great initiative. We actually, Brendan and I attended a talk a couple of months ago about a Dutch company doing a very similar thing called Leafcloud, and they would put them also in pools. They've created, I think, a heater that yeah, would take the energy from servers and transform them into heat for pools and also apartment buildings. So they're putting them into apartment complexes to heat the housing.

Brendan Kamp: I was always wondering, cause Gab's kind of explained this a little bit when we were there, but I was always wondering how they do the security side of things. Right? I mean, data centers are generally these walled off environments where you're storing companies' data. So understanding the technology underneath that to kind of like not allow those kinds of intrusions.

I mean, that must be phenomenal. Right?

Yeah,

Chris Adams: This is actually one thing where I'm moving out of my expertise, but I do know that this is actually something that is an ongoing challenge when you think about edge and stuff like that, because most of the time you, like you say, people talk about data centers as big buildings with big scary dogs and men, often with like some kind of weaponry patrolling these, and this shifts to a wider, more distributed set of places does mean that you might think about physical security differently to some of the other ones. Now, my understanding so far is that there is a bunch of different forms of encryption used so that the actual content is not particularly readable in many cases. But this is also something that, because we're on a podcast and there's more than just the three of us involved in this conversation, albeit many of them more passively at the moment, something we can find a bit more about or even raise in future, because you're right, Brendan, this is going to come up again and again and again. I'm also glad, Gabi, that you mentioned Leafcloud, because I'm actually quite a fan of them, because as I understand it, Leafcloud offer things like, compute as a service, storage as a service, all the things that you might see from some of the big cloud providers. But, so it's the same kind of API, like I said, like the idea being that you don't need, you don't need to care where the cloud is. You just need to know that your tests pass or you're getting the same things responding. Maybe you could just touch on that a little bit more because I haven't actually used them myself but I did read over their website and they've got a cool domain.

I think it's leaf.cloud or something like that which definitely got some nerd points.

Gabi Beyer: Yeah, I actually haven't used it as well either, but talking with some of their engineers, I found them very interesting, along with the domain. They have some funny lunchtime antics that they seem to get along in. But as for the technology itself, I Yeah, I can't really speak to it because I've never used it as well. But to kind of go off of the security question or thought Brendan had, I'm under the assumption that they might, for both use cases, since the Fermyon one is serverless, I'm assuming that they don't store any data at these pool sites or at these hotel complexes.

And it's a lot of, they do still maybe have that big scary data center where they send all the data to, but yeah, the actual operations are occurring elsewhere.

Chris Adams: I see, okay, so maybe there's a thing where it's just being loaded into memory for a short period of time and then it's being processed and then the results are being put back somewhere else, back into somewhere else in the cloud where it's somewhere more durable. Well, I guess there must be some people who seem to be okay with this because Deep Green, in the last literally couple of weeks, there was a really interesting announcement. They raised 200 million pounds for a massive raise to start rolling out these kinds of like integrated servers all around the UK. This was an investment by Octopus Energy, who are probably one of the kind of energy unicorns, I suppose, globally, basically. So that's something there, and we'll share a link to that as well.

So maybe we should ask one of them about, say," In your due diligence, how did you figure out how to answer this question? Because when we were looking at this, we thought this was cool, but we didn't quite figure out this part here." And that's probably the thing that we need to understand before we start diving into dropping servers at the bottom of swimming pools and getting them to execute cloud functions.

Brendan Kamp: Just like off the top of my head, this sounds, I mean, this sounds right in the realm of Kubernetes, right, where you have this idea of, you just have all these nodes everywhere, which would be the pools, right? Like these little servers are just nodes and you're just using them as a pool of resources that maybe you

Chris Adams: Ba dum tss. Very good there. Yeah.

Brendan Kamp: Yeah.

Chris Adams: A literal swimming pool of resources. Yeah. Okay.

Brendan Kamp: Exactly right. Which makes sense why they would partner with Xevo, I think, cause I think Xevo is Kubernetes first provider,

Chris Adams: I think that is the case as well. Yeah.

Brendan Kamp: Yeah, so, I mean, it sounds plausible, and I can kind of do the mental gymnastics to how it could work, but it would be so fascinating to see some white papers from these companies coming out and saying, this is how your data is secure, this is why you don't need to worry, right?

Chris Adams: Well, I'm glad you mentioned that because we actually have a future episode with Kate Goldenring of Fermyon, who basically was one of the first people to respond when I asked some really nerdy questions on the Green Software Foundation discussion board about "how do people do isolation for this?"

Because one of the things about some of these serverless tools is figuring out, "okay, how do you make sure that when you're running some code, you're not being affected by other people's noisy neighbors" and stuff like that, basically. So yeah, we will definitely be diving into that into almost excruciating detail in a future episode.

So yeah, I'll be looking forward to that. Okay! Thank you for that, Gabi. This was fun. Okay, next story that we had on this was this one in the register, actually. So this was about users now keep cell phones for 40 plus months, and this is hurting the second-hand market, apparently. So this is one thing that, Brendan, I was thinking of you when this story came up, because we have seen a slowdown in people buying new electronics, and actually this has been one of the real problems we've seen cited with embodied energy and embodied carbon and hardware. And now we've actually seen a new trend where people are not choosing to update their phones every year by the looks of things.

Brendan Kamp: I absolutely love the headline, because it's like, they're making it sound like such a negative thing. "Oh, you're crashing this whole market of secondhand users," whereas you're just utilizing your resources for a longer time, right? And so, I mean, when I was going down the rabbit hole of embodied carbon, cell phones and laptops were one of the things that majority of the carbon emitted for these devices is in the manufacturing side of things and not actually in the electricity usage. So extending the lifespan of these devices just by, I think it

Chris Adams: one of the best things you can do. Yeah.

Brendan Kamp: Yeah, exactly, exactly. But it's also going to hurt the companies that make the devices, right? And I think that's where there's the struggle, is "how do we still keep this growth going for these companies so that they can innovate, they can like do these things, but not destroy the world by littering it full of.

Chris Adams: Almost. Yeah.

Brendan Kamp: Exactly. Yeah.

Chris Adams: So I just realize that we're talking about this and you've used this term 'embodied carbon' that may be new to people. So when you say the word embodied carbon, I assume you're talking about the fact, I mean, you did a quite good job of explaining this, the idea that if you're going to have a phone, because loads of energy goes into making that phone, like you need to heat sand up to like 1200 degrees Celsius to make a silicone crystal before you can slice it and then turn it into a chip. That's going to be a bunch of energy used there. And that's usually come from fossil fuel sources, so that's the embodied carbon that you're referring to in that context, right?

Brendan Kamp: Yeah. A hundred percent. And it's also, they try and include the other things in terms of like transportation of the device from the manufacturing plant to the sales warehouses, the end of life, carbon footprint, and all of these they try and calculate all together and they have this global term of embodied carbon. And for these devices, and you might need to check my data, but I think phones and laptops are like, 60 to 70 percent of their carbon emissions are wrapped up in their, in the embodied carbons, whereas servers, funnily enough, because of the immense power or energy that they use, it's only like 15 to 30 percent of their emissions.

Chris Adams: So it's the other way around then. Alright.

Brendan Kamp: Yeah. So servers, the embodied carbon isn't as big, but it's still a nice slice. And funnily enough, this is something that Gabi's and I have been struggling is how to calculate embodied carbon for like using of devices, right? So if you only use a device for a small amount of time, like how much of that embodied carbon pie is

Chris Adams: is attributable to you, it's your share versus someone else's share, right?

Yeah, you do need to kind of, I mean, maybe this is actually one thing that we'll just touch on a little bit before, because, Brendan, what you mentioned just like, oh, it, you know, this, the, the framing of the story, like, "Dammit, these people should be consuming faster," right?

I think that's an interesting one because there's also one thing, one interesting development we've seen on the policy side is that Google, which the register always refers to as the chocolate factory, which always makes me giggle; they're one of the second firms now that has actually come around on right to repair.

So I think last year or the year before you had a whole bunch of actual shareholder activism. You had some people putting forward a kind of shareholder resolution to basically start looking into the ways to reduce the embodied carbon of owning a Microsoft Surface. And eventually it passed, despite there being a bit of pushback against management saying, "no, we don't want to do this." And now you saw Apple come around last year saying, "oh, we're kind of okay around this right to repair," but they had this whole notion of like parts pairing, which basically meant that it's right to repair as long as you only ever buy the parts from one provider at Apple's prices, which is probably good for Apple shareholders, but that does kind of mean that that is not possibly the intention of the, of this. And then Google have recently come through and said, "yeah we're actually coming around on this as well because we realize we've got loads of Chromebooks around and if we can fix them rather than replace them that might actually do something for the embedded carbon."

And also this whole parts pairing thing, which has been one of the last things that large tech firms want to hold on to, they've said, "yeah, we're okay with not having the parts pairing thing" as well, as I understand it. So this is actually an interesting development. I don't know if there's another loophole or something like that, but this really caught my eye and I figured it was, I was thinking of you when I read this actually, Brendan.

Brendan Kamp: But now also coming out with the new EU greenwashing laws that have recently been passed, for Google, I would assume this would start looking good for their data because very soon, these big corporate companies, if they want to do work in the EU, are going to have to start providing this kind of data of just how much emissions are their devices emitting, etc.

And if they are reusing, and I mean, I've always felt like this idea of "you can only use our things" is ridiculous, because, for instance, if your sole goal is to make money, it works, but now we're shifting to a world where there's other incentives, and if those incentives are, "hey, we want to reduce our carbon," then if a vendor is providing the hardware, those emissions are for the vendor, they're not for me, they don't go towards my numbers.

And this means that you have a more collaborative society. So yeah, I'm really interested to see where this goes, especially in the next couple of years, you know, Fit for 55, the new greenwashing laws, because I think these tech companies are going to really have to do some changes.

Chris Adams: All right, you've added a couple of things that, Gabi, I'm going to ask you a little bit about. So there's a couple of interesting terms that you mentioned there, so Fit for 55, this is one of the big announcements inside Europe to basically say "we're gonna reduce emissions by 55% by 2030." And there's a bunch of new laws and things tied to that.

And you also spoke about this anti-greenwashing resolution. We'll share a link to that 'cause I believe that was passed last week or the week before, inside European Parliament. So there's a few follow-on steps and essentially saying things are carbon neutral isn't going to fly unless you have a really, really clear way of backing it up.

So when Apple have mentioned things like they're having an entirely carbon neutral watch in Europe, that won't be a thing that you can do. And I imagine we might see this also percolating into other territories as well. All right then. So Gabi, there's a really interesting story here, which is the, this is actually UBS, the bank, who are basically saying, "Hi, we're trying to develop a baseline for some of our early steps." They used to talk a little bit about how this is quite hard. And as I understand it, you spent a bit of time, and you even wrote about your experiences, taking some steps to try and measure things just on a single laptop. Maybe we could talk about that before we speak more widely about this one here, because there's some really nice things to touch on for the UBS story, and they explain a few steps they've taken, but maybe we just touch on your experiences with your first steps and then go work a bit more widely because I think you did write about this after, was it the SDIA green coding workshop in Berlin? But I think you mentioned something that maybe you talk a little bit about that then we can go into the wider case here because it's very rare to see large organizations talking about this. And to get there, you need to figure out what to do on your own laptop first, right?

Gabi Beyer: Yeah. Yeah. Inspired by the SDIA. Yeah. I wanted to measure the carbon emissions and the energy consumption of different processes running on my laptop. And that was challenging enough in itself. And to do that, I used this Intel RAPL hardware component that can measure the energy, and I used Perf, which is also a Linux command line tool to, which utilizes RAPL, sorry, which then can get the amount of joules of energy a process is running. And then, once you can get that energy consumption, you must calculate it into kilowatt hours, and again, multiply it by the grid database, and you can get the carbon emissions. So there's a lot of steps just to get the energy consumption and carbon emission data for a single laptop. And to build off of that, we've been working a bit on figuring out how to measure cloud, different cloud services, their emissions, specifically like VMs, which is similar to what UBS seemed to do because they were running VMs for their application data. And that is another level of challenge because the hardware components are being shared within the services. So you have to kind of then determine how resources are being shared.

Chris Adams: Yeah, so it's not just a single laptop. It's like you're sharing your laptop. So if I understand it, so doing it, it's hard enough for you with a laptop when it's just you owning the laptop, when you don't have to share that laptop with other people. When you're looking at a server, the number of people who you're sharing it with could be changing over time. And that means that There's almost like a kind of integration, mathematical integration problem that you also need to wrestle with as well. And that's another thing that makes it somewhat more complicated.

Brendan Kamp: Or maybe just to touch on, also you did the CPU calculations for VMs, but what you're currently struggling with is memory, right? Because there's no data on memory.

Gabi Beyer: Yeah, that's specific to the cloud though. We don't have their, like, hardware memory information, like what kind of DDRs and RAM stuff they're utilizing. And each one kind of emits different energy usage depending on that. So it's kind of difficult to say, like, "this application is using this part of memory whereas this application is only using this much."

So that's been hard to calculate.

Chris Adams: It's a real challenge. Yeah. This is something that we've come across quite a few times. There is actually two things that may be worth touching on here, actually. So inside the Policy Working Group where we work, we've seen various sectors really struggling with trying to come up with some reliable numbers for this.

And there's actually a roundtable that we're organizing in the coming months specifically for the financial sector, because amongst all of the sectors so far, they're weirdly one of the more transparent so far. I think it's partly because they've bought so many servers already, because they, That they actually have access to these numbers, whereas some cloud providers don't have this, and we'll show a link to a post about, there's a bank called ABN AMRO.

They're the third largest bank in the Netherlands. They actually were on the record basically saying, look, we've looked at our figures and 40% of our emissions are attributable to our own infrastructure, and partly this because they own some of their own servers, and they're moving to the cloud, but this is one place where it actually has been easier for people to come up with these numbers.

But when you get to the cloud, it becomes, as you mentioned, it's way more complicated, because Gabi, you said, who's RAM? What's CPUs? What machine? The fact that you don't know where it is means it's really, really hard to model some of this stuff as well, actually. And, yeah, I think this is going to be an ongoing challenge.

But I wanted to ask you, actually, when you're on this, there's a project that I think I saw in the kind of recent GitHub repo called, I think, is it called Carbon Cloud? This is a Golang thing or something running on the server. Maybe one of you could talk a little bit about that because that caught my eye, basically.

Brendan Kamp: That's all Gabi.

Chris Adams: Yeah? Okay. So, Gaby, I'm curious, maybe you could talk a little bit about some of that, because it seems like you've tried to wrestle with some of these problems yourself, first hand.

Gabi Beyer: Yeah, we're trying to, written in Go, we're trying to measure the carbon intensity of cloud software. But our goal is mostly to do it in real time and to be able to provide like a metric that users and developers can utilize and get that quick feedback cycle loop to see what is changing and going on in their code base that could be producing these higher emissions or change in emissions and stuff like that.

Chris Adams: All right, cool. Well, in that case, one thing you may be interested in is, so in the GSF, there's a project called the Real-Time Cloud Project, which I've been involved with, and we'll talk on, talk about a little bit later, because this is one thing that, as someone who's working in an organization that cares about a fossil free internet, a significant chunk of that is going to be, well, decarbonizing the power. And this is one thing that we've struggled with as well. It's really, really hard to find the numbers for this kind of stuff. And that probably brings us to the story that I kind of put forward here. So there is a really interesting story from Data Center Dynamics about Amazon, basically saying they're claiming they're the world's largest buyer of renewable energy in 2023. They said this story and we'll share a link to this and it sounds, this sounds really, really good when you first think about it, right? Like they're a large provider, they, they basically mentioned that they've invested in something like more than 100 new solar and wind energy projects and stuff like that. This adds to a total of nearly more than 500 wind and solar projects globally, right? So these are the figures that we have here. And this sounds on the face of it kind of large if you were to assume how big Amazon is compared to other providers, right? And I've been really struggling to figure these figures out because if you look into sustainability reports from any of the large providers, Amazon, as one organization that hasn't really published its absolute energy use figures ever, or it's very, very hard to find this information.

If you sign an NDA, you might get the figures yourself, but most of us don't sign NDAs with Amazon because, well, I'm not spending 15,000 Euros at least each month with them myself. But, what we found out when I was doing some research into this was the Carbon Disclosure Project is one place where these figures are submitted.

So I did a bit of research myself and we've shared a link to this specifically. Google and Microsoft both published their CDP responses listing a bunch of really interesting answers to the questions and this is helpful because it allows us to have comparisons across each of these. And the short version of this is that when I looked into this, the figures for absolute energy use were about just under 40 terawatt hours, 39 terawatt hours, is what was listed inside this, which is, for most of us, we don't know what that figure would even kind of compare to, right?

Like, is it like, you know 'giga watts', 'gigawatts,' 'kagoolies,' like, what does that even mean? For context, Ireland, the entire country, used 34 terawatt hours of power in the same year as this reporting. So Amazon is basically, is using more power than Ireland, but they also in the Carbon Disclosure Project, they also list how much renewable energy they've used and therefore have purchased. And they've purchased 35 terawatt hours of clean energy. So that's, they've bought more clean energy on an annual basis than Ireland or the country has used in the same year, which is mind-blowing as a figure. And it kind of gives you an idea of the scale we're talking about here, for example. Brendan, you got something to come in there.

Brendan Kamp: Yeah, yeah. So I just have a question and I'd love to hear your opinion on this around carbon contracts, right? So my understanding of carbon contracts is you're buying energy that would be used by another company or green energy. And you're then saying, "all right, that is now my green energy." So it's not necessarily a reduction technique.

It's more of a auditing technique in my mindset.

Chris Adams: I see why you would say that. And to be honest, the market structure is such that it's actually quite complicated and not very accessible for most of us. All right. I think what you may be referring to are two separate things.

So if you want to report electricity usage and the carbon from electricity usage, there is a approach which is based on your usage tied to your location,

right? And there's another approach which is designed to recognize the fact that you've Bought a bunch of renewable energy. So one is called the market-based approach and one is called the location-based approach for this. And one of the challenges that we've had over the last 10 years is that you can basically buy power and separately from your use of that power, you can just buy some certificates that have been sold by a bunch of green energy producers.

Because it may be that in certain parts of the world, people don't value those certificates, and then you can then apply that to your usage to then say, "well, this is quote unquote Green Power." This has been the approach that has been used. And Ireland is a particularly interesting case because in Ireland, you've had the Advertising Standards Authority basically say, "yes, this may be how your market works, but it's still misleading to consumers. So therefore, we will not accept, you know, we're going to stop Irish energy providers selling green energy that uses this certificates based approach." Now, the thing that's quite interesting with Amazon is that there's a project inside the Green Software Foundation called the Real-Time Cloud Project, which Gabi, I mentioned before. We've actually got someone who's been literally counting up all of the output from every single project to compare this to what the figures might actually be, so that you can get some idea of what the physical production might be versus the amount of credits that might need to be purchased. And this is, we've actually, we can also link to another podcast where we talk about this in terms of additional, deliverable, and timely as ways of talking about green energy.

Where if you're going to actually have, if you're going to make a claim around green energy, you need to be able to basically address these things. We'll link to the podcast episode which dives into this in more detail, but the short version is if something's additional, like you said, it's not reallocating green energy, it's introducing new energy into the grid.

And this is one thing that some of the large providers tend to do now, they make a big story about, "Hey, look at this new wind farm that we've helped create." And that is usually financed through a power purchase agreement for where people do that. So that's kind of the additional part. Now, deliverable is another thing.

So deliverable in this context might be, "I financed a renewable energy project in Norway, but my use is in Spain," right? Which is the other end of Europe. Now, it's not very plausible that the power would go all the way across Europe without any losses to then power your data center in Spain, for example.

So that's deliverable. And then timely is basically saying, "well, I funded a bunch of solar panels, so therefore I'm allowed to say my servers running at night are green." Now again, that is not necessarily the most plausible claim that you would make. So this is why you need a combination of all these three.

And this is one thing that I believe Nina from Energy Tag in the episode we'll link to explains in a lot more detail. Anyway, going back to the original story. Yes, it's really, really good that you see a company like this saying "yes, we're the largest provider," but they're just one of the largest users of energy, full stop.

So just by dint of the size, that they're going to be one of the largest. And when you look at the amount of energy used versus their revenue, I mean, I've shared this, actually, this research, we can see if you assume a figure of 100 Euros per megawatt hour, 100 Dollars per megawatt hour used, which is a pretty generous figure for data centers. It's, what, 0.7 percent of Amazon's revenue, and it's less than a percent for Google's revenue, less than a percent for Microsoft's revenue, so this is actually a good thing, but this is often a more statement of how large these companies are, rather than how much of their money and their revenue they're dedicating to basically green energy.

And that also tells us that we could probably be moving way faster. So that's my, as a executive director of a nonprofit, talking about this, saying we should probably be doing this more, especially when you look at how much money has gone to basically buying your own shares to make your share price go up rather than make sure that we have a functioning society and habitable earth.

Brendan Kamp: So do you foresee any of the new regulations coming in increasing the percentage of revenue that they'll be spending on renewables?

Chris Adams: This is an interesting question because typically when you look at it historically, you've seen that a significant part of the funding for renewable energy has come from various kinds of subsidies to make it easier for companies to get on board. Like, companies will basically say, I'm not going to do this until it makes sense to me on a financial basis. And if you're a hyperscale provider, or if you're just a large user of energy in total, the reason you would have a PPA is, or you would use renewable energy, is yes, it makes you look awesome and looks like you care, and it's good, but it's also the cheapest way to buy power, right? So it's almost willful to choose to buy fossil-based power in lots of places, if you can get a contract like this.

However, there are complications about making sure that the power is both timely, deliverable, and additional, like we've mentioned, but these numbers, the figure of a hundred dollars per megawatt hour, this was something that I ran by some of the energy modelers who we interviewed before, and they said, "this figure is, yeah, that's not an unreasonable figure to use. You could do that."

So if each of these companies doubled their... the amount they're dedicating, they could absolutely all go to 24/7 fossil-free very, very quickly. And there are smaller companies that are already doing this, who are already at 99%. So we'll add some links to that, but I better move on to the next story because this is something that I could talk about literally for hours. All right then, so the next story, this was one I think that you shared actually. Tripling the lifespan of servers. Why we retrofitted 14,000 servers. This is a story from Scaleway, the European cloud provider.

And Brendan, is it okay if I just hand over to you for this, to explain this one? Because you shared this, and I think it's actually quite interesting to see a company talk about this.

Brendan Kamp: Well, this was just something that, you know, pops up on your feed and caught my attention, obviously with talking about embodied carbon, quite a lot recently, the lifespan of servers is very much at the forefront and Gabs, correct me if I'm wrong, what do we estimate in the lifespan of servers? Is it six years?

Gabi Beyer: Think it's four. Maybe by dell.

Brendan Kamp: Four years, yeah, so like a four year server. And what Scaleway has done is they actually went in to their data center and did some, you know, a bit of analysis on what parts of servers were failing. And it turned out in this case, that majority of them were hardware components, the RAID controllers, and in the RAID controllers, the part that was failing was the battery.

Now, RAID controllers are slightly more old-school components of servers. Nowadays, you have software based RAID. And so what they did was they thought, okay, we can actually remove this components and potentially that could prolong the life of these servers and just switch them over to a software based RAID.

Now, don't ask me what RAID is. I'll probably get it completely wrong, but.

Chris Adams: a Redundant Array of something Drives,

is what it is.

Brendan Kamp: It's, it's, it's, a hardware thing.

Chris Adams: Yeah.

Brendan Kamp: But just the understanding that they invested all the time and money to go and do, I think they did 24 or 25 POCs, just proving that this could work. Then they went in and took out 14,000 of their servers, moved them to a new data center, updated them with these new controllers, and put them in, and carried on running them. And they had no reduction of quality and service, right? So the servers performed as well, if not better, once they'd done this. The hyperscale is also starting to invest in these ideologies a bit.

I mean, the amount of servers we can save, the amount of embodied emissions we could like reduce by, it would impact server companies quite considerably, but I mean, something has to give at the end of the day. And another thing that they also did mention, which I found fascinating was because we currently have this big chip shortage due to, you know,

Chris Adams: Supply chain.

Yeah.

Brendan Kamp: Supply chain, etc. The servers that were redundant, that they couldn't migrate to this new setup, they stripped for parts, and they're using those parts to maintain the servers that they updated. So they've kind of really tried to look into every single facet of these servers and kind of see how much longer that they can make them last.

And I mean, yeah, from four, as Gabs said, to 10 years now, I mean, that greatly reduces the percentage of the embodied carbon of those servers.

Chris Adams: Yeah, that is, on that kind of scale, that's a meaningful thing to look for.

I guess we should probably be asking for these figures when we purchase cloud services. Ask, "can you tell us about your embodied carbon for your service as well in that case?" Huh.

Brendan Kamp: Yeah. Transparency, right? I mean, this is the key for the cloud providers. I feel at the moment, it's just become more transparent about some of the, this data so that we can do the work to calculate, but just give us the data to do it. Right?

Chris Adams: Gabi, I see you nodding along like this is a thing that you've, you might have some scar tissue developed over the months trying to wrestle with.

Gabi Beyer: Just a little bit of blood, sweat, and tears.

Nothing, nothing I can't handle.

Chris Adams: Okay. So you heard it here first, please share these numbers if you operate some kind of cloud service or you're providing the infrastructure that people run on. Maybe it's worth asking the Leafcloud folks from up there, because they might have some of these numbers.

Alright then.

Gabi Beyer: That's a good idea.

Chris Adams: Folks, I've really enjoyed chatting with you and I've realized that we've almost hit the hour that we have allocated and I haven't got around to rounding this up and basically plugging this big event that's coming up.

So on the subject specifically of transparency, the Green Software Foundation runs a kind of annual hack day or hack event basically. Rather than trying to compress building anything into 24 hours of Red Bull, chocolate, and delusion, it's actually spread over a longer period of time. So this is actually a hackathon kind of thing that starts on the 18th of March and runs until the 8th of April.

So that means that as people who might be involved, we do get to sleep and eat and see our families and like, live full lives as people rather than just machines that crank out code. And this year, the focus is around a new initiative called the Impact Framework, which is essentially a bit like a kind of manifest file, or like, you can think of like a Terraform state thing for your entire system that enumerates through all of the figures for like carbon emissions or something like that.

It's designed to be kind of open and flexible. And there's a hackathon all about that at hack.greensoftware.foundation. And there's some specific awards around talking about measuring things beyond carbon, so that might be useful for some of the things we touched on today. Creating the best model so that if someone wants to figure out the emissions of using a service, like say the carbon cloud thing, that might be an example.

The best content for explaining why this matters. There's the best contribution to the framework itself, because it's an open source framework written mostly in TypeScript. And finally, because there's loads of undergraduates who will be alive longer than we will be and have to wrestle with this, the best undergraduate project as well.

So people can register interest there. And I think that's me done with my contractual obligations for this podcast, I suppose. Folks, I really enjoyed chatting with you. This has been loads and loads of fun. Thank you so much for coming on for the day.

Gabi Beyer: It's been really nice.

Brendan Kamp: It was great. Thank you.

Gabi Beyer: Yeah,

Chris Adams: Before we go, I just want to check if people were interested in the work that you do or wanted to follow up, where would I direct people's attention? Is it like, is there a place, a LinkedIn or a blog that you'd like to talk about? If I ask Brendan once again first, because it's alphabetical, and then I'll ask you, Gabi, if there's anything you would point people to, then I think we'll just wrap up after that, actually.

Brendan Kamp: Yeah, I mean, my LinkedIn's quite active. I'm terrible at Twitter, so it's just brendan-kamp-757 I think is the end. And also we do write quite a lot of blogs, so I've got blog.thegreencoder.io and also blog.re-cinq.com, where you'll find a lot of our blogs and things. And Gabs, code-wise?

Gabi Beyer: Probably LinkedIn as well. Maybe, yeah you can look at our GitHub also on re:cinq and Cloud Carbon and, yeah.

Chris Adams: Go from there.

All right then. Well, thank you so much for that, you two. As we mentioned, I'll put a markdown version of the transcript and the show links that we have. And if anyone wants to be mentioned with a PR for anything we fix or a typo, then here's your chance for a tiny two seconds of fame in the next episode. All right. Thanks, folks, and have a lovely day. All right. Ta ra!

Brendan Kamp: Ciao.

Gabi Beyer: Bye.

Chris Adams: Hey everyone, thanks for listening! Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode.

View Details

Join TWiGS host Chris Adams in talking to Kristina Devochko, tech lead of the Environmental Sustainability TAG at the Cloud Native Computing Foundation. Kristina shares her journey from economics to tech sustainability, and eventually joining this Technical Advisory Group. Further, they discuss the mission and projects of the group, as well as how anyone interested and willing is able to contribute. She elaborates on her experience of diving into this new field with no prior knowledge and acts as a reminder that no matter how scary it seems, you can do it too.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Kristina Devochko: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* TAG Environmental Sustainability [09:56] * The Week in Green Software: Carbon Aware Spatial Shifting [15:13] * Kepler | [16:07] * GSF Oslo Meetup group [34:08]

Events: CNCF Cloud Native Sustainability Week (2023*) [14:43] * Green Software Foundation Oslo - February Meetup [34:31] * Carbon Hack 24 | Online | 26th Feb to 15th March [39:02]

Resources:* Cloud Native Computing Foundation [01:53] * Kristina’s cat, Penelope [02:51] * Kristina’s cat, Sofie [02:51] * TAG ENV | Linktree [09:29] * Kepler GitHub repository | CNCF * Exploring Kepler’s potentials: unveiling cloud application power consumption | CNCF [23:23] * Environmental Sustainability Glossary [24:33] * Green Reviews WG task board[24:45] * Green Reviews WG project repository [26:45] * [WG Green Reviews] Design Document * TAG ENV Slack Channel [31:31] * GitHub - cncf/tag-env-sustainability: 🌳🌍♻️ TAG Environmental Sustainability [31:44] * Green Software Champions | Speakers [35:38]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

**TRANSCRIPT BELOW:

Kristina Devochko:** You know, there weren't many there at that meeting, but they were so passionately discussing the different topics around the topic of sustainability in tech, specifically in the cloud native technologies. And I really loved the passion and interest from those who were there.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello, and welcome to another episode of Environment Variables, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. Well, we talk a lot about green software on this podcast. If you've listened to some of these episodes, you'll realize that cloud is a really, really, really big part of green software now.

And last year, the Cloud Native Computing Foundation set up a sustainability focused working group. And given that it's the new year, 2024, it seemed worth checking in on it to see what's new. So today, I'm joined by Kristina Devochko, who's part of the CNCF and some of these groups. Kristina, thank you very much for joining us on the course.

Should I give you a bit of space to introduce yourself and talk about where you're coming from today?

Kristina Devochko: Yes, of course. Hello Chris and hello everyone listening into this episode. Thanks for inviting me. My name is Kristina Devochko. I am a platform engineer at Tietoevry and I'm based in Oslo, Norway, and I am very excited to be here. I am also a Microsoft MVP and a CNCF ambassador. And what comes out of that is that I do a bunch of different activities in the tech community that are mainly related to the topics of cloud computing, green tech, Kubernetes. And one of such activities is my involvement in the CNCF Technical Advisory Group for environmental sustainability, which kind of also correlates with, with a bit of my personal passion for this domain.

And a fun fact about me is that I am what you can call a cat mom at heart. And actually yesterday, right before we joined today with you, Chris, for this podcast, I, me and my husband welcomed two new family members, two adopted kittens that I will run to after we are done with this episode and kind of keep, continue training them to feel safe in their new home.

Chris Adams: Wow, I was not expecting cat pics so early in 2024, but it sounds like we might need to have some reference to this, because you can't talk about cats without sending pictures of cats. So maybe that's something we add to the show notes.

Kristina Devochko: Yeah, that's, by the way, one thing. I love adding the photos, fun photos of my cats into all the technical content I make. So if you would like, we could totally do that.

Chris Adams: All right, if anyone who's not watching for this, I have to say, while I'm using like a basic headphone, Kristina has an awesome set of headphones with glowing cat ears on this. So this may be a running theme for the rest of 2024. All right, so if you're new to this podcast, my name is Chris Adams. I work at the Green Web Foundation, which is a Dutch nonprofit focused on reaching a fossil-free internet by 2030.

I also work in the policy working group inside the Green Software Foundation, where we do work on policies and respond to future coming legislation and things like that. But for the purposes of this show, what I can share with you is that while we talk about this, and we're going to mention various projects, we do our best to share a transcript and set of show notes for all of these things.

And because it's New Year, we're going to be trying something new. We're going to be posting a transcript of this plus all the links onto GitHub. So if there's something that you're curious or you want to learn more about or we've got something wrong, we'll be accepting pull requests for the transcript if there's anything that you really were curious about.

And yeah, we'll be sharing that on podcast.greensoftware.Foundation as per usual. And I think with that, should we begin then, actually, Kristina?

Kristina Devochko: Yeah, let's do it.

Chris Adams: All right. Okay. So, Kristina, you mentioned before that you're calling from Oslo, and I no longer live in England, but I grew up in England, so old habits die hard, and we always talk about the weather.

And I'm calling you from Berlin today, which is coated with snow. So I should actually ask, how is the weather in Oslo today?

Wow.

Kristina Devochko: Oh, that's a very relevant question because it's quite freezing, actually. And like, personally, I love winter and I love snow. And we were lucky enough this year to have a truly white winter and Christmas and the New Year's Eve. But I need to say that this year we had like a few extreme cold waves happening in Norway.

And I was recently reading an article, I live just outside of Oslo and like, right after the New Year's, in the beginning of January, there was a new record that was hit in the Oslo municipality, where it was registered to be minus 31.1 degrees Celsius, and that's like, the previous record was from 2011, and it was 28.8 degrees, I think. And today I had an appointment at 9am before this podcast recording. And when I went outside, I saw that the temperature was minus 20 degrees. So that's kind of when you feel that your nose is full of needles at that point. So I love winter, but not when it's that freezing. But I'm here now in a warm room and happy to be joining you for this podcast. So...

Chris Adams: Well, I'm glad. I'm glad we're both in somewhat warmer temperatures than minus 31 degrees Celsius. All right. Okay. Fun fact for this, if people follow along, there is, if you have any kind of carbon aware websites today, the coldness is actually changing some of the carbon intensity for some websites. So there's a website called Branch that me and some friends maintain.

It actually broke the code because it was so cold and so not windy in the UK for a certain time that the carbon intensity went higher than we've ever seen it. So this is an example of how some of this can manifest in software itself. All right, so we'll get to that a little bit later on, but I should basically, before we dive into this, it's worth asking, you now work in green cloud computing and that's like your new specialization.

But that hasn't always been the case. So if I understood it, you did, you worked as, you trained as an economist first before you came to working with cloud and development, and then you changed directions into this field. Is that the case?

Kristina Devochko: Yeah, yeah, that's true. I mean, I never, I never thought of working in tech as being my kind of career. I wasn't born and raised with like all this programming knowledge from the start. So I came from a culture where it was natural for women to do something else than computer science. So for me, in my head, it was natural to do something like economics.

And that's what I started with. I got accepted to the bachelor's program at the university. And then I figured out that it was so boring. The first year I started, it just didn't work out. I couldn't find the motivation. And I had a friend who was studying computer science, but more into the NLP domain, into natural language processing.

And she kind of challenged me because kind of the atmosphere there was good and people were nice. And it was interesting. So I just took a chance and applied and got in. And from that point on, there was kind of no way back. So I started working with as a full stack developer and got really that spark after studies.

And for two years ago, I think there was someone from the community who challenged me, like, why don't you start contributing to the tech community as well? There is so much you can do there if you really love working with tech also outside your full time job. So I actually started doing that, and from that point on, it's like, I've tried a lot of different things, and I find it being a lot of fun, so it's for me like more, it has become more than a full time job, a source of income, it has become a hobby, and a sort of passion, and like if, since we are talking more about the sustainability in this podcast, personally, I've been really focused on that area, like in my life, in my everyday life, living a more eco-friendly, planet-friendly lifestyle. And from that, it kind of naturally transitioned into also putting focus on that at work, in my company. And from there, I ended up joining the Environmental Sustainability Technical Advisory Group. So it was like a very interesting journey starting, now that I look back at it, starting with economics and thinking that this is my only way to kind of take my career and then like ending up in a totally different space.

That's, yeah, that is somewhat, somehow that was a bit of magic for me.

Chris Adams: Okay, cool. Thank you for that. So there's from an academic transition to I guess an energy transition really. And as I understand it, so in the last year you got involved because you mentioned the Cloud Native Computing Foundation Technical Advisory Group for Environmental Sustainability. That's quite a mouthful.

I mean, I have to ask, is there a short name for it or is there something I should use instead when I'm using that? Because I don't think it rolls quite off the tongue and I'm sure there's a faster way I can refer to that, right?

Kristina Devochko: Oh, yeah, totally. I know. That's like, that's a bit of a wording there because you need to kind of also showcase where this technical advisory group come from. So, like, we call it the TAG ENV, like TAG ENV. So TAG for technical advisory group and ENV is That's kind of our abbreviation for environmental sustainability.

So we just call it TAG ENV or CNCF TAG ENV. So that's what we also use in our writing, writing content.

Chris Adams: TAG ENV is easy. TAG ENV I'm going to use from now on if I'm going to refer to this, because that's much, much faster, and it's kind of fun to say. All right, okay. So I should have to ask then. There is now a TAG that's focused on ENV, right? And maybe you could tell me a little bit about actually what it does, and what kind of work or what kind of projects might be associated with that, for example.

Or maybe even how you got involved in it, actually.

Kristina Devochko: Yeah, of course. So, CNCF has, and CNCF, the Cloud Native Computing Foundation, so I'll call it CNCF. It has a specific structure as an organization, so it has different groups in order to ensure that the different projects and users and organizations that are supporting the foundation can kind of develop and improve in a sustainable, expandable manner. So the, therefore there is a concept called Technical Advisory Groups. And this is basically a group that is led by people that are community members that are specialized in that specific domain that the group covers. And then anyone from the community can join those groups depending on their area of interest and participate in the meetings, participate by contributing to the different projects and activities that are going on in those, in those TAGs, which is the short version of the name. And there are many different areas. There is security, observability, there may be networking and like for, I think now it's two years ago, like one and a half years ago, the Environmental Sustainability TAG was founded by some of the community members. And at first we didn't hear about it. Like I personally haven't heard about it until spring last year, because I was starting to prepare more content on the topics of green tech. And I got in as a speaker at the KubeCon and CloudNativeCon Europe conference, which was in Amsterdam in April last year. And I start, and I was doing my research, preparing for the talk, and I, by chance, found this TAG, this group, and I was like, wow, okay, CNCF has a dedicated group now, but it, it didn't seem very active because it was just starting out. And then I, of course, highlighted it also during my talk and also saw on the schedule during the conference that they had the pro, a group meeting. So I just joined that, actually knowing nothing about the community in that group. And that was really for me as a beginner, a bit scary, but at the same time, when I joined, I was very warmly welcomed and I loved the engagement, you know? There weren't many there at that meeting, but they were so passionately discussing the different topics around the topic of sustainability in tech, specifically in the cloud native technologies. And I really loved the passion and interest from those who were there that I thought, "wow, cool. This seems like people really care about it, not just do it for, you know, to check, have a checkmark somewhere." Yeah, And I started just after that, I came back home and I started joining the regular meetings and just contributing with small steps, just doing some minor changes, asking questions.

And now it's less than a year actually. And now right before Christmas, I got appointed to be a tech lead for the technical advisory group. And I'm really happy about that because I've been putting a lot of love into supporting the TAG and we have grown and it's really great to see more and more people joining us and also joining on the activities that we are doing. And kind of the main mission of this group is to raise focus and raise awareness about the importance of sustainability in the cloud native landscape.

Like what is the current state of that?

What kind of challenges we have and how can we help both the CNCF landscape, the projects there, but also the companies that are utilizing those projects that are running in cloud, be it public cloud or private cloud, are running in a cloud native manner, how can we help them get the sustainability of their systems and software better, basically?

Chris Adams: Okay. I'm somewhat aware of the TAG ENV'S work. I remember that, I think, last week, there was this, last, towards the end of last year, there was a sustainability week with a bunch of online talks by various people presenting, yeah, and we'll share a link to that, and I know there's a couple of other projects that we're going to talk about in a bit more detail, and you've mentioned this idea of, well, what is a state of the art, how do you make some of this visible to people, and you name checked some things like observability.

Are there any kind of particular projects that you're particularly excited about, or you might be seeing kind of repurposed, because you, I believe you mentioned one project, and I think in July we had Niki and, Niki and Ross, who were also part of the TAG at the time, talking about some of the work in making carbon emissions more, more, more observable and visible to people.

Maybe you could talk a little bit about that, because I think that's one thing that you've mentioned to me that you're quite excited about.

Kristina Devochko: Yeah, absolutely. And Niki and Ross, it's great that they have been on the podcast because I know that they have been talking also about Kepler, which I also wanted to highlight in this episode as well. And they are also driving now the kind of subgroup in our Environmental Sustainability TAG that also has a separate project, which I also would like to talk a bit more about afterwards.

But like the first CNCF project that I would like to highlight that kind of touches upon the observability piece in context of measuring, like, the sustainability of your, of your system. And that is Kepler. And this, this project has now, for a few months ago, I think, entered the CNCF landscape as a sandbox project, so that's kind of a big deal for the whole project and everyone who was supporting it. And for those of you who are listening in and haven't heard about Kepler, it's the short name for Kubernetes-based Efficient Power Level Exporter.

So that. sounds like a very complex name, but that actually makes meaning. So that's a word with the meaning behind it. So this project, its main goal is to measure energy consumption so that this data can be gathered, collected, and afterwards you could feed it to the machine learning models that can perform a specific analysis on that power usage utilization data. And then you could visualize that. And by visualizing that over time, you could also understand how efficiently your resources, your power is being used and what kind of optimizations you can make based on that. So you could kind of...

This could help you make more informed choices on, in terms of optimizing your resource usage.

Chris Adams: So there's a couple of things I just want, so I just want to check if I, check my understanding and also for other listeners on this. So there's a tool called Kepler, and because measuring power usage inside the cloud can be quite challenging at times, this is essentially an open source tool that goes some of the way to looking to making that more accessible and observable to people who are responsible for, like, operating clusters of computers and things like that.

And, if I understand it correctly, it's using what was the kind of hip and trendy software, like, Extended Berkeley's Packet Filters. It's using something quite close to the metal, so it doesn't actually slow down the system to report information as much as other things. Or, at least, that's one of the considerations that people have been taking some steps for.

Is that correct?

Kristina Devochko: Yeah, you're correct. And I think an important piece to mention here, like coming on to your point that it's not that easy, necessarily, to gather this type of metrics for power consumption. Like if you think about bare metal, that type of data can be more, in a more easier manner gathered because it is available directly from the hardware when you're running on bare metal, but when it comes to cloud providers, or like when you're running on virtual machines, this, there is no support in virtual machines to be able to make these types of metrics available.

So there, that's why it may be challenging for example to get 100 percent accuracy of running Kepler on, on managed Kubernetes service. And to just make a notion of that, Kepler is mainly targeting the Kubernetes-specific workload. So when you're running Kubernetes clusters, be it on bare metal or be it in, as a managed Kubernetes service, for example, in public cloud. And like you mentioned, it also uses BPF to gather some of that specific metrics specifically that would be specifically useful in, in public cloud. But we would link a blog post as well that I would recommend to check out because it goes in more very technical details around the different deployment models and architecture for Kepler because they have, they are currently working on a specific deployment model that I really hope we will get to see public cloud providers collaborating with Kepler project on, which would potentially allow to not use a pre-trained model with some kind of pre, pre tested, yeah.

Pre, there is like a data set that was based on some of the other data that the Kepler community has collected, for example, from running on bare metal.

And it does make some assumptions based from that. So it provides some pre-trained power models that you could use in public cloud to get somewhat close to reality type of data, but still, for example, things like idle power, you will not get that information or that metrics from Kepler because there is no way for the tool knowing about how many VMs are running on the host when it comes to public cloud.

Chris Adams: Oh, I see.

Kristina Devochko: There, that's kind of the, there are some limitations there and this blog post goes very nicely into those details. But the deployment mode that they're working on, that would allow you to install Kepler on the host first, that public cloud providers could do. They would install Kepler on the host first, that would gather that hardware specific metrics for power consumption.

And then you would kind of have a layer.

Chris Adams: The visibility at that point, rather than like, you're inside the virtual machine guessing how many other neighbors are also using your physical machine, you're actually getting the physical machine saying, "yeah, you actually have 10 neighbors and six of them are mining Bitcoin."

Or they wouldn't be doing that. But like, you get the general idea. I'm not sure if you're allowed to do that in some, in a lot of clouds. Okay. I'm glad you mentioned that.

Kristina Devochko: Hmm. Yeah. So that would require some collaboration with public cloud providers since they have control of the hardware. But then in that case, you would kind of install Kepler twice. You would install it on the host and you would install it in the Kubernetes cluster. But then by doing that, cloud providers, maybe by making Kepler data from their hosts available as an add-on on, yeah.

Chris Adams: Service you could then subscribe to.

Kristina Devochko: So you could get that data. Yeah.

So you could get that data and you could get an even more, more accuracy on that power consumption metric. So I really hope that the adoption of the project takes off and we get to see it available in the managed Kubernetes services in public cloud, for example. So i, it's, it looks really promising, to say least.

Chris Adams: I'm glad you mention that, because there's one project inside the GSF, this is the Green Software Foundation for other people, called the Realtime Cloud Project, which is currently led by, amongst others, Adrian Cockcroft, formerly VP of AWS, and there's people from Microsoft and also Amazon who are working to essentially do the carbon part if, if things like Kepler are actually exposing some of this.

And for the nerds who are on this, listening on this podcast, I'm going to ask for your help. Because one of the reasons that's cited for not sharing this information is there's a very particular kind of attack that you can use if you have direct energy emissions being exposed at a very high resolution.

You can find out what programs are running or even some information like that. So there are reasons cited for not sharing this information. There's a whole line between zero knowledge and letting everyone get hacked and like the, the research that we've seen or that's been shared inside there is that around the minute resolution, that's still enough for operators like yourself to kind of like tune and manage carbon, but also is something that still mitigates against most of these attacks.

And I do forget the name of the animal that the attack is named after, but if you're listening to this and you submit a PR, I'll be very grateful for this because it's got a cool name. It really does. But I'm totally blanking on this. If you're curious about this as well, we did actually do a podcast in July last year with both Ross Fairbanks of Flat Peak and Niki...

I can never pronounce her surname. Niki, I'm so sorry. Niki, she works at Grafana and, Manoladeki, I believe. So that's the people. And we'll share a link to that podcast, which dives into a bit more detail about some of that. Okay, so we spoke about that. And that's one of the wider projects that has some application clearly inside this.

But there's maybe some projects, there's a, well, there's one or two projects inside the TAG ENV that you're also involved in, that you said that you'd like to kind of talk a little about. Maybe if we give you a bit of space to mention one of those, perhaps.

Kristina Devochko: Yeah, of course. So like Kepler and other projects that are coming out that are related to sustainability, we support them as a technical advisory group. But we also are looking for ways we can also contribute by starting some of the projects inside the TAG. And we have a few like content focus projects, like the landscape document that Kind of covers the state of sustainability in the cloud native space that we are working right now on creating a version two for. And we have recently published the glossary for cloud native sustainability glossary that could help clarify some of those specific terms. But when it comes to more technical contributions, I wanted to highlight the project that we are working on in the subgroup of the TAG that is called Green Reviews, so it's a working group that is run by Nicky, Antonio, Antonio DeRosso, which is one of our TAG contributors and now is his co chair in the group, and Ross Fairbanks as well, that is the technical lead for that group. And what we are working on in that group is that we are building a workflow that can be used to target the projects in the CNCF landscape, like Kepler for like, not like Kepler, but the other projects that you would be using, for example, Kubernetes, Kubernetes, I think would be a better suggestion in this case, because the workflow actually uses Kepler together, some of the, of those metrics.

So this workflow would then be connected towards those CNCF projects that will be running under load and so that we could simulate a load on kind of the application itself so that we could gather the sustainability specific power and resource utilization specific metrics over time so that we and that workflow could analyze the data and publish information about the sustainability posture of that project.

And this statistics can then be publicly available for all the projects in the CNCF landscape so that over time, the project maintainers and project contributors could look into the states of their projects from the sustainability side and improve the resource utilization of those projects over time, make them more resource efficient, which also is one of the goals for Kepler projects, for example.

Find those bottlenecks that, find those ways to improve and make those projects more lightweight and more resource efficient. So this is also something that is open for anyone to contribute. So if you like to code, you could just join and pick an issue and, you know, start helping out.

So if you would like Chris, you're also welcome to join.

Chris Adams: Maybe some, there may be some things we look into a little bit later on. So, if I understand that correctly, there's a couple of things you mentioned, and you use this term sustainability posture of a project. I'm taking that to mean like, what the kind of profile might be like, where, under what, so how it might perform under certain circumstances and what in certain places it's, is it more efficient here or less efficient there, is that what you mean when you say that?

So, the idea, you get an idea of where there might be common areas for improvement across the whole portfolio of projects, for example, based on some of the real world data. Is that the thinking behind it?

Kristina Devochko: Yeah, we are like still in very early phases. So this working group has been like a few months old. So the piece, for example, of what kind of methodologies we would use to calculate that, that kind of sustainability posture, how efficient a project is, we have still not 100 percent defined that. So I think we want to start like simple by just gathering some of the Metrics like the SRE specific metrics, you know, like CPU, memory usage, maybe use, use the Kepler specific power consumption metrics.

Start there. And then the next step would be to see what other metrics we would need, or those metrics that we have collected by now, should we use as, the Software Carbon Intensity Specification, should we use that in combination with something else? Should we use something like Impact Framework Engine, right?

From GSF. So we have been looking into that. There are some discussions around if we should use, for example, SCI as a Software Carbon Intensity methodology.

Chris Adams: That's one way of measuring the basic, it's a bit like, a little bit like PUE for data centers. It's like the amount of emissions associated, a kind of rate, as a software. Okay.

Kristina Devochko: So that we could provide some of that information, like you say, that we could provide, like how much power has been used, if we could correlate that to the amount of carbon emissions, maybe water consumption at some point, because this is also becoming very important these days with enhancements in artificial intelligence and machine learning.

So we're still figuring that out. So I don't have an exact answer for how exactly it will look like, but this is an opportunity for anyone also from... Yeah.

Chris Adams: Refer to some of the existing state of the art. Okay, that's cool. For folks who were interested in listening along to this, so, Kristina, what you've actually described might make you think of an episode that we did with Arne from Green Coding Berlin. We've interviewed him as well.

He spoke about some of this in a bit more detail. We should share a link to that because he dives into very deep amounts of data for this and also his organization has been sharing some really interesting stuff about the difficulties of tracking some of this stuff on the cloud. Because, you know, one of the, while the cloud can be extremely convenient, there are knock-on effects on basically having an amorphous blob of compute that you kind of tap into, rather than having a direct machine that you can direct measure directly.

All right, great, and I'm really glad you mentioned the glossary and some of the other things you had, because one thing that I found really helpful when helping other people actually to talk about something for the first time is having this stuff saying, "well, this means this," or even just having the landscape with you seeing that, well, "wow, there's actually a really wide range of projects where the sustainability aspects do touch on a bunch of these things."

So, thank you for mentioning those, actually. I should probably ask you now on relating to that. We spoke about, like, TAG ENV. And we spoke about some of the projects that are ongoing, but it might be useful to talk a little bit about how you folks organize and how people can get involved, because I was able to join the Slack and chat to a few people to kind of more get a kind of feel for it, but I figure it might be useful for other people to realize that it is actually quite easy, and this is something that you've invested a bit of time in to make accessible to people, and well, you're here, so I should, I guess I should ask you really.

Kristina Devochko: Yeah, I appreciate you asking that because we are always looking for ways to communicate to the other community members that it is not that scary and difficult as it may seem to start contributing to some of these groups and organizations. So in the TAG, it's pretty, I think it's quite simply structured.

So of course we have some of the chairs of the TAG, and we have also tech leads that kind of overview the different types of activities in the TAG and in subgroups are done in accordance with our mission and our goals and contribute in that area. But it is open for anyone to join. So we don't have necessarily like a membership or anything. So everyone can just join our slack our regular meetings we have both meetings for the TAG in itself, which are bi-weekly, and the working groups-specific meetings as well. And anyone can just join and start asking questions, participating in discussions, you can go to our GitHub repository and in the issues filter on 'help wanted' or 'good first issue' labels.

And then you could see if there is something that resonates with you, or you could just start by contributing to the existing discussions in those issues. You could contribute content. So if there is a specific topic that you would like to write a blog post on when it comes to cloud native sustainability, you could just submit that, and then we will help you to get it there, to get it on our website, to get it on the CNCF blog. So there are quite a few ways you could just start. And even if, yeah, and even if you feel like, it feels a bit scary, you are very much welcome to reach out to me. We could probably share some contact info, or just go on the Slack and send me a message if you need some guidance on how to join us.

And we have a separate blog post that we recently wrote.

Step by step guide.

Chris Adams: Like how to take your... okay, well you heard it here first, you have a direct offer from one of the members to help you in if you're curious about doing this. This is one thing I actually quite admire about the CNCF. With the Green Software Foundation we, while it's a membership organization, it can feel a little bit difficult to get in, and this is one thing that I've been really impressed by.

And I'm aware that yes, there are all these weekly calls and there's things where it's very easy to see what's going on if you're remote, for example. But as I understand it, you do a fair few things in Oslo as well for like people who like to meet up and physically share the same physical space as other people sometimes, like doing meetups as well.

Maybe you might want to just briefly touch on that before, because I know this is one of the first things we have coming up in 2024 that you mentioned actually.

Kristina Devochko: Yeah, that's true. And like, like you mentioned with the Green Software Foundation, I, when I first started learning more about it, I was like, "Oh yeah, I would like to become a member." And then I realized that my company was not part of that yet. So it was not, not that easy, but still, you, you of course have some opportunities to just follow and participate in discussions.

But what I also liked when I saw that GSF started with local meetups, local meetup groups and supporting that initiative. And then when I checked, there was no one, no such meetup group in Norway. So it was open for anyone to just start one under the GSF umbrella. So in September last year, I just asked if I can do that.

And then we started a group, Green Software Foundation Oslo Meetup Group, basically, which will, I hope can become an arena for the, to grow and strengthen the local community of technologists who are passionate about the topics of green software and green coding in general. And we had one meetup last year to launch the group in October and hopefully can have it on quarterly basis.

So now the next meetup coming up is in, in February, and we'll have some nice topics about the impact of AI and machine learning on sustainability and also the adoption of Cloud Carbon Footprint, open source tool in one of the Norwegian companies called ODA, and I believe one of the recent episodes was precisely on that topic, wasn't it?

Chris Adams: No one admits to using it, but it's basically underpinning so much of all this stuff. Yeah. That's really, I'm glad, I didn't actually know that Oda was actually doing that kind of work. And it's quite nice to hear that, yeah, it shows up in various places, because I, I really enjoyed chatting to, chatting to the guys last, for the last episode, and nerding out about like Legend of Zelda, if nothing else.

That was of

the

call

Kristina Devochko: yeah.

Chris Adams: was some of it. Okay, so we've shared a link to the Oslo meetup group, so people can find out about that and when that's taking place. I believe that's open to anyone who's physically in Oslo. You don't need to be a member of anything like that, you just need to be interested along those lines.

I should probably, at this point here, just give people a heads up that if you're not in Oslo, and you're not on remote event, and you're maybe organizing events, it's worth knowing that there is actually a directory of potential speakers at speakers.greensoftware.foundation. This is one place where, if you're running an event, and you're looking for someone who can contribute some expertise, or is able to kind of help with it then, that's one resource.

And also, I believe that you've shared a link here, which is run from the CNCF, which basically has a listing of other events coming up as well. Is that the case?

Kristina Devochko: Yeah. On the website for the TAG ENV, we have a separate events section and currently we are working on adding, implementing some automation because we have the tool that was donated by some of the community members so that we could use to scrape the data about different sustainability related conferences, sessions, meetups, and then we could continuously update that events page.

So hopefully there will be coming out there automatically in not too long. So you could check that one out as well.

Chris Adams: That sounds cool. I can't believe in 2024 we still don't have a kind of, like, solved problem. Like, we haven't solved the problem of events yet, like finding out when they're coming up. Because this is something I really struggle with, and I'm glad that you have that mentioned. And I think you just said something kind of cryptic but interesting there. So there was a Cloud Native Sustainability Week in October, and I will happily admit on air that I basically plundered that place for all these videos and people to speak to for future shows.

And we've got one or two of the speakers who've been presenting there talking about some really deep dives. We've got, we've got some of those episodes lined up. You're planning one for 2024 as well. Is that likely to be around the same time, like October-ish?

Kristina Devochko: Yeah, I hope so. I, we will need to see if this is the date we should go for. We haven't decided on the date yet, but we have seen that it has been a success. It was the first time in 2023 that we decided to do it. So we were not sure how it would work out, but actually, despite the virtual mini conference that we had like a two hour event with some speakers presenting virtually, we also had like, I think we were around 20 plus local meetups that were, we calculated that it was happening in 17 countries across four continents.

So we think that it has been quite a success. So we hope we could do it on an annual basis. And now we have just started planning for the Cloud Native Sustainability Week in 2024. So if you or any of the listeners would like to contribute, it's totally open. And we have a tracking issue in the repository for that as well.

Yeah.

Chris Adams: you for that, Kristina. We'll share a link to the last one because there was really, I actually filed an issue in the TAG because I was like, "hi, I missed all the talks because I was in the wrong time zone." Or moreover, I might have been asleep at the time or something like that. But and then I think within two or three days, I had someone basically show like here's a list on YouTube of every single talk with links back to the slides and everything like that. It was so, so nice to see that. And there was some fantastic content. I was really impressed by that. So yeah.

Kristina Devochko: Yeah, it was really good, I agree.

Chris Adams: Oh, we're talking about events and I almost forgot. I should mention that there is, there's a quick announcement I kind of have to share as part of like me working in the GSF.

There is an event coming up later in this year called Carbon Hack 24. This is the Green Software Foundation's kind of global event, basically. Essentially, the idea is that it's a little bit like what Carbon Hack was like last year. So it's a week's long kind of hackathon kind of thing. This time, the focus is around a piece of software I believe you mentioned called the Impact Framework.

This is an idea which is a bit like something like a kind of manifest file or an executable manifest file for us, for people to kind of understand and measure the impacts of software. The idea would be that there's this piece of work that the GSF has been working on called Impact Framework, and the idea is a bit of a hackathon around something like that.

And at the, right now, there, we often talk about sustainability in terms of carbon only, but Kristina, you mentioned water as one, one possible dimension. And there's a number of other dimensions that we've actually spoken about as well, which are also fair game for exposing or looking into and things like that.

So that's one thing coming up. And I should say, it's online. It starts on the 18th of March and ends on the 8th of April. You don't need to stay awake for that entire time, surviving on Red Bull and chocolate. That's not a good idea. But the idea is that there's space to make it kind of accessible to people regardless of where you are in the world.

And if you go to 0hack.greensoftware.foundation, then people can see and learn all about that. And the only thing to bear in mind is that the registration is the 22nd of January. So there's a, it will need to move relatively quickly on that. Okay, there's a, there are a series of awards for that, that we'll be referring to.

And yep, I think that's the plug that I've done while we were talking about events. So thank you for bearing with me for that, Kristina.

Kristina...

Kristina Devochko: Of course, I'm very excited for that. I'm very excited for the hackathon and it's cool to see that it's not just a one day, one day, 24 hours type of activity.

Chris Adams: Here's my free idea that I'm unable, that I would like to work on, but I don't want to promise myself that I'll do it, because that's, I'm getting older, I'm not sure how much time I have, but I know there's a thing called Node-RED, I want there to be Node Green, to use some of the ideas behind Node-RED to create a visual representation of all of the inputs of data that you might have in, so you can work out some of this, because when we talk about this kind of stuff, it can be a bit hard to understand where information about carbon intensity might be coming from or where, like you've described utilization or how hard a machine is working is coming from.

And I think if there's a visual way to present that, that would be useful. And if there's absolute precedent of things like Node-RED being used in all these different places. So that's like kind of my lukewarm take, I suppose. Alright, Kristina. Thank you so much for spending the time to talk with us.

I really enjoy, appreciate you coming on and talking all about the TAG ENV and how people can get involved. And yeah, this has been really fun. Thank you for giving us your time and talking about this. This has been good.

Kristina Devochko: Thank you, Chris. It's been a great discussion. It's, it's been fun. So thank you for inviting me. It's been a pleasure. So I hope some of you would be listening in to this episode, would be interested in joining us and don't hesitate to reach out if you're not sure about anything.

Chris Adams: That's a really good point. Just before we close off, we should, if people are interested in the work that you're doing, either personally or the actual TAG ENV ,what's the best, what should people be typing into their search bars, for example, just to learn about your work or learn about the CNCF's environmental work?

Kristina Devochko: Yeah, I think that if you would like to get in touch with me, you could probably just type my name, Kristina Devochko, and on LinkedIn, normally I use most, mostly LinkedIn, and then I have a separate technical blog where I write some technical content on those different topics, kristhecodingunicorn.com.

And if you would like to join the Environmental Sustainability TAG, you could just, I hope we will add the links to the website and to the repo, but we are also at the CNCF Slack. So if you join that, you could search for a channel called TAG-environmental-sustainability, and we'll warmly welcome you there.

Chris Adams: Brilliant. Thank you so much. I'm also really glad you mentioned Kris, the Coding Unicorn, because although this is an audio podcast, you need to Imagine that behind Kris there is a neon sign saying, Kris, the coding unicorn. And that's, it's... That's all I've been able to see or look at when on this conversation, so I'm really glad you mentioned that.

Kristina Devochko: Almost like product placement.

Chris Adams: Yeah. Okay. Well Kristina, thank you very much for this and hopefully you stay warm and cozy for the rest of the day. Take care of yourself.

Kristina Devochko: Thank you, Chris. Thanks everyone.

Chris Adams: Okay, bye.

Kristina Devochko: Bye.

Chris Skipper: Hey everybody, this is Chris, the producer of Environment Variables, just butting in to tell you about an additional resource that we have for the upcoming Hackathon 2024. Join us every Monday at 2:30pm GMT for our regular live stream, which explains how the IMPACT framework works and shares hack project ideas.

You can visit hack.greensoftware.foundation to find out more about that and sign up for both the live stream and the Hackathon. That's all for now, see you next time.

Chris Adams: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again, and see you in the next episode.

View Details

Asim Hussain is joined by guests Srini Rakhunathan and Navveen Balani, the technical leads on the Impact Framework. They delve into how this innovative tool effectively models, measures, simulates, and monitors the environmental impacts of software across various platforms. The conversation explores the framework's unique ability to handle diverse environments, from cloud systems to mobile devices, with an emphasis on the practicality and necessity of measuring software emissions accurately. Highlights include intriguing insights into integrating the Impact Framework with SCI Open Data and the future of green software development. This episode is packed with valuable information and thought-provoking discussions that offer a glimpse into the future of sustainable software.

Learn more about our people:
* Asim Hussain: LinkedIn / Twitter * Navveen Balani: LinkedIn * Srini Rakhunathan: LinkedIn

Topics:* The Impact Framework | GSF [3:00]

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

Events:* Carbon Hack 24 | Online | 26th Feb to 15th March [40:08]

Resources:* The Software Carbon Intensity Specification | GSF [3:44] * CarbonQL | CarbonQL [09:19] * Joseph Cook | Project Lead on IF [13:43] * Kubernetes [16:45] * Node.js [17:13] * Cloud Carbon Footprint | Thoughtworks [21:18] * Boavizta [21:32] * Azure Functions [23:29] * Cloud Instance Metadata Model [25:22] * Teads Curve | Benjamin Davy of Teads [26:12]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
That simplification that you can just download the code. You need to know a little bit of Node.js or Yarn or how to use it to just be able to run it. As long as you are able to do that, you're pretty much up and ready. Maybe we can even set up a timer, Asim, how long it takes for someone to run it. I bet it will not be more than five minutes.

Asim Hussain: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host, Asim Hussain.

Welcome back to Environment Variables, the podcast that covers just about everything to do with sustainable software development. I'm your host, Asim Hussain. I'm the executive director of the Green Software Foundation here to navigate you through the evolving landscape of green software. In today's episode, we've got a special segment lined up to you, joining us are Srini Rakhunathan and Navveen Balani, the brilliant minds leading the project on a much anticipated Impact Framework from the Green Software Foundation. They're here to give us an insider's view of this revolutionary tool designed to model, measure, and simulate and monitor the environmental impacts of software. From cloud environments to your mobile devices, the Impact Framework is set to redefine how we understand and reduce the carbon footprint of our digital world. Before we dive in, let me introduce my esteemed guests and colleagues for this episode of Environment Variables. Navveen, how about, let's start off with you, please.

Navveen Balani: Yeah, thank you, Asim. Hello, everyone. I'm Navveen Balani. I'm Managing Director and Chief Technologist with Technology Sustainability Innovation Group at Accenture working on the intersection of technology and sustainability, and an active member of Green Software Foundation from its inception. Happy to be here and be part of this podcast.

Asim Hussain: Thank you, Navveen. And we also have Srini. Srini, do you want to give an introduction to yourself?

Srinivasan Rakhunathan: Definitely. Thanks, Asim. And wonderful to see you again, Navveen. I'm Srini. I'm part of Microsoft's cloud sustainability team, and I am a senior program manager. I work on sustainable hardware, and as part of Green Software Foundation, I got an opportunity to work on sustainable software with this amazing team.

So glad to be part of this call and happy to help.

Asim Hussain: Before we dive in, just a reminder that everything we talk about will be linked in the show notes below the episode. So I've got a couple of questions that maybe we can go through, but I actually thought, we were having a chat before that, I actually thought it might be interesting for everybody to understand the journey of Impact Framework, because that might actually help people understand what it even is.

I struggle to even explain. I think that's one of the, one of the things I want to chat to you all about is like, how do you even talk about Impact Framework to others? Because I, it can be so many different things to so many different people. It's a little bit challenging. But, yeah. I thought it might be interesting to talk about, you know, the early days, like years and years ago. And I remember, this is how I remember it. So I remember it as: we were all working on the Software Carbon Intensity Specification together, getting really deep and diving into a lot of that stuff, and then we knew we needed to start actually using the SCI and writing case studies. Srini, I believe you were the first person in the entire world to have written a case study on the SCI.

You did it with the MST, FTE shop on sample one. And that was a wonderful moment. I remember that. And then a little bit later, Navveen, you wrote like a very detailed one with kind of a larger case study with, I think, an Accenture use case. Yeah. I don't know. Let's just start off there. Like, what did you guys like, do you remember much about that time?

Like, what were you thinking? Like, what was, what were the challenges I'd say that you had when you were implementing and trying to write some of those case studies, do you remember? You were the first people in the world, almost, who would like actually bother to measure software.

Srinivasan Rakhunathan: You know, it almost seems like, you know, you were on a journey for which you didn't know where to start or where to end. And that's how I used to think when I did that case study, because there was no reference material. There was no guidance. There was no, you know, right or wrong, right? We had multiple discussions with this forum and the extended forum pouring over the calculations again, again, and again, to even figure out whether we are doing the right thing or the wrong thing. So yeah, very, um, anecdotal, Asim, that you're talking about how we started off. I remember there was this SCI data project, SCI guide project. We knew that we were looking for something, but in parallel, we were building these case studies, it's almost seems magical today that we are at this place today.

Asim Hussain: That's true. I remember one moment, you just, we were getting really deep into trying to figure out the carbon emissions of networking. That was one of the things I remember that we're getting really deep into trying to figure that out. And we were, you were looking at energy expenditure of bits across a network and trying to estimate the carbon intensity and of the embodied carbon that was being used when you're transmitting data.

And I think eventually we just landed on using a coefficient of like gigabytes per, you know, carbon per gigabyte that we got from some source. I remember like that, there was all of trying to figure all of that out. Yeah, we'd had, you're right, there was all those, like, hard won lessons that we've kind of also forgotten about these days as well. Navveen, what do you remember about when you were writing your case study? What was the hardest challenge that you had when you wrote your case study?

Navveen Balani: So I think going back, I think the fundamental challenge that we faced was around data and particularly around whether the data is authentic enough, right, for measurement. Now that's a, that is a problem to solve at that point of time. So, what we did was, why not go with approximations, coefficients, so at least unblock us from a data perspective. And once we have the data sorted out, I think next was around energy calculations, measurements. And since we are all deploying on cloud, right, most of the applications are running on cloud. At that point of time, uh, a lot of these data was transparent to us, right? So whether it's watching machine, choice of processors. So how do you even get to the power emissions and then calculate energy? So I think it's a journey. We went through the data challenges. We went through the vendor challenges. We then we a lot of reference material, which we use. And I would say finally we then had projects like the SCI guide that we wrote, which provided instructions on how can you go about doing a calculation.

We started off with the ontology project where we thought, okay, we'll give them a model representation of your software boundary, then maybe do a one click and then calculate the SCI score. So a lot of these thinking projects finally landed up in the Impact Framework. I think it's been a journey over the last couple of years, right?

And now, yes, at least we have, we are working towards a mature product or an API, right? Which can help enable any developer, right, to calculate SCI based on their boundary.

Asim Hussain: you're right. I think it basically came around, this is, it basically came around, you actually were, with pen and paper, in its rawest form, trying to calculate the missions of some software, you realize that data was the biggest problem. So then we launched like the data project. And I remember the first thinking we had was like, we, maybe we need to go and create some datasets, but I remember when you guys were starting to investigate this stuff, you were saying like, actually, you know, these datasets already exist, it's not a case of like creating a dataset, it's like we're not even too sure which data sets to use for which contexts. So then you wrote the SCI guide, which then became the "if you want to measure this type of information, use this data set and use it in this way, or use this equation and use it in this way." And so then that evolved to, well, now that's just some text on a page, how do we programmatically help people to actually calculate this stuff in, in a, you know, more scalable way, rather than just giving them content. Navveen, you started to look at this ontology project, which I still, SciOntology, I still love that name. We should have run something with it, but that was all about, like, how do you figure out what it is you're going to measure? That is, that was trying to answer the question, "what is an application?" Like, what are you including?

What are you not including in an application? And then like Srini, you and I were talking about this old project called CarbonQL. And what that was trying to do was trying to create like an API where you could ask this API, like anything. Like I have like. Remember we even came up with like a key format.

If you remember, I'm looking at a server, I'm looking at a server of this type. I'm looking at a server of this type on this cloud. I'm looking at it. So you came up with this, like you could request anything from this API and it was like a facade or something, and it had lots of code we had to just figure out all this logic and come back in with an API. And I can't remember exactly how we got from there to like a YAML file and an Impact Framework that may be lost in time. But we evolved from kind of an API to realizing, actually, this is just not something that we could ever do. It's too big as an API. It's like, it's enormous. It's like, how do you measure everything in the world with one API? So we said, actually, this is software that you're going to write. And then we started talking about that. And I don't know, then we just lost in a whole load of a year's worth of conversations, and then we evolved into where we are right now, which is, how would you describe, let me ask you this question.

This is an interesting question for me. I'm going to ask Srini first. When someone asks you, what is the Impact Framework? How'd you respond? Like, what'd you say to them?

Srinivasan Rakhunathan: So, and this question has been asked many times by my engineering team when I have presented, how do we, you know, they try to push through my agenda of having Impact Framework. And I'm trying to do that more and more with the projects that I handle. The key difference, the key USP of Impact Framework is this is by developers and this is for measurement of your development efficiency, development processes, code, as opposed to what we had prior, which was focused on, you know, what are the standards governing emissions?

What are the reporting? What is GSG saying? What is X? You know, this is a star contrast where you're trying to do something that is going to help developers measure emissions from their day to day code, day to day, you know, CICD pipelines. So that's, that resonates, uh, with most of the developers when we talk to them.

And they're more curious, you know, uh, I think, like, one of the things that we also talked about, all of us, is to, how do we make it granular such that the measurement is easy. So developers don't just need the final emission number, they need to know what you did to come to that number. They will not accept, you know, just something that you give to them on a piece of paper.

So I think that is the USP of Impact Framework for me.

Asim Hussain: Like debugging the carbon emissions of your application is giving you that, you need that granularity. So, you know, like someone just doesn't give you like, "Oh, my carbon score is eight." And you're like, "okay, good. What do I do with that?" It's all of the workings out underneath. And I'm, and I thought it was really fascinating because we had an organization come on our last call, didn't we?

And they showed us their manifest file, which is like 13 megabytes large. So they really went granular and it still only ran in like 20 seconds. I was really impressed with that actually. So Navveen, like, how do you describe Impact Framework to, to whoever you need to describe it to.

Navveen Balani: So, so I described as, as Impact Framework. It's probably a framework that helps you realize the SCI Specification. Uh, and what it means is it helps you basically come up with an SCI score based on, uh, your software boundary. As Srini mentioned, right, it's basically a developer framework that can be used for measuring any software application. And I would even say it's a vendor-neutral framework where you can plug and play your own models or use open source models to come up with a measurement and finally arrive at an SCI score.

Asim Hussain: Yeah, I like that. I forgot. Like, yeah, we, you, you, you're the one that kind of, I remember and the calls like would, was gently nudging us back into like focusing on the SCI, which we, I suppose at that point we kind of got lost in some conversations, but that really focused the, the whole team again quite a few months ago. Do you know, I won't give my definition. I'll actually give a definition that Joseph gave me yesterday in a call that we had. Joseph's the PM for the project. And he described in a very interesting way. He said he's now thinking of it as an executable audit for a software application. And I thought that was a really interesting term, isn't it? An audit, like that manifest file that we're creating is like an audit. And the term executable is like, again, as you're saying, Srini, it's not the final number.

It's like this whole thing that you can re-execute and readjust and value. I think it's been coming up a lot. 'Cause everybody's asking me what is Impact Framework and we're constantly trying to come up with a language for it.

And I just want to maybe just acknowledge the fact that we've come up with something very different. We're kind of like setting like a paradigm here and that's why we're struggling so much to explain to everybody what Impact Framework is. And I'm very excited about that because I think that's when you really change things. We can't even really explain what it is right now. We can only tell you that anybody who gets involved gets really involved and they can really see themselves in it. It's our most popular project in the foundation right now. And when I talk to people externally, there's just a lot of interest in it.

And I'm, and I'm just so excited about it. Should I move on to the questions? I've got some questions. Yeah, should we go ahead? Okay. So here's the first question. So can you explain how the Impact Framework simplifies the process of estimating energy and carbon impact for various applications? So pretty broad question.

So can you explain how the Impact Framework simplifies the process of estimating energy and carbon impact for various applications? Hang on, let me ask this question. Does it simplify? Maybe 'simplify' isn't the right term for what it does. It's quite complicated, isn't it? Maybe it kind of surfaces information in a different way. This is one way of describing a framework. It takes observations about a running system and turns them into impacts. So that's one way. It takes observations about a running system and takes them into impacts. So I suppose one way it simplifies it is if you've got something you are already observing about your running application, like CPUtilization or something else. It can help you then turn that into energy. So that's one way it simplifies it. One other thing that, this is one of the misconceptions people have about Impact Framework when I talk to them about it, is they think it's something that you have to install on every one of your servers, right? Cause that's how most of the things that measure energy work.

They're like, okay, Impact Framework. So how do I install it on my GCP servers or my Azure servers? And I'm like, well, you don't, you just. You know, you just have to tell us what the utilization was of each of your machines and each of your processes and Impact Framework will try and convert that into energy.

So I think that's one way maybe you could say it simplifies it. You don't have to install anything at all?

Srinivasan Rakhunathan: I think so.

And, uh, when you use the word 'simplify,' Asim, to me, the very fact it's a command line utility, it's a huge bonus, right? You don't have to spin up Kubernetes clusters. You don't have to spin up Spring Boot services. You know, you don't have to host it on an API. You don't need an infrastructure for all that, you know, you can

Asim Hussain: You don't need to instrument any of your applications or code or anything. It's just, yeah. It's just like observing. It's

just looking at it. Yeah.

Srinivasan Rakhunathan: Exactly. so, so to me that simplification that you can just download the code, you need to know a little bit of Node.js or Yarn or how to use it to just be able to run it. As long as you're able to do that, you're pretty much up and ready. Maybe you, we can even set up a timer Asim how long it takes for someone to run it.

I bet it'll not be more than five minutes. You know,

Asim Hussain: I don't think so. I don't think so. To get the simple, like hello world version of it out with like, yes, sampled, maybe it's use it with your own data. It will take a little bit more time, but to like use it with a sample data, I think five minutes is absolutely yeah. Any thoughts, Navveen, or how, like anything you want to add to that?

Navveen Balani: So I would also say that it simplifies, I mean, if you're a beginner who wants to do software Carbon Emission Measurement, then, I mean, this API, I mean, the turnaround time for basically measuring, let's say, a virtual machine is, uh, maybe a few hours, right? Just going through the API, uh, setting things up. So the barrier to measurement, uh, I think is quite simplified. Given our history, right, where at least we took maybe a month or two months, right, just to go through the entire data capture process, which model to use, right? So all those knowledge, I would say, is accumulated in this tool, right? So the entry point to SCI now is drastically reduced.

Asim Hussain: I remember that being, I remember that was one of the, one of our original kind of design, I don't know if that's a term design decisions or requirements of the tool was to codify the expertise that was in like both of your heads and in the heads of other people, like the very small set of people who've been looking at this to make it easier, because now all you have to do is you just have to like plug in a utilization value, pick a model or a set of models, and it will like compute all that for you instead of like, "which coefficient should I use, which this, which that?" Is kind of all baked into these models. Talking of models, we call them plugins now, don't we? Sorry. We call them plugins now, which I'm having some name changes. So I remember I was chatting the other day.

We originally had this way of thinking, which is we know we need to capture some observations about our running system, be it utilization of virtual machines or billing data or whatever it is, some observations we have. And we always knew we were going to pass it through some sort of model to create some sort of impact, like energy or, or, or whatever. Then at some point we realized it's not, one model isn't going to work. We're going to have to break it out into lots of, and that was a very important decision that we made. I feel like that was like an inflection point. And there was a moment when we were like thinking about this thing in terms of one model rules them all, to hundreds of thousands of models that you can like combine in this kind of Linux piped command line process. I think that was a real breakthrough moment in the project. I think it was something about, were we trying to compare Boavizta, Cloud Carbon Footprint and Teads and these other models together?

Was that what it was? I can't remember what even triggered

Srinivasan Rakhunathan: I'm, I'm also trying to think.

Asim Hussain: Yeah, I think it was something to do with that because CCF did a lot. Oh, I can't remember. Anyway, what are some of, what are some of your favorite models? I was going to ask, like, what are some of your favorite plugins? Or, yeah, like pipeline plugins. I do remember the moment, actually, I think this is quite important, actually, as well, like, when what once we finally had this ability to grab some observations, put it in a YAML file and then pass it through a set. We know that's what we did. God, this is a memory lane. We standardize the interface to these models.

That's the first thing we did. And as soon as we standardize interface to models, we could then. Use the same data and pass it to different models. So we took the same utilization values, suddenly, suddenly, and I can't believe no one had ever really done this, ever. We took the same utilization values and we passed it through the Cloud Carbon Footprint model plugin that we created. We then took it to the Boavizta model plugin, and we then took it to the Teads, there was a Teads model plugin. And the numbers are so different.

I remember that was a real shock for all of us. And I won't go into details, but there was a, almost a 400 percent difference in the energy values from one to another.

Srinivasan Rakhunathan: I think the methodology differences between these datasets were so pronounced, like you talked about Boavizta, you talked about Cloud Carbon Footprint, that with the original concept that we had where we wanted to cover all, we would have had to build multiple flavors of the Impact Framework and there were cost issues in maintenance that would have caused issues in adoption.

I think the standardization of a model plugin was more a decision that we took once we realized that one model is not going to cut the cake for all of us. And You had different models depending on whether you are hosting it on AWS or Azure or GCP or your laptop or even your mobile devices. But if someone wants to just look at the raw emissions from the software, agnostic of the hardware, you could do that only if you have a very thin measurement tool.

Asim Hussain: Yeah. And for instance, also remember at the time I was still at Intel and we were building a model, a plugin for Impact Framework, which obviously would only measure Intel chips. So you had to have multiple models in a pipeline because if you had other vendors' chips, you would need that model in the pipeline as well to like calculate that model, you know, and the way I imagine the future is that vendors themselves would then be releasing their own models. Like my dream, Srini, is like Microsoft releases, I know it's doing the importer model, but then, you know, the future dream in the future is Microsoft releases models for every single one of its services. And if you're using that service, you plug in the Microsoft model for that service. You plug in whatever observation, like let's say it's gigabyte seconds for Azure Functions. You grab your Azure Function's gigabyte seconds, you've got the observations for there. How do you turn that into energy or carbon?

So ideally you just use the Microsoft Azure Functions plugin, plug

it in, and it knows how to convert gigabyte seconds for Azure Functions to whether, whatever it would be like energy probably, or maybe carbon.

I don't know how we'll end up there. So that'll be like, yeah, that'll be the future. My dream would be like, you come to Impact Framework and like, imagine you see like a page which is like hundreds of models and each of these models has like a logo of like some cloud service on it, you know, and you just drag and drop the cloud service that you're using. And then maybe you've even got some like automatic importer which imports the data from your cloud service into it. And boom, it's all working. It's all automatically calculating

Navveen Balani: It'll be probably like a GPT store.

Asim Hussain: A GPT. Yes. Oh yeah. The Impact Framework store where you go to, I could even imagine like, honestly, everything we've done is open source. Everything we're doing is publishing is open source. I'm fine if a commercial entity wants to come along and create a paid-for model, you know, "if you want to use this model, you need to sign a contract and pay us some money and, and use it" because honestly, maintaining a lot of this stuff is very challenging. Like get making these models is a lot of hard work. I'm okay with organizations, hint, hint out there if there's anybody listening, he wants to create a business on top of Impact Framework. It's, I think it's absolutely fine to, to create a plugin that is commercial creates, you know, let's say. I don't know what that would look like, but, you know, it pays money to, to do this properly.

Cause one of the things we're doing is like with one of our models is the Cloud Instance Metadata model. That model, given a cloud instance ID, tells you metadata about it, like the number of virtual CPUs, this, that, and the other. Because there is no good data set. There is no API, which you can go to for that.

So we need to maintain that as a GSF. And that takes time, effort. So if somebody out there wants to, you know, go do that, I think that's perfectly reasonable. Yeah. Why don't you each say what your favorite plugin is so far? I don't know if you have one. Navveen, what's your favorite plugin so far that we've built? I think I know what Srini's going to be. But, uh,

Navveen Balani: Let Srini go

Asim Hussain: Yeah, Srini go to first.

Navveen Balani: Let me

Asim Hussain: I'll Srini go first because it's a hard choice, isn't it. Srini, what's yours? If it's not the one I think it's going to be, I'm going to be surprised. Go on.

Srinivasan Rakhunathan: No, it's not the one you're thinking because it's not yet there.

Asim Hussain: Oh, okay.

Srinivasan Rakhunathan: Yeah, so I really like the TDP model. Yeah.

Asim Hussain: Like the Teads Curve one,

what we call Teads Curve? Yeah.

Srinivasan Rakhunathan: Yes. Because that's something that was very manual earlier. I don't think any of the other assets have that capability to give that Teads curve. And for me, while the solution, the technical solution was

simpler, I think, but the concept of having a model in the first place was awesome. I think that's how, you know, keep things simple, that same, the logic that works, right? Because it solves, you can extend the TDP model for any hosting infrastructure. It doesn't have to be a laptop or anything. I can just open my power configuration on my laptop, find out what is the TDP score, and then do a multiplication.

Asim Hussain: Oh, just plug it. Yeah.

Do you remember when, cause it's Benjamin Davies. We even brought him in to the standards working group one day, like years ago, just to talk through, cause he wrote, he did that. That's, it all started when he wrote that Medium post where they'd done that analysis and he'd like scanned through all of Amazon's bare metal servers, averaged every single server out to like, this is the generic power curve.

That's what we call the Teads curve. I don't know if that's the right term. We just call it the Teads curve, you know?

But like, that's the generic power curve. And then all you need is that data, plus what's called the TDP of a chip, and then without getting too wonky for our audience, then if you, then you can compute the, an estimate of energy for any single chip in the world. So open the door. I remember when that first came out, I was like, I felt like such a relief when Benjamin did that work. Cause prior to that, I was thinking, "Oh my God, we have to sit and figure out this data for every single chip in the entire world on every single device. How are we going to do this?"

And then he came along and went, "ah, I averaged it all out and it works pretty good." So we were like, "okay," and I see that used everywhere. So many places I see that used every, cause it's so easy. It kind of taught me a lesson actually, which is it was so stunningly easy. It was like one sentence could summarize that model. It's just everywhere. It's just absolutely everywhere. It's so simple to use. So yeah, that's a good one. That's the tease one. Yeah. Srini, Srini, you have one? Is it the SCI one? Maybe. No, Navveen.

Sorry.

Navveen Balani: Probably I'd like to have some AI model. Currently, we don't have one. So probably I'll wait for the hackathon to provide, right? Hopefully, as part of the hackathon, we'll get a lot of good models to evaluate.

Asim Hussain: What would be a good like AI model? Because like. Would it be something that kind of like, looks at it, like, what would the observations, is it prompts? It'd be like, what would be the observation prompts?

Navveen Balani: it'll be, yeah, it'll be an interesting model, I would say, based on the deployment. Uh, for instances, just to give an example, let's say if somebody is using an OpenAPI directly, right? They're just interacting with prompts. So in that case, how do you evaluate the carbon emission given just the prompts, right?

And a lot of these observability data may not be available from OpenAPI. But let's say if you're doing fine tuning or if you're doing your own model, then you will have access to infrastructure, and then you probably can use our existing models. So I would say the first one would be quite interesting where you don't have much information available from vendors.

So how do you come up with emission, right? Just maybe, just based on traction and prompts. Maybe it is prompts, length, latency. Let's see how the community as part of the Hackathon picks up this challenge.

Asim Hussain: I think, like, when I think of the future, like, it's interesting how our world's changed because we used to talk about AI emissions in terms of the training and, like, how long it

takes to train and we used to talk about inference in this very abstract way. And I'll be honest with you in the last six months, everybody just talks about prompts.

Like the word prompt is, and I use, I'll be honest, I use AI co pilots and all this other stuff all the time. And it's like, it's all about prompts, isn't it? I do think, Navveen, I think the future is going to be prompts. Like how many prompts have you made that generate images? Like an image prompt is probably going to be different. You probably have like a coefficient for an image prompt, code prompt, an LLM prompt, something like that. At least in terms of the way humans are working with AI these days. I think prompts is like the key. Yeah. And when you see like articles and stuff out there, it's always like, "Oh, on average prompts cause this impact" that I think I see the language being used that way. So, yeah.

Navveen Balani: I think that probably brings up to, I think, one of the challenges that we still need to solve around managed services, right? A lot of these, if you treat also OpenAPI, right, servicing offer as a managed service, now how do you calculate the carbon emissions? For instance, serverless is a very good example. So you have to use some kind of approximation, right? Because based on time or resources So expect similar models once we get more data and clarity, right? Yeah, we'll reach there.

Asim Hussain: Yeah. I think that's a really interesting, yeah. Maybe we'll get you, let's propose something in the, so there's a Carbon Hack coming up, a Hackathon coming up in a, in a couple of months around Impact Framework. I was going to mention at the end, let's talk right now, actually. 'Cause that actually, 'cause obviously there's going to be prizes for the best kind of models and plugins that we're describing right now.

And, and then Navveen, just as we're talking right now, I think I would love to see, as you say, like some submissions, and we can post in the ideas forum on the hackathon website, like. I'd love to see, you know, turn prompts into emissions.

That might be a right, that actually is turning into like a bit of a working session on Impact Framework that actually might be a good way for us to influence direction of what people are building in the hackathon is what we just described is like, "what are the observations that we want people to try and figure out the impacts for?" So I want to help figure out the impacts of prompts.

We talked about serverless, serverless, the observation for serverless is something called gigabyte seconds. Help me convert gigabyte seconds to energy. Like I can, I've got some ideas for that. Like, yeah, that's how we should think about this. We should be thinking about, we should be saying like, these are the observations that would be the most useful for us to create models, to turn those observations into impacts. So I don't know, I don't know what other observations that we have. Like billing data is obviously oftentimes a fallback.

Srinivasan Rakhunathan: GPU utilization is also there, I think.

Asim Hussain: Yeah. GPU utilization. Yeah. Or like, what about a non-cloud? Well, here's an observation. Yeah. Gigabytes transferred. Yeah. Write a model to turn gigabytes transferred into.

Srinivasan Rakhunathan: Emission.

Asim Hussain: What other observations are there, like from the web space, your observation might be page views. There's already models that do that, like page views.

Maybe this, oh, I think we've hit on something just now. I've been struggling to try and like, how do we encourage, how do we direct people? But I think this is how we direct people, which is: These are observations that we want to be able to model, submit, think it through. And we can, we can submit, but yeah, there's lots of others.

It's just late in the day. So just final question. So let's talk about this. Like, you know, we've been just building the alpha and beta version of this. And you know, there are some people using it right now, but let's just talk it through amongst ourselves, like in practical terms, how would you see, you know, a software developer, a practitioner or a company just start using the Impact Framework?

Like how would you. Imagine if you were talking to a company, what would the very first steps? What would you, what would the conversation be? Like, I'll tell you what I've been thinking about this stage. 'Cause I've really loved the idea of this term that Joseph used, which is like executable audit, maybe it's an audit. Maybe it's a, "bring me in, like what software do you want me to audit? Oh, you want me to audit your XYZ software. Okay. Give me your data. Give me your observations. I'm going to write a YAML file. I'm going to write a manifest file. And at the end, here's a file which gives you. All the emissions of this software over the last month," something like that.

Is that how you would start off or, or are you seeing the conversations go different ways? Srini, I'm seeing you like, I think you think differently. I'm just starting to suspect your mind looks looking, your face is looking.

Srinivasan Rakhunathan: No, I think, see. One scenario we've already seen, Asim, right, is many people are talking about region shifting and time shifting. So if you're running a workload based on the carbon intensity of the underlying region of data center or whatever, electricity grid, people are talking about, and I think many cloud providers have implemented it even to shift their workloads behind the scenes without.

With or without your consent to a different region which is more greener. Now, if people have accepted that as a new normal, then why are we waiting till the operational aspects of the software? Why can't we look at the development cycle, left shift the entire process, give the tool to, there are projects which have 80 developers, 100 developers, 120 developers.

Today, nobody has any idea of how many dev environments, prod environments, pre-prod environments. I think, unless you show people numbers and show people how to measure them, the real impact of what is translating into carbon emissions doesn't even come through. So I think a lot of value is there when it's a practical, when you talk to companies who are in this cloud migration initiatives or huge initiatives, multi year, multi semester initiatives, there is a lot of value in even calculating it at a development level.

Why do we even wait for the operational aspects of, you know, calculating emissions? So I think that is a USP for sure.

Asim Hussain: So I think you mentioned two things that were interesting. One was like. I think you were alluding to this whole idea of once you've got this kind of like Impact Framework manifest file, you can do this kind of what if scenarios that you're alluding to that, right?

So once you've got that manifest file, when you were saying shifting left, were you talking about once you got that audit effectively, once you walk in and you audit your application, and like, "here's my inventory," passing that to the developers and the team going, "by the way, this is everything that you're running. You can run some scenario, don't build CarbonAware computing, just add the CarbonAware scenario model to the end of the pipeline to simulate what it would look like if the CarbonAware was," it kind of gets that kind of, yeah, helps, it almost helps like model, like what if scenarios in, in that environment. And the other thing you were talking about, it was almost like, yeah, you mentioned cloud migration. In my experience, cloud migration is this kind of like, no matter what you do, it's just this messy thing. It's very confusing. You start off with like a very clear idea, a very clear plan. It's very messy and you're not really sure what's going on.

And by the end, you're very clear again, cause you're in the cloud and you've got some good metrics. I remember there was one organization that was reaching us out to the start. And they were like, we're moving to the cloud. And we wanted to measure using Impact Framework on premise. And then consistently measure as we slowly migrate our replication to the cloud. And that way, the audit from Impact Framework should then change slowly over time. Because theoretically, like the cloud is more environmentally better. Then that would have given them that clarity in that migration process. Which we were too late. They did the migration before we, we completed in where we are right now.

But anyway, that was an interesting thought. Navveen, I think because you work in the consulting scene, you actually speak to a lot more customers and clients than us. Like, I don't know, like, what do you have, do you have conversations? Like, how do you have conversations to them about the Impact Framework?

Navveen Balani: So to extend to the simulation example, right, I think a lot of cloud vendors provide calculators, right, to calculate, let's say, the cost based on virtual machines, the entire infrastructure, right? So if you could put the element of carbon and emission also, right, because they know how the infrastructure is set up. And now they can do a simulation based on both cost as well as the carbon emission and also do simulations that reducing carbon also reduces your cost, right? So a lot of, I think enterprise wants to do a lot of FinOps activity, maintain the cost also, right? Sustainability of this tool, right, can be good uh, outcome to reduce their cost also. That can be also a value proportion to lower, I mean, lower the carbon footprint as well as the lower, the total cost of ownership.

Asim Hussain: There is nothing, I would say, stopping anybody using impact for any, like cost as an impact. There's nothing stopping anybody using it just to look at cost and then scenario cost reductions as well. So, okay, I think we're running out of time now today. So let me just maybe just close out statement. I also want to give it a bit of a call out to the Carbon Hack. So thank you both again for like, I know we chat every week, but thank you both for having another chat here. I think it's been such an exciting journey that we've been on. So that's just about it for our deep dive into the Impact Framework. Before we head off, I just have a quick announcement about CarbonHack24. CarbonHack is a global contest for developers who want to make a difference in the fight against climate change. It challenges participants to use the Impact Framework, which we've just been speaking about in depth. The theme of CarbonHack this year is measurement. We want to see how you can use Impact Framework to measure the carbon emissions. You know, other, we're also talking beyond carbon this year. So we have a prize of, you know, water, carbon, other things like that. If you could help us to write plugins for Impact Framework, which help us measure beyond carbon. We would love it. That's really where we want to move the conversation. We have kind of basically three prize categories.

One is the best plugin, which is like what we've just been describing, which is like something that can take an observation and turn it into something else is a plugin beyond carbon is a price for us for a type of plugin, which can take an observation and turn it into like a water or a. Or another beyond carbon type of type of measurement.

And we also have a prize for best content. So if you can help us to explain Impact Framework better than we're explaining it ourselves, there's actually a prize for that. That's like a non technical prize, whether it's a video or a tutorial or anything like that. We also have an undergraduates prize. So if your entire team is made up of undergraduates who are university, there's a special prize for you in addition to the prizes. And we've also now got to confirm, I don't know if I told you, but we've now got to confirm that we can have an under 18s prize. So if your entire team is made up of under 18s, there is again, an additional prize just for you on top of everything else. So I'm very excited about that. So CarbonHack is online.

It's starting on the 18th of March and ends on the 8th of April. You're going to compete to showcase your best application in the prize categories I've just spoken about. The hackathon is open to all, but you must register to be part of it. Registration begins on January 22nd.

Please head to hack.greensoftware.foundation. It's a pre-register. And once you're there, then we'll send you further emails about how to get, how to get more involved. So please go hack.greensoftware.foundation, register now. It's all in the show notes. So we've come to the end of our podcasts. All is left for me to say, thank you so much to Navveen and Srini.

That was really great. Thank you for your contribution. And we really appreciate you coming to Environment Variables.

Navveen Balani: Yeah. Thank you everyone. Looking forward to the Hackathon.

Srinivasan Rakhunathan: Thanks. Thanks for the opportunity and looking forward to meeting you guys in future as well.

Asim Hussain: Awesome. That's all for this episode of Environment Variables. All the resources for this episode are in the show description below. And you can visit podcast. greensoftware. foundation to listen to more episodes of Environment Variables. See you all in the next episode. Bye for now.

Hey, everyone. Thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we want more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation. Thanks again, and see you in the next episode.

View Details

Host Chris Adams is joined by Arik Smith and Cameron Cash from Thoughtworks in this episode of Environment Variables. Together they discuss the Cloud Carbon Footprint (CCF) tool and the role it plays in sustainable software development. Join this conversation as they nerd out together about the future of measuring carbon in the cloud, open source collaboration, and some cool posters in the background.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Arik Smith: LinkedIn * Cameron Casher: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Responsible Technology Playbook: Tools for the United Nations | Thoughtworks [06:40] * GCS23: Cameron Casher on Responsible Tech & Cloud Carbon Footprint [07:05] * Cloud Carbon Footprint [09:25] * Etsy Engineering | Cloud Jewels: Estimating kWh in the Cloud [12:41] * 20231124 - green coding summit - ai environmental impacts assessment workshop [26:19] * 20231124 - green coding summit - infra/cloud environmental impacts assessment workshop [26:52]

Resources:* Arik’s awesomely distracting looking poster [02:36] * Notes from the SDIA Green Coding summit [07:05] * (GreenOps) A forecast of green clouds | Thoughtworks [08:18] * Green Software Patterns [08:24] * Electricity Maps API Documentation [28:36] * Software Carbon Intensity (SCI) Specification Project | GSF [32:38] * GitHub - cloud-carbon-footprint/cloud-carbon-footprint [38:04]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

**TRANSCRIPT BELOW:

Arik Smith:** [00:00:00] At the end of the day, CCF is a community supported and collaborative tool, and I think that's the biggest and strongest part of all is that this isn't a methodology that one organization has owned or came up with, but that the, I want to say the entire industry who really cares about this subject has contributed and promoted growth within.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host, Chris Adams. Hello, and welcome to another episode of Environment Variables, where we bring you the latest news and updates from the world of sustainable software [00:01:00] development. I'm your host, Chris Adams. In our first episode of Environment Variables, we spoke about the team working on Cloud Carbon Footprint, about the subject of carbon calculation in the cloud. And a lot has happened since that episode. We've basically seen a spawn of imitators, and we've seen a launch of a number of native new platforms that various cloud providers use to help people understand the environmental impact of using digital services. Cloud Carbon Footprint has remained the open source reference, and as we'll discuss in more detail, parts of it end up making it into all kinds of other services these days. So it's been a while since we spoke about Cloud Carbon Footprint, or even Carbon Calculation in total. So joining me today are two of the main maintainers of the project to dive into some of the weeds on this. All right, today I'm joined by Cam and Arik. Folks, I'll just give you the space [00:02:00] to introduce yourselves.

Cam, if I give you the floor, then Arik, I guess you can introduce yourself after that.

Cameron Casher: Thanks, Chris. Really happy to be here. I'm Cameron Kasher. I work at ThoughtWorks on software, data, sustainability, general responsible tech, and really happy to talk to you today about Cloud Carbon Footprint.

Chris Adams: Cool, thank you. And Arik?

Arik Smith: Hey, I'm Arik Smith. I also work as a developer consultant at ThoughtWorks, mainly as a cloud SME and a green software specialist. But I am also excited to be here, so thanks for having me.

Chris Adams: You're very welcome. I'm excited here, but I'm also quite excited by that awesome looking poster that I can see inside the video. I'm afraid that you can't see it in the audio, but there looks like there's a Japanese poster behind you. Is that Zelda or something? Arik, can you please tell me what that is, because it's totally distracting, but it looks really awesome.

Arik Smith: Yeah, for sure. So behind me I have my home office, which is basically in my basement that I call my culture cave. So what [00:03:00] you're looking at is what I call my wall of culture, where I just hang up artwork that I usually find at local vendors around town, mainly around my favorite video games and movies.

So yeah, the poster is a poster with Link on it and in Japanese katakana, it says Zelda, but there's also some other stuff on there. I have an Avatar poster right next to it for The Last Airbender, and a Final Fantasy VII, and an Arcane League of Legends poster. Lots of fun stuff going on.

Chris Adams: Wow that's an impressive nerd cave, and I think anyone who's been following Zelda this year will probably be excited about a reference to Tears of the Kingdom, amongst other things. All right, and Cam, we met in person, actually, about a month ago, when you came over to Berlin for the Green Coding Summit, and I A, I realized you were so much taller than me, oh my god, but also I didn't realize whereabouts that you were coming from.

So you were coming from Colorado before, and at the time of recording, this is the 21st of December, so there's a bunch [00:04:00] of really explosive political news that might impact what will happen with elections next year. But, as much as I do want to talk about that, and what the climate implications of having different leadership in America might be, I think I should ask you about one thing you told me about, skiing in Colorado. That's a thing that you do on a regular, right?

Cameron Casher: Yeah, it was great to see you in the flesh in Berlin. It was really awesome to be there. And yes, Colorado has found itself at the forefront of U. S. politics at the moment. So, that's exciting. And, yeah, we're in uh, ski season here. I'm excited to get out and snowboard a bit. But still waiting on some of the good snow to hit some of the Colorado ski resorts, but I'll be trying to get some days in this winter for sure.

Chris Adams: Nice. Okay, cool. I'm calling from Berlin, and if you haven't heard this podcast before, I should probably introduce myself as well. My name is Chris Adams. I work as the executive director of the [00:05:00] Green Web Foundation, a small Dutch non profit focusing on reaching an entirely fossil free internet by 2030. But I'm also one of the chairs of the Green Software Foundation's policy working group, where we do work with standards bodies and other organizations working in this field of sustainable software and general sustainability. All right, I think with that in place, I should ask you folks, are you sitting comfortably?

Looks like you are. Okay, then I guess I'll begin. Okay, Cameron, I'll ask you about this because you were talking about this notion of responsible tech when you came over in Berlin, and then maybe that will use that as a way to talk about some of the projects that you've been working on. Maybe we could just open with what this notion of the Responsible Tech Playbook that you're presenting, because that looks like it provides a bit of context and that helps understand where tools and carbon calculation might actually fit into the context of using technology in a more responsible basis.

If you could start there, maybe.

Cameron Casher: Yeah, [00:06:00] definitely. I know you'll probably hint to this, but we can definitely link to these resources in the podcast description. But

Chris Adams: Yeah, absolutely. Thank you for reminding me. If you hear any projects mentioned or anything like that, and if we don't put it in the show notes, please do let us know, because we realize that people who listen to this podcast often use every single project as a jump off board for their own research. So we will do everything we can to make sure this is useful for other people who are taking their first steps or trying to explore this new field. All right, Cameron, yes, you were saying we were, you were

presenting about this, yeah.

Cameron Casher: So ThoughtWorks has done some really cool stuff in the area of responsible tech. We had a playbook that came out a couple years ago. And really cool thing recently is we got in touch with some folks at the United Nations and they were very interested in our Responsible Tech Playbook. So we were able to do some really cool work partnering with them to create a more customized [00:07:00] version of it. They're very large around the world and they have a lot of people doing a lot of great stuff. So incorporating responsible tech principles and practices was very important to them and doing it in a more customizable way. So that's what I talked about in Berlin a bit at the Green Code Summit about what the playbook was.

So maybe it's worth just defining what we consider responsible tech.

Chris Adams: Yeah, go for it.

Cameron Casher: We consider responsible tech as the active consideration of values, unintended consequences, and negative impacts of technology. A lot of times these tend to go overlooked. It's not always necessarily a negative intention when developing technology, but really it's, the idea is to manage and mitigate potential risk and to be inclusive to all communities.

There are a lot of different topics we cover in the playbook, including data and AI. Accessibility is a big one, but what I really focused on in [00:08:00] Honestly, because a bit of my background was sustainability, so I was able to shift the focus at the conference talking about it, but also help get a really cool chapter in the playbook around sustainability and how we could incorporate the idea of GreenOps and incorporating Cloud Carbon Footprint.

Chris Adams: Okay, and GreenOps in this scenario is essentially what DevOps is to developing. GreenOps is to this same idea, like it's essentially operationalizing some of the kind of aspects of green software. Is that the idea behind it?

Cameron Casher: Yeah, and another ops really, there's a ton of ops these days, but the idea is tying it really close to DevOps or FinOps too, from a more financial standpoint, really considering green software, carbon emissions, carbon footprint within your development process.

Chris Adams: Ah, okay, so that makes sense. And now I understand the link between there and Cloud Carbon Footprint in its own right, which basically ends up essentially using some of the [00:09:00] usage data that gets produced as a byproduct of operating various digital services and then providing that in a way that you can act upon, or do something, or, or, you shouldn't.

Arik, I see you nodding, so I suspect maybe I should actually give some space for you here. Maybe you can introduce Cloud Carbon Footprint to people who have never heard of this, and why someone who is a software engineer who is curious about environmental sustainability in this context might care about it or want to know about it.

Arik Smith: Yeah, absolutely. Cloud Carbon Footprint is an open source tool for tracking your energy usage and carbon emissions across All the major cloud providers, AWS, Google Cloud, and Azure. And, which we can talk about later, we've also added, or begun to add support for Alibaba Cloud as well. It's a great tool, it serves as an unopinionated monorepository of multiple toolkits for you to go about grabbing your estimates.

So we have a CLI, uh, or a command line interface you can interact with, uh, we have an [00:10:00] API that you can integrate into existing workloads or directly carry, as well as an out of the box dashboard for visualizing and tracking your emissions over time. Um, and we present this at a daily granularity, sometimes even hourly.

Because what we do is we query your usage from your billing data. So think about AWS, Athena, costing usage reports, exports, or your Google Cloud, BigQuery, billing data exports, or your Azure cost details API or exports. We take all of that in the granular usage data that they use and convert that into energy where we can then convert that into carbon emissions to display.

Chris Adams: Ah, cool, okay, so anything that can basically expose billing data or usage data can then basically provide a single view across maybe in a state or a different set of services. So rather than having 3 or 4 competing and possibly incompatible calculators, you have one [00:11:00] consistent way of looking at this stuff, right?

Arik Smith: Absolutely, yep, you'll have one unified methodology to be able to view your usage across multiple cloud providers all within a single dashboard or a single place, which is great just to get a holistic view of where you stand and comparing apples to apples in that way.

Chris Adams: Gotcha. All right, okay. Now, I know that I've been somewhat familiar with Cloud Carbon Footprint and there's a bit of a backstory behind how it came about, because I think there was actually a few years ago there was some really like pioneering work from some folks at Etsy who started on some of this. I'll leave that open for either of you to actually talk a bit about that, because I think there's a really interesting story about how some of this work done in the open there ends up turning into a tool which ends up feeling a little bit like, you know, that XKCD cartoon where there's that one piece of project that everything gets built on? That's how I see a bunch of this. And maybe I, maybe I'll let one of you folks explain some of the origins of this and how that end up, how some of that led to [00:12:00] CCF, or Cloud Carbon Footprint, being like an open source project with a number of users.

Arik Smith: Yeah, absolutely. So within ThoughtWorks itself, there was a lot of growing interest within climate action and getting a hold of our own infrastructure and where our footprint stands with that, especially within our cloud resources. And what we found was that there was not really a tool to do so at the time.

So this was about, and Cam, feel free to correct me on timing, but I believe about 2020, where the bulk of this work was done. And being ThoughtWorkers, we typically decided to look into ways we could perhaps create a way for ourselves to measure our own cloud usage. And we came across Etsy's awesome Cloud Jewels methodology and saw the way that they were estimating compute resources within the cloud, and it served as a great basis and foundation for us to build and find out how can we do that for Google Cloud and AWS and Azure, all the [00:13:00] different cloud providers that we have some level of usage within.

So we started building out a proof of concept to estimate our own internal usage and eventually we made the decision that due to the absence of any tooling out there that this is something everyone should have because we want to empower all organizations and all users to be able to have this level of transparency with their cloud usage because the compute resources and overall energy usage of the IT industry in general is a big major part of our global footprint, especially in major large tech companies and large scale product companies.

We went open source back in March 2021, and since then we've been iterating on it ever since until the cloud providers came out with their own native tools, which is great, and we saw more and more tools and interests popping up in this space.

Chris Adams: okay. That's cool. So basically there's this OG climate calculation stuff, uh, from Etsy, and then that big, that served as some of the basis for a more polished [00:14:00] tool that could be used in lots of different contexts, rather than just the ones that Etsy used, because I think back then, Etsy had a bunch of on-prem stuff and a bunch of Google Cloud, so that was where some of it looked like, but when CCF became, I think the first version that I saw, actually had support for both AWS and a bit of Google Cloud, and now it's actually got support for, like you said, all the big ones, plus Alibaba, I didn't know about Alibaba, actually.

it.

Arik Smith: Yeah, Alibaba is limited to compute resources for now, but we're still looking into ways to expand that. Um, similar to how we did Um, at the beginning with Etsy, they were estimating cloud, um, compute resources. And then we started thinking about how can we expand that to memory and to networking. And all of that has been a collaborative effort, which is why we call out Etsy within our methodology as the basis from where we started from.

Like even just the networking estimations. We work with Benjamin Davey from Teads based on a write up he did for estimating network as well as embodied admissions and iterated within the other [00:15:00] usage levels within the same way.

Chris Adams: Ah, cool. I think I remember, actually, there's a bit of work by David Mitton there, when he did some work around the CPU coefficient stuff as well. I realize I'm diving into, like, loads of really nerdy stuff, uh Cam, I see you nodding, so maybe I'll let you just touch on some of that stuff, because I think it might be worth talking a little bit about where else this turns up, because we've seen a number of calculators kind of launch now.

A lot of them either reference CCF, or have started using that as a basis. But before, though, I'm getting ahead of myself, yeah. Maybe I'll give the space for you, Cameron, because I saw you getting a bit excited there when we were talking about some of that.

Cameron Casher: Yeah, what's funny is the opportunity to speak here today with you gave us, gave Arik and I a chance to be a little retrospective about our time with CCF and think about lessons learned and what's gone on, what's been challenging. And yeah, even just hearing Arik talk about our partnerships and collaboration, I think it's just worth saying that's been a really cool aspect of being an open source maintainer. [00:16:00] Just being able to openly work with the community, being able to have really awesome discussions with industry experts like David Mitton or Benjamin Davey or everyone at Etsy to just continually evolve the methodology for CCF and make it better, make it fit users, and getting into some of the challenges, I don't know if it's necessarily a challenge, but it's just a tough point is that. We don't have the best transparency into who's using the tool, and I think that's a pretty common trend for open source software, but a lot of it is just through word of mouth, or even when I was in Berlin and talked about it, I got the chance to meet a lot of people that approached me and let me know that they were using CCF, which is, it's really cool to hear about that and the impact that it's had.

Chris Adams: Oh, thanks, Cam. So you mentioned David, uh, David Mitton, and, uh, and I realize there's a couple of other people who are also involved in this as well. I mean, well, the original person on the podcast was, uh, [00:17:00] uh, Danielle, uh, oh, Cameron, I need you to help me with her surname. What was Danielle's surname again?

Because she was

the original product manager on this.

Cameron Casher: Danielle Erickson, and she was, yeah, one of the first guests, and she was a very integral role with the open source launch and continued feature development for CCF as our project manager. So, um, yeah, Danielle had a serious role. And also Lisa McNally, who is the, also on the policy working group with you, um, she helped spearhead a lot of our development too.

And I'd be remiss if I didn't mention Marco Valtas, who had a significant role on the dev team as well.

Chris Adams: Oh, cool. I'm really glad you mentioned that, actually. And, uh, actually going back, Jesus, in a few years back now, oh, uh, was, uh, I believe Chelsea, Chelsea, I think it's Chelsea Mozen. She was one of the people who was organizing Climate Action Tech back in 2019 2020, and, uh, I learned so much from her, and she was one of the people really pushing the stuff at Etsy as well.

So, it's, I'm really glad [00:18:00] you spoke about some of the other people, because there's a whole lineage of people who've been contributing to this now over the years.

Cameron Casher: And so many people are coming to mind and, you know, even Dan Lewis-Toakley, who's been a part of the Green Software Foundation, really spearheaded the open source launch too, in the early days. So important to include him as well.

Chris Adams: Yeah, happy days.

Cameron Casher: So I think we're just trying to look for ways to have a better understanding of who's using it.

We have an adopters markdown file in our GitHub repo. We're still trying to get the word out that we want to know what your story is and what your experience has been with CCF. And we have a blog that we just put on the microsite and we're very open to just sharing stories and experiences to providing help for anyone new who wants to try and get it set up at their organization or just for their own personal use.

Chris Adams: I can definitely speak to this because, uh, we maintain, where I work, we maintain a library called CO2.js, which we know is used in a few places, like, uh, we [00:19:00] spoke to Mozilla, and it's in their browser, which is cool, and we work with some other people where we collaborated, but then sometimes it turns up in totally random places.

So, like, I did a talk, um, in Hungary, uh, and I was invited to speak at this event, and then when it was launched, I found out that it was actually used inside one of the key projects that people were actually launching on the day. I was like, "oh! Wow, that's cool and unexpected, but nice to know," right? And I feel that seems to be some of the cases when I see with CCF, because I know that, um, there's a tool called GreenPixie, which is a quite well developed, quite sophisticated commercial product that initially had some origins with CCF, where they use some of that.

I understand, I believe, I think VMware uses some parts of it, as well as IBM. So it turns up in all these interesting places that I didn't, that I hadn't thought about. And when I actually was at the same event as you. I didn't realize the footprint it had in the financial services industry. And that was the thing that really blew my mind, actually, and this, it's, I guess it kind of does [00:20:00] make sense, really, because if you don't have access to information here, having an open methodology is quite useful, and we, at that event, we saw at least one person from a well known bank, ABN AMRO, this is like one of the third largest banks in the Netherlands, they basically said, we're a regulated organization, we, when we calculated our emissions, it's like 40 percent of our carbon footprint comes from our use of digital services.

So we want to have an open tool that doesn't have us rely on a single thing and lets us be transparent with both our regulators, but also our sustainability teams. And this was actually mind blowing that you'd actually have companies talking about this because for the longest time, people tend to either don't say too much about what the environmental impact of digital services might be in their organization, or they say it's very low.

So to have organizations say, yeah, we're using it, this is what we use as our basis, and this is how we calculate it, was mind blowing. It was really useful to see that actually because Like you said, it's really hard to see, and it would be so nice to know that it's [00:21:00] reassuring to find people using your projects, but sometimes it's so hard, you do ask yourself, like, could we have found out another, did I have to really fly across the Atlantic to find out that people are using this tool?

Cameron Casher: Yeah. Yeah. And I'll just add, I think we might touch on this a bit too, but our roadmap, how we decide what we want to continue to build and look into is really community driven. So it's really helpful to understand how people are using CCF to help us understand what to fix or implement. Yeah, it's just very important, really.

Chris Adams: So maybe we can talk a little bit about that then, because we spoke about roadmaps, and like I saw you nodding along when you were thinking about some of the things that are on this list, and I realize that you've been implementing some of this. Are there any kind of, like, exciting things that you're looking forward to seeing the light of day, or being able to work on, that you're really thinking, "Ah, I cannot wait for this to be visible," for example?

Arik Smith: Yeah, absolutely. So we have a few things in the works that I think are [00:22:00] exciting. One of the big things is a lot of improvements we've been trying to do this year is to our overall implementation of Azure, as well as just performance and scalability, which has been one of the biggest lessons learned during the time that we've been developing CCF.

Because ThoughtWorks itself isn't a product company, so we don't have a lot of internal cloud usage. So really learning and leveraging partners and collaborators and sometimes even clients to figure out what type of issues or what type of considerations that enterprise level product companies will have when using CCF has been really helpful and what we've been really leaning into.

And even just Azure as well, because Azure has a Different implementation where it's more API based instead of SQL based like your Google Cloud BigQuery or your AWS Athena, which we interact with for usage. So we currently have a migration going on to migrate to some of the new ways that Azure has made available to [00:23:00] grab billing data.

And one of that is through their new Cost Details API, which we were previously using their Consumption Management API. And then as well as the ability to export cost into an Azure blob and be able to parse a large amount of data from that. So that's currently in the works and we can't, we think this will help a lot of large scale Azure users, which unfortunately due to the differences in implementation.

tends to lag a little bit behind in some of the ways we deal with the other cloud providers. But also, even beyond that, we've seen a lot of interest in Trying to get a grasp of usage and cost for Kubernetes workloads and clusters. And we have a really cool partnership coming up in ways we are looking into collaborating with OpenCost, another open source tool for diving into Kubernetes spend and finding ways to use CCF as a basis to showcase energy [00:24:00] usage and carbon emissions alongside the data that they show within the tool.

We've done a similar collaboration in the past with Backstage, making CCF a plugin for their platform. And that is also another cool opportunity coming up because people use open costs and we're trying to really leverage the ways that CCF is flexible and extensible to where you can still use CCF's methodology as we've seen

in some of the other tools we mentioned, but also in your existing toolkit, and that's why we keep referring to it as a tool and not just a product, because it's really just a means to an end to be able to get transparency into your cloud usage and carbon footprint. I think those are two of the biggest things.

Oh, and we also have Boavizta, but I may actually toss that to Cam because that's something he's been a little bit closer

to to talk about.

Chris Adams: Alright, Cam, before we go into that, I just want to, I realise that we didn't actually speak about this now, um, CCF [00:25:00] is a open source product, um, it's presumably written, is it TypeScript or JavaScript? Maybe we could just touch on that briefly because I realize that we didn't actually talk about any of that, uh, and it might be useful for people who are curious about taking their first steps, right?

Arik Smith: Yeah, for sure. Yeah, CCF is an open source monorepository, all written in TypeScript. And that was a deliberate decision because we wanted to have a single language used across the entire codebase to make contributions and onboarding to the project easier. So if you're looking for an open source project to contribute to, we welcome it.

Even if you just want to read the methodology and provide feedback, we welcome that as well. But yeah, so the dashboard itself mainly leverages React. It has a simple React dashboard for visualizing your data with the API being in Express and the rest being in native TypeScript. Tried to keep it simple, but,

Chris Adams: so it's stuff that people are likely to be, to use, it's not something like written in Sorry [00:26:00] Haskell Friends, like Haskell, or something which is not that popular. Okay, cool.

All right, Cam, yeah. Cam, you were about to talk about some of the other things on the roadmap that you, uh, touched on. I think, maybe it might be worth just briefly explaining what Boavizta is, because if people haven't heard of Boavizta, they might not know about the cool French guys and, uh, women working in that particular project.

Cameron Casher: Yeah, Boavizta actually had a really cool workshop at the summit that we were at in Berlin. And they were explaining some of the ways that you can go about measuring the energy from some of your server usage, which is some really cool work and props to those guys who did an excellent job there. Because I think there was a really good collaboration in that workshop and it was pretty well received and spawned a lot of great conversation.

Chris Adams: I agree with you on that. I remember, so the, so the thing with, the interesting about Boavizta is like, we'll share a link to the workshop, because one thing that was nice is they did this, Boavizta led one of these workshops about understanding [00:27:00] the both embodied energy and the usage energy in cloud, but they did another one about AI as well, but they were gracious enough to share the entire decks and everything online as well, so we'll add some links to that.

So we've established Boavizta, that was one thing, but you mentioned there's some other products or other kind of integrations that are on the roadmap that you might be talking about, possibly also with French speaking people involved, I suppose.

Cameron Casher: Yeah. So I guess for context, we, with our methodology, we've had to rely on a lot of other public and open datasets since a lot of the information around carbon or energy estimations, we haven't been able to grab directly from the major cloud providers, at least just yet, we are really reliant on some of the open data sets we find.

And with that comes a lot of manual updating and monitoring to make sure we're aware of when some of these data sets get published with new information, this really led us to the idea of wanting to [00:28:00] more automate the way that people could get some of this data, whether it's energy estimations for servers or even carbon intensity values. What I really wanted to try and do lately is almost integrate feature toggles. You can always default to some of this average data from the publicly available sources, but if you have a Boavizta subscription or however you'd connect, then maybe you could select that as your way to get some server information from some of your, let's say AWS vCPUs. Or another thing that we wanted to express was our partnership with Electricity Maps. This is another company over in Europe that's doing a really great job around understanding real time carbon intensity values from regions globally around the world. This is really nice for CCF because you can really get more accurate carbon [00:29:00] intensity data, which is a integral part of our estimation for carbon emissions in our methodology. And some of the work we were able to do lately was map the Electricity Map zones to cloud provider regions. So you're able to directly connect. If you have a subscription to Electricity Maps, you essentially just pick a box and say you want to use this and get to see some of their data and map it to some of the daily values that you'll see from your cost and usage report.

Chris Adams: Ah, I see. Okay, so if I, to make that a little bit more concrete, when you often have, say, some values which might be, so people often talk about the idea that you can maybe change a region to reduce the environmental impact. Let's say you're using AWS, and on one part of the United States, on the Eastern Seaboard, New Virginia, not Eastern Seaboard, but North Virginia, yeah, that's going to be using a bunch of coal, and you, but on the other side, you might have, say, in Oregon, it's going to be a very [00:30:00] kind of like cleaner grid by comparison, but there may be other places which might fluctuate at various times and that will capture some of those changes specifically that an Electricity Map would give you, right?

If there's maybe times of day where it's particularly sunny and windy, you'd have green energy there and it would actually reflect that in the billing, for example, or show it in your stats in a given day or hour, right?

Cameron Casher: Right. And the really cool thing about their API is that we are able to grab historic data. And a lot of people using CCF are wanting to see what their usage looks like for the past year or two. So we're able to actually map on those given days of their usage, backtrack and backfill. And yeah, they also offer hourly estimations too.

That's something we're looking forward to potentially implementing for CCF is estimations on an hourly basis.

Chris Adams: Ah, I did not know that. That's very cool to know. All right, because this is one of the scenarios that I'm curious about. Because once you do actually have like enough usage data, you often, the question is, it's almost hypothetical. [00:31:00] "Now I know I've been doing this year. What could I have done so that I can inform like future discussions?"

This is why, because a lot of the time having maybe a bunch of historical data and then being able to see would it have made a difference if I switched to another region, or would it have made a difference if I moved a particular piece of job that happened, a computing job that happened every single time at this time, could I have measured that?

And it sounds like this, these are some of the tooling that actually makes some of that possible, so you can start comparing what you would do then, say this is what we should be doing next year, now that we've actually got some of our own usage data and some carbon information about what, where we might go from there.

Cameron Casher: Yeah, and I know a lot of organizations that are trying to set their sustainability goals for the future and even in the case of ThoughtWorks, having that baseline year is very important where you can set a year and be able to say, okay, this is our baseline. This is where we want to measure up against as we try and hit some of our goals that we're setting, like our 5 or 10 year plans.

Being able to see that historic data is very important today. If you want to [00:32:00] set 2023 as your baseline, you can see what your cloud carbon footprint looks like from that year and just move forward and try and improve it.

Chris Adams: Ah, okay. That's helpful because basically the entire sector needs to halve its emissions by 2030 in order to stay on the kind of pipe, on the trajectory for 1.5 degrees. And I guess that gives you some context that works out to be about a saving, you need to reduce emissions by between seven to 10% per year depending on what you have.

And this might give you a way of saying, "okay. Here's what they are now, this year, this is what we need to beat or stay inside if we're going to be on track." Huh, I didn't know that.

Okay,

Cameron Casher: Yeah. And actually that's a good plug for the, the SCI standard at the Green Software Foundation because, uh, CCF does a really good job at giving you your holistic view of all your usage and emissions, which a lot of companies is only going to grow as they scale. Also using this alongside the SCI could be helpful to see more of the rate of carbon emissions.

Chris Adams: [00:33:00] Okay, so this is one thing that I think is interesting that really caught my eye, because when I was initially looking at Cloud Carbon Footprint, there was this idea that you can tag certain services, so you can say, here's my team, or there's a particular there's maybe a particular digital service I make available to people. Presumably you could track that, and you could say, "over this week, the SCI has been this much, which is the Software Carbon Intensity. And then I want to improve that by X percent," and you could set that as a target for the next month, and so on. That's essentially what you would be able to do. Is that correct?

Cameron Casher: Yeah. So we did implement tagging, which was a really crucial feature for us in a lot of ways to help with this whole idea of GreenOps and just understanding how you can do different breakdowns for teams or resources. And actually Arik was a really pivotal developer for the tagging. So I might let him speak a little bit about,

Chris Adams: Yeah, please do. Yeah.

Arik Smith: Yeah, for sure. So yeah, so tagging [00:34:00] basically allowed for us to display the same tags that you would use within your AWS or Google Cloud or Azure Resources, but also expose them on the resources that we were estimating within CCF. And it's great because not only does does it allow you to filter at a more custom level when you're using the CCF API, if you only want to see

resources tagged with a specific value, but it's also great for when you're trying to see aggregated estimates for a custom grouping of resources. So Cam mentioned whether this may be at a team level, or a sub organization level, or a project level, or however you wish to organize it. So, it has been great in getting a grasp in a much more custom level of where you stand within your organization and what your big contributors are that go beyond just the account and service level.

Chris Adams: No, that's actually really interesting. So, what I think it sounds like you're saying is, with tagging like this, you could basically say in a given [00:35:00] month, I know that all the billing for this particular service has been this much. And I know I've done maybe 100, 000 or 10 million requests. Then basically, because the software carbon intensity is essentially, it's the number of things you've done, divided by the emissions, or the other way around basically. That sounds like you could plausibly get SCI ratings for almost any service very quickly that way, across an entire project, basically. I didn't really, I didn't really think of it that way, but that, that, that would be right. If you just have a bunch of things tagged, you know how much usage you have, like, how many people have used this, or how many requests have you served? That will be enough to put together some calculations for a rate like that that you could track over time, right?

Arik Smith: Yeah, absolutely. I think it also opens a lot of possibilities for the ways that you can use CCF. So it's something that I forgot to mention on our roadmap. We're trying to continue to expand upon right now, a lot of those features are available at the API level, which just so happens to be the most [00:36:00] popular way people interact with CCF.

But we're also trying to leverage the dashboard to be able to view a breakdown of your tagged resources in a much more custom way and be able to filter through data through there as well. But absolutely, yeah, it opened up a door to where the world is your oyster in terms of how you choose to bring your estimates or certain groupings into your overall footprint.

Chris Adams: Okay, so I'm glad we had this conversation, because the next thing I want to ask is about community involvement, because when you're running an open source project, there's, there's a, there's a challenge about working out, do you use a mailing list? How do you actually get feedback from people? Let's say we just had this conversation about, okay, I want to have automatic SCI readings for every single thing that comes through, like, where would I ask?

Is there like a Slack channel? Is there a mailing list? Or is there a GitHub discussions board or something? Maybe I could ask one of you about where I would ask something like this to have this conversation, because I'll be honest, I might look at some of this over winter, if nothing else, over the winter break, [00:37:00] because I'd, that didn't occur to me until we just had this conversation now.

Arik Smith: Yeah, absolutely. It's been a learning experience for us. Um, ThoughtWorks has had a few open source projects previously, but at least for us personally, we've never been maintainers, so we've definitely still have been trying to figure out that cadence of what is our preferred communication method? What do people prefer?

And with this project being targeted not only to the software engineer that's curious about their own team's carbon footprint, but also IT execs that are can actively make decisions and utilize CCF to provide a lot of information behind those decisions. We have to be flexible. So we started and currently still use a simple Google group, which is on our website that you can join and become a community member of.

And we get lots of emails that way, either asking direct questions or troubleshooting information from our team or just the community at large, which has been [00:38:00] great because sometimes people may chime in and share their experiences or give their feedback. Of course, since our project is on GitHub, we leverage a lot of GitHub issues and the typical cadence that you would find within the open source repository there.

So people usually raise new issues for bug reports or features, and we've also recently enabled the GitHub Discussions board for our repository to allow for further discussions, especially around feedback or general questions to hopefully try to lessen the load on our email group a bit and keep it closer to our code since we've been seeing a lot of technical questions and bug reports and troubleshootings coming through there and more recently we've been trying to experiment with a Slack channel to get some of those conversations going at least a little bit more seamlessly because one of the main things we've been troubleshooting and learning from is the way that we interact with collaborators.

A lot of times when [00:39:00] other organizations or companies are standing up CCF within their own organization, they often want to get back to the tool or they may find a bug or something to improve and may open up pull requests and a lot of that conversations have been through the email group or GitHub at large, but for instance, that Azure API migration that we're working on is actually being collaborated with some engineers from Resync that Cam met during his time in Berlin.

So we've opened up a Slack channel to hopefully make some of that collaboration and communication and questions easier. Before it's been ad-hoc, "okay, we'll join your Slack or we'll join your, your Teams account or maybe we can do a simple Google chat," but hopefully to centralize and encourage a lot of those communications and collaborations going forward.

Chris Adams: Ah, cool. So you said one thing that was quite interesting there, about that it's not centri It's, this gives me the impression that it's, that Cloud Carbon Footprint is almost like yes, there's obviously some work from ThoughtWorks, and some [00:40:00] contribution there, but it exists as its own project, and I think when I'm looking up now If I go to GitHub, it's its own organization, so there's like a, there's the implication there that this would be like a community project that, in the long run, would have other organizations contributing and maintaining it, because I didn't know about Resync actually contributing in that way.

That's really neat.

Arik Smith: Yeah, absolutely. That's the stance we've always taken with CCF. I know we mention ThoughtWorks a lot, and that's why we're trying to pivot the language to ThoughtWorks just being the primary sponsor of the tool.

Because at the end of the day, they have invested a lot. Within Cam and I's team and the sustainability solutions team at large to put in a lot of the day to day work within the tool, but everything we spoke about from that initial methodology and building on top of Etsy Cloud Jewels, like there were conversations with Etsy actually being had to get Feedback on the methodology, we're coming up in the okay to move forward that way.

Uh, we've collaborated with cloud providers [00:41:00] themselves to get feedback on the way we're doing things and to see if our estimates make sense. And yeah, even with other organizations on our website, we have a list of innovation partners, which really don't even cover everyone we've worked with that have contributed to the project in some way.

And that's why even on GitHub, it's organized within, at least all the, all of the CCF related repositories are organized within the Cloud Carbon Footprint Organization. Because at the end of the day, it is a community supported and collaborative tool. And I think that's the biggest and strongest part of all is that this isn't a methodology that one organization has owned or came up with, but that the, I want to say the entire industry who really cares about this subject has contributed and promoted growth within.

Chris Adams: okay, so like an open place where there's some consensus to actually figure out, "okay, this is how you measure this stuff." All right, wow.

Alright, we're coming up to time now, so I just want to make sure, are there any things that you folks would like me [00:42:00] to draw attention to, or are there any questions I haven't asked yet that you'd like me to ask or you want to talk about before we come to the end of this?

Cameron Casher: I'll just say that I just want to thank you for letting us speak to CCF. Um, If there's anything that's become more apparent to me recently, it's been the impact that CCF has had in the community and in this domain. And I know we talked a bit about this, but just stressing that we want to hear more from the community.

We want to understand the people using it. So really feel free to reach out to us in any of the ways that Arik just explained, Google or GitHub. And. Yeah, we'd love to talk more and understand about how you're using CCF and one of the things we didn't really get into today was just how CCF can really be like the starting point for a lot of companies because just understanding where you're at in measuring is a first phase of even this Green Ops idea where you get into [00:43:00] understanding, measuring, and then the final act of reducing your carbon footprint. So, we'd like to think that CCF really helps enable that act of reducing, and I know the Green Software Foundation has a lot of great material around where to start, especially around the cloud with the green software pattern.

So, using CCF to have sort of a perspective and baseline of where you think you can start to tweak and make some changes is really a cool and important way to understand how different people are mitigating their carbon footprint in the cloud.

Chris Adams: Brilliant, thank you for that Cam. And to Arik, I realize that I should have asked this at the very beginning, but if someone wants to find out about Cloud Carbon for the project, is there a domain name, is there a website, what would you, what would they type into their favorite search engine or browser?

Arik Smith: Yeah, absolutely. Usually, if you Google Cloud Carbon Footprint, we're appreciatively [00:44:00] one of the first, if not the first, to pop up. But, yeah, you can definitely find us at cloudcarbonfootprint.org. Um, it contains our website, our main documentation, and a breakdown of our methodology. There's also a live demo there, if you don't want to download the tool but want to get familiar with what the dashboard is and the capabilities of it, um, and also links to our GitHubs and some of the community groups like the Google groups that we mentioned is available there as well. Otherwise, like Cam mentioned, we're pretty open, so if you still have a question or want to get involved in some way or even have feedback, which we welcome a lot, feel free to hit us up on LinkedIn or shoot us an email.

Maybe we'll provide a link or something and, or any preferred channel that you can find us on.

Chris Adams: Brilliant, thank you for that. Okay then, and maybe we'll just wrap up there, but I feel like there's maybe one thing that it's really worth emphasizing. If you're using tools like Cloud Carbon Footprint, please do tell the maintainers that they're using them. [00:45:00] Because usually you only ever hear from people when they're unhappy with your product or project rather than when they are using it. And it does make it easier to feel better about your life choices. So that was the last thing I might share with you, uh, because it's something that we actually experience ourselves with CO2.js as well. But folks, I really enjoyed learning about cloud carbon footprint with you here. And, uh, I'm looking forward to some of the cool new things that come up from there.

Once again, thanks again for your time. And Cam, enjoy your skiing. And Arik, enjoy adventures with Link, alright?

Arik Smith: Will do. Thanks a lot, Chris.

Cameron Casher: Thank you, Chris.

Chris Adams: Thanks guys, see you around. Hey everyone, thanks for listening! Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the [00:46:00] Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again and see you in the next episode.

View Details

In this episode we take a look back at another talk from our Decarb 2023 Event while we’re all on the New Year break at the GSF. Titled Driving Climate Change Solutions with AI, Charlotte Degot of CO2 AI and Diana Dimitrova from Boston Consulting Group talk about the Third Annual Carbon Emissions Survey titled Why Some Companies are Ahead in the Race to Net Zero.

Learn more about our people:* Charlotte Deogot: LinkedIn * Diana Dimitrova: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

Topics:* CO2 AI and BCG’s Third Annual Carbon Emissions Survey | Boston Consulting Group [2:55]

Resources:* CO2.AI | CO2AI [1:19] * Boston Consulting Group | BCG [1:19] * Klöckner & Co. [6:00] * Nexigen® Data Services (PCF) | Klöckner & Co SE [6:45] * The Economist Group [8:55] * CodeCarbon.io | Code Carbon [14:53]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
Asim Hussain: Hello and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

Chris Skipper: Welcome to another episode of Environment Variables. Happy New Year, and I hope you are all enjoying this holiday period and looking forward to 2024. Seeing as we're all on a bit of a break here at the Green Software Foundation, we've got another highlight from the recent Decarbonize Software 2023 event.

We'll be showcasing a talk on driving climate change solutions with AI. From Charlotte Degot, CEO and co founder of CO2 AI, and Diana Dimitrova, managing director and partner at BCG. They are introduced by the wonderful Namrata Narayan, director of communications and member relations at the GSF. So it will be her voice that you hear first.

So, without further ado, here's driving climate change solutions with AI.

Namrata Narayan: Now we're going to hear from another steering member, BCG, and their partner, CO2 AI. I'd like to welcome Charlotte Degot from CO2 AI and Diana Dimitrova from BCG. The GSF is focused on addressing the environmental impact of software. With the rise of AI, we wanted to take a moment at Decarb to discuss how this technology can assist our efforts to decarbonize software.

Charlotte and Diana are here to cover this topic and highlight the results from the Carbon Emission Survey Report that was just released. Charlotte and Diana, over to you.

Diana Dimitrova: Great. Thanks so much. And thanks so much for hosting us today. We're super pleased to be here. And as you mentioned, today was the launch date of our third annual survey that actually found some fascinating insights around green software and how that propels climate action globally. So Charlotte and I are thrilled to take you through it.

So maybe as a first step, we can just introduce ourselves. Charlotte.

Charlotte Degot: Yes, very nice to have us, I'm Charlotte Degot, I'm the founder and CEO of CO2 AI. Just in a few words, CO2 AI is a sustainability platform that helps large organizations on their end to end net zero journeys from measuring and reporting their emissions down to reducing and proving their impact.

Diana Dimitrova: Excellent. And, um, I'm Diana Dimitrova. I'm a managing director and partner, uh, in BCG, and I focus on building digital solutions for clients, um, that advance their climate goals, um, that's specifically in our unit called BCGx. I'm going to kick us off with the main findings, um, of the report, and, and let me just contextualize that a little bit.

So, we publish a third annual report around carbon emissions, uh, and measurement. It includes. 1,850 organizations that reported back to us. It does represent over 20 countries in 18 major industries. And based on the reported emissions, it's about 40 percent of global emissions. And the report is called Why Some Companies Are Ahead in the Race to Net Zero.

Now what we found, the unfortunate bit, which is the first column, is that comprehensive measurement of scope 1, 2, and 3 actually hasn't improved. It was 10 percent this year, it was 10 percent the year before, and 9 percent the year before that, so real stagnation there. Now, we did see some elements that gave us quite a bit of hope, and that was really in scope 3.

So in scope 3 measurement has landed at 53 percent or partial scope 3 measurement has landed at 53 percent which is up 19 percentage points in two years. So we are seeing organizations actually be selective of which categories they measure but really starting to get at scope 3. And more interestingly is they've actually set targets and that's the 12 percentage points that you see on the bottom there.

Organizations at this stage are setting targets for scope three categories at 35 percent rate, which is a notable improvement. And regionally, we are seeing changes and we are seeing certain regions pull ahead in the race. And again, this is a scope one, two, and the comprehensive measurement that they have.

South America, APAC are really pulling ahead when it comes to their measurement. And then finally, the most important bit is why are companies doing this? And 40 percent of the folks who responded are telling us, well, they do this because they're seeing a hundred million or more dollars in annual financial benefit when they get on the reduction journey.

So there's a real financial incentive for them to be tackling these massive challenges. And then let me tell you a little of how they did it on the next slide. So these companies are doing four things twice as well as the average organization. The first thing that they're doing well is they're collaborating with their suppliers, meaning they have workshops together, they have joint targets, they have joint programs.

So they're engineering products together for a lower carbon solution. The second bit is Digital solutions that allow you to measure at a product level, so it's not good enough to just know what Apple's total emissions are, it's actually much more interesting to know what the iPhone's emissions are, and getting at that product level is fundamental to enable consumers to make a greener choice.

And the highest number on this slide, as you see, is the use of digital technologies, and Charlotte will give us a few examples of that, but those that adopt digital solutions or green software really make a dent versus those that don't. And then lastly, I heard our host kick it off, regulation, and those that view regulation in a positive way, catalyze around it, really are seeing those benefits when it comes to meeting their reduction targets.

Now, to give you an example, I'm going to take you through a client where we've done this. The client is called Klöckner & Co. What does Klöckner do? Klöckner actually distributes steel. So steel is a heavy emitting sector. It represents 7 percent of the world's emissions. We all have a stake in the ground to really decarbonize steel.

Unfortunately, there is no net zero steel, but there is a lot greener steel than what we use on average. What Klöckner did is recognize that they needed to get to that product carbon footprint element, which is the second pillar I just talked about. So they actually built a software that was able to calculate their product carbon footprint for over 200,000 products, and you see that's called Nexigen PCF algorithm.

It's cradle to gate emissions. And it covers, as I said, 200,000 products, and it is certified, which makes it really important that whoever gets a number actually gets a certification. And then they decided that wasn't good enough, they needed to push a little bit further, and then they created Nexigen Data Services, which is an online purchasing platform where anybody who's buying steel can log on and look at what the carbon footprint of their basket was in the last purchase, and how, what greener alternative is available to them.

And so this platform allows procurement individuals to actually really arbitrage where they're going to spend their carbon because they're given the transparency and the choice to make the lower carbon solutions. So it's a great example of leveraging technology and getting at product carbon footprints, which is still a bit of a panacea that organizations are gunning towards.

Having said that, I'm going to hand it over to Charlotte and she'll take us through some of the other details on digital.

Charlotte Degot: Yes, thank you. So, as Diana was saying, one of the four key things that companies will succeed better on their reduction journey do is adopting digital solutions. As you can see on the left part of the slide, what we see is that companies who use automated digital solutions are actually two times 2.5 times more likely to comprehensively measure their emissions.

And this is very important because what gets measured gets done. This may look like a basic, but it's a basic that just sets the foundations right for you to then decarbonize. And what's also encouraging is that when we ask the 1,800 companies who answered our survey, what is the number one enabler that they see and that they think they need to adopt to accelerate on emissions reduction, they quote, technology, uh, as the first enabler.

Before leadership buy in, before sustainability focused, uh, culture. So it really means that they have, uh, perceived the importance of digital and that, uh, we can hope for a wave of adoption in the years to come.

I just want to give you one example from real life of what it means to be using tech and how it can bring value to a very large and complex organization. We are talking here about The Economist Group, so the press media group as they are very large and they, um, they issue a lot of newspapers. They are very committed to sustainability and what they do with technology is using CO2 AI to help them steer their end to end net zero journey. So what they use it for is first to measure and automate their carbon footprint calculations. They have a very complex carbon footprint. They need to capture a lot of data points, and CO2 AI helps them collect those data points, structure those data points, and get to a level of granularity in their footprint, which is really good and really helpful to make decisions.

The second thing that they do with CO2 AI is to really set up a road map. And define the hotspots and the reduction levers that go with the roadmap so that they really have a plan and they can cascade the plan across the organization. This is a big pain point that sustainability face team, um, sustainability teams face today.

They tend to have targets, but high level plans and no resources to actually make that happen. Technology can really help broadcasting the information, make sure that operational teams get involved into the decarbonization journey. And last but not least, as we were saying, scope three. So the emissions that come from outside the direct operations of the company, typically the emissions from the supply chain, the suppliers, et cetera, are, um, extremely important.

They are on average 90 percent of total emissions. And those are the hardest to tackle. What The Economist is doing with CO2 AI is mapping suppliers and being able to really prioritize with who, with what suppliers to engage and what to discuss with them to go at a level of granularity. We were talking about product level at a level of granularity, which is good enough to have proper discussions about reductions and, and impact measurements.

Finally, I want to say a few words about AI before taking questions. We talked about tech and digital in a broad sense, which is extremely helpful and will drastically help us accelerate on our sustainability journey. In this field, artificial intelligence is Extremely important. You see here on the page, 30% of respondents who plan to adopt AI, uh, to, uh, steer their net zero sustainability and journey moving forward.

Uh, they see artificial intelligence and, uh, as an enabler and a helpful way on many that different dimension. Uh, a couple of ones are making intelligent decisions. Typically on energy usage or decarbonization initiative. Artificial intelligence is a key lever to automate and increase the quality of carbon footprints.

This is what we do at CO2 AI, and I could talk for hours about that, but there is a huge accuracy issue and granularity issue with carbon footprints. On carbon footprint when made manually, and artificial intelligence can really help solve this topic. And finally, making predictions and making sure that roadmaps ahead, both from a business and from a sustainability standpoint, are optimized.

So we're reaching the end of our presentation. You have two QR codes here to go deeper into either the report or what we do more generally. And I think it's time to take questions.

Namrata Narayan: Thank you so much for sharing. I know we've got a ton of questions to follow up with, but first, I do see we've got a few audience questions, so I'm going to ask you both. The first one is from Jean Luc Bonnet, and he's asking about the baseline. He said two times of 10 companies is not so great, but two in 100,000 companies is a great achievement, so could you comment on that?

Charlotte Degot: I think the question is related to the four levers that accelerate and that multiply by two the likelihood of managing your reduction journey. So what I can say is that what we ask for in the survey is what percentage of companies are measuring the emissions comprehensively. And as Diana was saying, this has not moved and this is stagnating at 10%.

And the other key metric that we asked for in the survey is how, what percentage of companies have actually managed to reduce their emissions in line with their ambition. And here this number is 14%. So I will I will see the glass half empty on this question, and I will say that the baseline is not high enough, and we need to really accelerate the adoption of those four levers, and that will increase the baseline.

Namrata Narayan: Thank you so much, and then we have a question with regards to the carbon emissions survey, a couple which I'm going to you know, group together. So, one is, how many companies were part of the survey, and did the survey find any advice regarding how to decarbonize AI itself, since it's also a cause of emissions?

Diana Dimitrova: Great, so let me take the first part and Charlotte, I think you can comment on AI itself. So it was 1,850 organizations up from 1,600 last year and up from 1,450 the year before, so we have been seeing a steady interest in folks giving us this information back and the sample is hoovering for some of the kind of large organizations that are between 10 and 25,000 employees, and it said based on their self declaration it was 40,000 percent of global emissions, so we're quite comfortable with the sample that came through this year.

Charlotte Degot: And on, uh, uh, how to reduce the footprint of AI, this was not part of the questions we've been asking, uh, on the survey, but what I can say is that, um, there are, uh, many ways to optimize the carbon emissions of any model. Also, tools that exist like CodeCarbon, et cetera, I'm not going to teach anything to this group about it, but clearly, the impact of AI needs to be monitored as any other type of impact, and it needs to be used wise.

Namrata Narayan: Well, Charlotte and Diana, thank you so much. There are several more questions, so we might have to come back to you at a later time to get them answered. Thank you so much for joining us at DeCarb.

Chris Skipper: So, that's all for this episode of Environment Variables. If you liked what you heard, you can actually check out the video version of this on our YouTube channel. Links to that, as well as everything that we mentioned, can be found in the show notes below. While you're down there, feel free to click follow so you don't miss out on the very latest in the world of sustainable software here on Environment Variables.

Bye for now!

Asim Hussain: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show and of course, we want more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. Thanks again and see you in the next episode.

View Details

TWiGS host Chris Adams is joined by guest Savannah Goodman from Google, to bring you the latest news and updates from the world of sustainable software development. They discuss insights from Google’s Sustainability report, the need for a fossil fuel free internet by 2030 and the importance of microgrids and nanogrids. They also highlight Google's sustainability tools including Cloud Region Picker, ActiveAssist and Carbon Footprint.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Savannah Goodman: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

Topics:* We need a fossil fuel free internet by 2030 | Branch Magazine [6:38] * Tesla Megapack | Microgrids & Tesla [12:27] * Google Sustainability Goals | Google [21:19] * Google & Fervo Geothermal Partnership | Google [22:58] * Google Cloud Region Picker | Google [26:44] * Google Active Assist | Google [29:20] * Google Carbon Footprint | Google [30:13] * The Realtime Cloud Project | Green Software Foundation [32:15]

Resources:* Octopus Energy [15:04] * The Week in Green Software: Modelling Carbon Aware Software | Environment Variables episode with Iegor Riepen at TU Berlin [20:07] * UN Global 24/7 Compact | UN [24:46] * Vincent Poncet LinkedIn| Linux Foundation [32:08]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

**TRANSCRIPT BELOW:

Savannah Goodman:** [00:00:00] While it's important for us to reduce our own carbon footprint, we think the opportunity to provide these flexibility services to the grid will actually help drive broader system decarbonization and allow for broader carbon emission reduction.

Chris Adams: Hello, and welcome to another episode of This Week in Green Software, where we bring you the latest news and updates from the world of sustainable software development. your host, Chris Adams. when we talk about green software, whether you're diving into papers about carbon aware computing. or hearing someone talk about GreenOps, a new [00:01:00] variation of the term DevOps, or even as a consumer, looking at the work that the company's been doing to make it easier to understand how you can reduce the carbon footprint of things like flying. It's hard to escape the work of Google when you look at climate and tech. be honest, it's not that surprising. They operate at a scale that's hard for many of us to really comprehend. Alphabet, the holding company for Google, has a market capitalization of 1. 75 trillion dollars these days. And they use enough digital infrastructure to really care. Their own sustainability report in 2023 shows that Google used something in the region of 22 terawatt hours of electricity last year. This is not a small company. Since 2007, they've generally been one of the leaders when it comes to decarbonizing infrastructure. And recently, they set a public goal to match every hour of power they use with an hour of generation from carbon free sources by 2030. This is something we've seen a [00:02:00] number of organizations get behind, and even the UN with their recent 24 7 compact. So we know there's a lot of smart people working at Google, working on the greening of digital. And today, I'm joined by Savannah Goodman from Google to talk about the finer points of doing green software at scale. Hi Savannah, the floor is yours to introduce yourself.

Savannah Goodman: Thanks, Chris. Hi, everyone. I'm Savannah Goodman. I lead the data and software climate solutions team at Google, and I'm super excited to be here. I'm an energy nerd at heart, and I've been studying and working in the climate space for the last decade.

Chris Adams: Thank you, Savannah. Okay, so if you are new to this podcast, here's a quick reminder of how it tends to work. Uh, When we mention projects or papers or any links like that, we'll add them into the show notes. And if there's a thing that you heard us talk about that you'd really like to learn more about, please do leave a comment.

It really helps other people who are trying to actually learn things about this as well. The other thing I should probably do is introduce myself. My name is Chris [00:03:00] Adams. I work at the Green Web Foundation, a nonprofit focused on reaching an entirely fossil free internet by 2030. And I'm also one of the chairs of the policy work group inside the Green Software Foundation, which Google is also a member of. All right. I think that's pretty much it. Savannah, if you're happy for us to go and sitting comfortably, shall we start?

Savannah Goodman: Yeah, let's go for it.

Chris Adams: All right. Okay. So we're going to talk about some of the cool carbon intelligent computing stuff that Google does shortly, but before we dive into there, I figured it might help to talk a little bit about how you got here first, because as I understand it, you've worked with technology that interacts with grids at various scales in your career.

And if we start at the small end, I realize that if you're going to be talking about data centers, it helps developers to understand some of the principles that are behind the kind of power grids in the first place. And this is something you worked on before. And I think what I learned about was there was a project that you worked [00:04:00] on previously with the idea of an off grid internet cafe in a box.

This seemed too cool to not ask you about basically. So I should ask, how did this come about before you worked at Google?

Savannah Goodman: Yeah. Yeah. Thank you for asking. It was a super interesting project and happy to get the chance to start small and then go all the way to data centers. But yeah, I was in grad school and I was interning at a company that was focused on improving energy access in East Africa. And they were working on a couple of different products for pretty specific applications and they were really tailored to the needs of the local communities that we were working with.

So just a few examples, they had very small microgrids, you'd maybe almost call it a nanogrid to provide lighting at night or to charge a few cell phones. So really small kind of mobile solar and storage. And during their research they identified one of the other kind of key pain points in these [00:05:00] communities was the need for better and more reliable internet access.

And while some internet cafes existed in the cities, they could be cost prohibitive, they may be very far from some of the local communities, and oftentimes they were actually unreliable because of grid reliability issues in the region. And so my job was essentially to do the research and propose what an off grid internet cafe in a box might look like as a product, and how it could actually solve the pain points in these

from these local users. And so I did a lot of really interesting landscape research, developed some product specs, and ultimately also came up with the business case. And I think what I really liked most about this project was the fact that it had a ton of potential impact. I was really excited about the idea of enabling information access for everyone, not just folks in developed countries and big cities, and especially through more [00:06:00] reliable clean energy access.

Chris Adams: It's actually timely that we're having this conversation now, just after COP28, because we've seen a few specific announcements that tie into this, actually, things like this goal of tripling renewables globally, for example, by 2030. And there's actually, it's interesting that you talk about some of those things there, because T that was maybe a few years back, and I want to ask you, if you were to come back to this, were there any trends that you saw back then that you might have seen playing out that you'd probably look for immediately, or you'd probably want to dive into if you were coming back to this?

Because you mentioned some things like nanogrids, and the idea of moving past basically fossil based generation, because we know in lots of places, like for example Nigeria, You still have two thirds of the power is coming from generation rather than the grid. So it's extremely dirty power compared to what you have now. Maybe I'll just give it a bit of space for you to say what you would be looking for, what you're excited about seeing over the next few years in this particular field.

Savannah Goodman: Yeah, thank you. It's definitely some really interesting trends and a [00:07:00] lot has changed even since I was in grad school. And I think one of the first things I remember thinking about is how big, right? What is the optimal size of a microgrid? I mentioned this term nanogrid, which was, like I said, a few solar panels, a small battery that was very mobile.

I think that that sort of solution can target a few very specific and acute pain points, but didn't necessarily, I think, scale to the level that these companies were looking to have, especially given the impact that they wanted to drive. So I think one of the interesting trends we've seen is maybe moving from these nano grids towards more true micro grids that can enable multiple applications and are not necessarily mobile, but actually require more robust grid infrastructure.

And so that's something very interesting and especially in the context of the developed region, especially in the U. S. where I'm from, grid infrastructure is a very big focus right now. And I think it'll be [00:08:00] really interesting to see how we can take some of the learnings of how we've grown our own grid infrastructure and hopefully leapfrog in some of these areas that don't quite have the existing distribution or transmission build out.

Certainly a challenge as I don't think we've fully figured it out for ourselves, but there's definitely a lot of lessons learned along the way. So I think that's . Something really interesting that will play out. Another area that always really stood out to me was the energy and water nexus. And this is something that is really important in a lot of developed countries where there's also a lack of clean water access.

And there's been a lot of kind of technology development over the last decade, and I'm sure there will continue to be. And I think the challenge with this is more, again, the kind of go to market of those products. How do we actually ensure that these products fulfill really specific needs and have an appropriate business model that actually meshes well with the type of [00:09:00] communities that need it most.

So that's an interesting one that I'm really curious to see how this will continue, especially as there's more and more focus on the global south and adaptation for climate change, which is closely tied both to water and energy as well. And then the last thing.

Chris Adams: Oh if I can just stop you there, you said you introduced this term, which some other listeners might not be so familiar with. You mentioned the energy water nexus. Could you maybe expand on that a little bit? This is the idea that basically generating water uses energy, but there's also a flip side to that.

Could you maybe expand on that? Because I think that's quite an interesting topic

Savannah Goodman: Yeah.

Chris Adams: up some people's ears actually.

Savannah Goodman: Yeah, definitely. And, um, I think there's, yeah, this sort of exciting concept of the fact that energy and water are two absolutely necessary resources for thriving communities. Like you said, you can, you need usually energy to make water accessible, especially to make it clean and to make it drinkable and portable, right?

There's usually some sort, usually using [00:10:00] electricity to do that can be really effective. There's other ways to do it without electricity, but it's a lot more challenging to have infrastructure that scales and is robust enough. The flip side too is water can be a really great energy source. We think of pump storage and hydro, and that's really important for providing clean, dispatchable resources.

Of course, hydro is very dependent on the weather and the climate, and as climate changes, it can become actually a less reliable resource. And so there's just a lot of interesting intersections there. We can also think about the climate impacts and droughts and how that might impact both water access for drinking, but also for energy.

So, it's a generic term, but it's intended to capture the fact that there's actually a lot of intersection and dependencies between these two fields both ways, and I think it's a really important focus area, right, as we think about you know, impacts on the climate and how communities are going to need to adapt.

Chris Adams: Thank you. That's really useful. I [00:11:00] didn't, I've been looking for a term to describe some of this and this immediately makes me think of, say in France or in Germany, where we saw in the heat wave last year, for example, we saw some of this, we saw the reliance on water from things like say nuclear power stations in France, for example, which were essentially. They end up having to come offline in some cases simply because they didn't have enough access to water to actually keep them cool, for example. And this is something that a lot of us don't really think about necessarily in the first place. Okay. It's power, but where does the water fit into this? But flipping, that's actually a really good example of some of this. Okay, cool. So we spoke a little bit about grids. You mentioned that there's like nano grids and say slightly larger grids, like a micro grid. It's worth moving to there, actually, because I understand that when you were working at that company, then you've also worked at Tesla working with microgrids. And when most of us think about, say Tesla, they might think about electric cars more than microgrids. And in fact, I suspect that most developers might not have heard what a microgrid actually is. So for people who are not familiar [00:12:00] with the term, you maybe just explain what a microgrid might actually be? And just to give people some context, because we'll talk about how this relates to data centers a little bit later, but in the short term, maybe you could just briefly provide a kind of microgrid 101 and why you might care about it, why an electric car company might care about some of this, because that will probably be useful context when we talk about data centers and how they integrate with grids and stuff like that.

Savannah Goodman: Yeah, absolutely. So a microgrid is a localized group of energy sources and loads that can typically operate independently of a larger grid system. And so this sort of independent network of resources can be useful for a few reasons. First, microgrids can improve energy security and reliability. They tend to be less vulnerable to large scale outages because they can usually kind of disconnect or what we might call island and continue to [00:13:00] operate even if the main grid system goes down.

So this is especially beneficial for critical loads. So oftentimes hospitals or emergency shelters may have their own kind of generators and may be able to create their own sort of micro grids. Further, microgrids can actually help reduce, you know, the cost in carbon, uh, depending on the situation. So, for example, a lot of island nations typically have some form of microgrids.

Because they're not physically connected to large land areas that have the privilege of having these large scale grids and a lot of infrastructure and robustness. And so while a lot of these island microgrids have historically relied on diesel generators, they can instead integrate wind, solar, and batteries, which can then actually reduce the cost compared to diesel, importing diesel, and will actually reduce the carbon emissions.

So that's another big advantage of, or opportunity for microgrids. And to answer your other question on [00:14:00] why companies like Tesla might have incentives to build batteries for the grid, it's really a way for them to scale their battery production for EVs. So Tesla Energy was created actually a while back and it really helped drive down the costs

of manufacturing batteries at scale, and it also has the, you know, added benefit of actually creating new business value, new business lines for the company. And the other thing I would say is there's also some really interesting synergies between electric vehicle charging and using grid connected batteries to manage consumption spikes and, and some of the charging costs.

So when Tesla deployed the supercharger network, they also looked at deploying grid scale batteries at those charging networks to help manage the costs that they were paying to the electric utilities. So it not only can be a business line, but batteries for the grid can be used to help manage their overall kind of infrastructure costs for the [00:15:00] EVs.

Chris Adams: Ah okay, so that makes it a bit clearer for me to understand, and also this makes me think of some of the stuff we've recently seen in the UK, for example, there's a company called Octopus Energy, they're an energy company, and they basically They have this new deal working with people who are building homes and they have this kind of this deal basically if you have batteries or renewable energy fitted into the house when it's being built they're offering zero energy bills for the next for the first five years as long as you're able to make the house integrate into the grid and it seems to be like you said because sometimes energy is expensive when there's, it might be cheap when there's lots of renewables on the grid.

For example, it's taking advantage of some of that and storing energy when it's cheap and then using it locally rather than having to buy expensive energy from the grid and vice versa. Ah, okay. That helps me understand that now. Thank you. you said something else, actually, about the fact that you've got grids which are interconnected.

So they're independent, but they're connected in some ways because there's a larger thing. This made me think a lot about the internet, actually, how the internet is [00:16:00] basically made of a series of smaller networks which are interacting with larger networks. So there's some parallels there. And I can imagine how some of these ideas might scale all the way up to something like a large hyperscale data center. I suspect there's probably a bit more to it than that. And I guess this is probably where the work that you've been doing with Google might come in, actually. So for folks who are following along for the ride, when you're talking about, say, hyperscale data centers versus micro grids or small grids here, what are the differences when you're working at that different kind of scale, for example?

And is this idea that, okay, you've got a series of small grids connected. That's a little bit like the internet. Is that a comparison that you could really make? Well, maybe you could just expand on that a bit more. Cause that's what I immediately think about when you talk to me about series of grids connected to each other, for example.

Savannah Goodman: Yeah, I think that's a great analogy. Like you said, the internet is made up all of these different kind of nodes and is really a network of nodes and connection points. And that's [00:17:00] exactly what the grid is. And some areas are better connected, right? They have more interconnectivity and nodes, and that can make them more reliable than others.

Also similar to the internet, because there's this network and different demand and supply pockets. There can be congestion of just like there may be network congestion for internet or data transfer. There can be grid congestion for the flow of electrons. And so keeping this in mind, as I alluded to earlier, there are a lot of opportunities to really better optimize the grid when you have

flexible resources, whether it's EV charging or storage for the grid. This flexibility makes it a lot easier to manage the grid during peak times. The example you, you mentioned with Octopus, I think is a great one, where they're fully recognizing the value of having flexible grid to the point where they won't even charge you for the energy because they know that's really important for the way they manage their portfolio.

And so for data centers, the way that we [00:18:00] contribute to this load flexibility is we can actually shift our compute load. And we can do that in response to signals from the grid in specific locations, where there may be congestion or during kind of the peak times of the grid. And this is what we would typically call demand response.

And just,

Chris Adams: Ah, okay.

Savannah Goodman: yeah, and it's- Demand response has actually been around for a long time, but what's really, I think, new and innovative about what we're doing at Google is leveraging compute demand to be able to participate in these demand response programs. Historically, demand response has typically been from industrial factories who are turning down their manufacturing or from thermostats, right, who are turning down the heating.

But what's really great about compute load is that it's a virtual load. And so the fact that we can shift it not only in time. But also in space is really, um, the unique part of, of, um, compute. And we've [00:19:00] actually been shifting compute at, at Google for a few years now. Historically, we were shifting in response to a carbon intensity signal from the grid.

In order to minimize our own carbon emissions. And for demand response, we do it a little bit differently. We will typically receive a notification from the grid operator, or we'll agree on the local peak time. And then we dispatch our kind of global compute planning system to overwrite that existing schedule that was carbon optimized.

And that basically limits non urgent compute tasks for the duration of that event at the data center. And I think we're really excited about these capabilities because while it's important for us to reduce our own carbon footprint, we think the opportunity to provide these flexibility services to the grid.

Will actually help drive broader system decarbonization and allow for broader carbon emission reduction through enabling the increase in clean [00:20:00] energy and just being able to turn down load when the grid is being supported by gas peakers, for example.

Chris Adams: I see. Okay. So for people who may have listened to this before, we, we did a podcast with, I think, I believe his name is Igor Repin at the Technical University of Berlin. He was talking and going into quite a lot of really nerdy detail about how some of this stuff was modeled on the European grid to explain this and saying, if you're able to smooth out these kinds of spikes, then you don't need to actually have quite so much infrastructure in the first place.

Or it may be that you don't need to have things like, say, as many peaker plants, often tend to be very carbon intensive and tend to burn a lot of fossil fuels. I see now. All right then. So maybe we can actually just talk a little bit about this being part of a of broader strategy. So we spoke a little bit about there being a kind of target to be entirely fossil free by 2030, for example. Is it a chance we could maybe just dive into some of that a bit more? Because for most of us U understanding [00:21:00] why you'd have a target to be running entirely a fossil free energy by 2030 might not be obvious to everyone. And sorry, I think the term that Google uses is carbon free, but basically this idea of you want to have things running 24 7 rather than just saying, having an annual kind of claim, for example. Could you talk a little bit about some of that and what some of the thinking behind that might have been?

Savannah Goodman: Yeah, definitely. So As you mentioned, Google has two main climate goals. One of them is to be net zero by 2030. The other is to be running on 24 7 carbon free energy by 2030. And just to clarify too, 24 7 carbon free energy is much more complex. Than the annual matching schemes that have been most common to date, because we're essentially moving from global annual matching to local hourly matching.

And so you can imagine how, especially over a global, uh, system, how complex that gets and there's no playbook. But we see these goals as a way to actually help scale new [00:22:00] global solutions that drive broader system wide decarbonization because we're actually aligning our own goals with what the grid needs.

Through these hourly local matching, that's how the grid operates, right? It operates, you have to have local constraints. You have to match supply and demand every hour. And so we've seen research from folks like TU Berlin and Princeton and the IEA that show 24 seven procurement is one of the best ways.

For corporates to help accelerate the energy transition towards grids operating on clean energy every hour, every day. And for 24 7, load flexibility is really complementary because it provides this nhe gew sort of flexible resource that can help us better match the clean energy that's on the grid or the clean energy that we procure on a local hourly basis.

So we're also looking, besides load flexibility, at other new next gen technologies like geothermal. We've [00:23:00] announced the starting operations of our geothermal plant with Fervo in Nevada. We're also really excited about battery storage. And there's a lot of other technologies that we're looking at, and research shows that having this diverse portfolio, both of Load flexibility and next gen technologies is what can make 24 7 more cost effective and more accessible and actually meet the grid needs, especially when we consider rising demand in electricity from things like electrification and data center growth.

So, so yeah, all of this demand response effort is really a key part of our kind of sustainability strategy, and we've recently announced a couple of pilots to prove out that this is real, this can work, it has benefits for us, it has benefits for the grid, and we're going to continue to evolve our capabilities and work with our utility and grid operator partners to make sure that we're maximizing the shared impact [00:24:00] of this system.

Chris Adams: ah, okay. So it sounds like rather than just we're saying I'm going to buy a green energy tariff and that, it's all more I want to shift the entire paradigm that the grid actually operates on. And I know that Microsoft have also come on board, but they're not going to call it 24 7, of course, because that's what's called by the competitor.

So they're using the term 100, 100, 0. I think it's 100 percent of the time. Coming from a hundred percent renewable energy or zero carbon. It's something like that. It's not as easy to remember as 24 seven, but that's one thing we've seen. And we've also seen the federal government. I believe they've made us, they made it last year, actually saying they're aiming to have by 2030, 50 percent of all of their power. And that's the entire federal government, not just a single company, for example. So that was like another example of this. Okay, cool. And I think we might have alluded to this. This is actually a kind of wider scheme. The UN has this global 24 7 compact that any organization can sign on to and get on board with as well, I think, right?

Savannah Goodman: Yeah, exactly. And we're really excited to see during COP that the US government officially also [00:25:00] signed on to the compact. There's over 100 signatories at this point. And I think what's most exciting to me is that it is really a community of different kinds of companies and organizations from all across The energy sector that need to come together.

So there's some energy buyers. There's energy suppliers. There's governments. There's cities. There's software and data providers. There's hardware providers. And I think we're not going to do this alone. But what we're really excited about is creating this ecosystem And developing technologies to advance that ecosystem so that we can all collectively work together to meet the ambitious decarbonization goals for the grid that are really needed to enable the broader climate targets for 1.5 degrees.

Chris Adams: I see. Okay. All right. Thank you for that. So we've spoken a little bit about data centers and how flexibility there can actually have some kind of impact inside this. And we spoke also a little bit about, [00:26:00] uh, the kind of wider context of why you might think about this in terms of decarbonizing a grid. This gives a bit of visibility there, and you spoke about some internal things. Maybe we could talk a little bit about some of the things that end users of services that, say, Google might offer, might use, because we've got a lot of developers who use, say, Google Cloud Platform or even other such platforms as well, and I know that I've used some of Google's tools previously, and I know that there's some projects inside the GSF, the Green Software Foundation, that talk about this and are contributing to that, but maybe you could just tell touch on some of the tooling that you've seen in use or made available for end users, because there's a couple of cool things, which I think are worth develop, worth some of our listeners not knowing about.

Savannah Goodman: Yeah, absolutely. And just to set the context right now, as part of our Carbon Intelligent Compute or our demand response programs, we're not actually shifting customer workloads. We're focused first on shifting some of the internal workloads that operate Google [00:27:00] products like YouTube videos and things like that.

However, we're very keen on exploring with customers who are interested in reducing their footprint to shift their customer workloads. In the meantime, we've developed some tools that can help these cloud customers reduce their carbon footprint themselves. And so, just to talk through a couple of the different tools, one of the first ones we launched was called the Region Picker.

The Region Picker allows customers to look at all of the different kind of characteristics that they may want to optimize for, in particular, latency, cost, and then carbon footprint. And based on,

Chris Adams: Hmm.

Savannah Goodman: you can essentially adjust the weighting of those different Aspects, depending on what is most important for you and your business.

And based on that, the tool will actually provide you a optimal region or a set of optimal regions to site your new workloads in. And this tool, we've also embedded [00:28:00] the essentially green leafs into the cloud platform. So when customers are choosing regions, they can actually see which ones are cleaner.

by based on meeting a certain threshold of carbon free energy. The reason we started with the region picker tool is through our own analysis and data we've seen that one of the most, pretty much the most impactful factor when siting workloads is location. So, eventually we'd love to be able to shift workloads in time as well for customers, but this spatial sort of shifting or site selection is really impactful because customers can move their workloads from a dirty to a clean grid, and that makes a really big difference.

Chris Adams: So the region picker, for people who haven't seen this before, as I understand it, when you're using this, it basically gives you an idea of saying if your audience is in Germany, rather than running it in say, one part of there, you might want to consider looking at Switzerland. Who are still in the same place, but have much, much cleaner power, for example, [00:29:00] and still would be staying inside your latency requirements is tools like that.

And that's the kind of stuff that I, uh, that I saw. And I think that's the first time I've ever seen any large organization sharing some of that stuff. So that is included in active assist now, or some of the tools inside Google. Is that what you were saying?

Savannah Goodman: Yeah, that's exactly right. That's part of our region picker tool. The active assist tool can help customers reduce their footprint in a slightly different way. So the focus of the active assist tool is, let's say customers have some projects that have just been running in the background. The ActiveAssist tool can recommend automatically certain optimizations, could turn down a project, or minimize the runtime of a project, which will not only help reduce cost, but also reduce carbon.

So the ActiveAssist tool is using machine learning and AI to serve predictions and recommendations for cloud customers.

Chris Adams: So the active assisting, so it's a bit like, so yes, there's AI and things, but it also just tells you, by [00:30:00] the way, mate, you've left your computer on, or you've left this project running. Maybe you want to turn it off if it's not serving any traffic, because this is one thing that comes up. It'll basically do some stuff like that, as well as providing some specific, much more tailored recommendations as well.

Yeah?

Savannah Goodman: Yeah, exactly. That's right. And then the last tool that we've developed is called Carbon Footprint. And this is really a reporting tool. There's also some kind of insights that customers can glean to optimize how they're setting up their infrastructure. But this is the rounding out the suite of tools we developed.

It helps customers understand what their actual carbon footprint is from the use of cloud services. So as they make changes, They can see how that impacts the trends of their carbon footprint over time, and they can also use the data for their own corporate reporting. Usually the use of cloud falls into a customer's scope three, indirect emissions, and so this is an important, an important [00:31:00] reporting tool for our customers to be able to meet their reporting needs.

Chris Adams: I see. Okay. And this is something that is just built into the system from day one, or is it part of something you need to purchase separately, for example?

Savannah Goodman: So this tool is available and free for everyone in the cloud console, can access it directly and it's organized per billing account. You can see pretty granular data too, per month, per project, per region. So there's a lot of different ways you can slice and dice the data. There's also a data export, right?

If you want to integrate that data directly into some of your own dashboarding and marry it with other kind of cloud operations data. So yep, it's free and available for everyone on Google Cloud.

Chris Adams: Cool. Thank you for that, Savannah. All right, then. So I know that you work for a specific vendor, and I am mindful of us spending too much time talking about this, because I know that, I can see why it's useful for one company to share this visibility. And from the perspective of a non profit, I'm glad that there's one company pushing this stuff and has been. forthcoming sharing this information compared to some of the other providers in this [00:32:00] kind of space. And I know that from speaking to one of your colleagues, I think Vincent, I never pronounce, I'm going to pronounce, mispronounce his name, Ponset or Ponset. He's also, he's been involved in some of this as well.

And I met him at the Linux Foundation at LF Energy Summit in, in, in Paris, basically. I understand that there's a project called the Green Software Foundation Real Time Cloud Project, which is, being led by both Adrian Cockcroft and Pindy. I, oh, Pindy, I totally forgot your surname, but there's, we have a couple of people inside the GSF who are members who are leading on this, maybe we could talk a little bit about why that's important and why as a member of GSF, you've been involved in some of these projects to create some kind of consistency and conventions around this data that gets exported or exposed to customers.

Savannah Goodman: Yeah, definitely. So we've heard from our customers that the data we're providing is super helpful, but they also need more, more transparent data that's consistent and comparable across their cloud providers. [00:33:00] Often customers will have multi tenant use cases and will have multiple cloud providers. And so it's really important that we can provide more accurate data, more transparent data and comparable data to help them, like I mentioned, with their reporting needs.

And to also make better informed decision for taking action within the cloud environment on how to reduce their carbon emissions. And so we're really excited to be working on the cloud project with Green Software Foundation. Um, that's looking at two main use cases for the project. The first one is this emissions reporting, and the second one is really carbon optimization.

Ideally, these two use cases would be tied closely together, but in reality, because of the way the current accounting and auditing systems work, the reporting Use case typically has a significant lag in the data. And so we're hoping that this project will enable better standardization across metrics for better comparability for reporting.

But at the same [00:34:00] time, we think there's a lot of opportunity to provide more real time, more accurate data for the optimization aspects. And so we're hoping to develop methodologies and tools that can enable cloud providers to offer this more granular and realtime Data. That will support the carbon optimization use case in the near term and then ultimately with the goal of reducing the lag of carbon reporting in the long term . So we're super eager actually to explore working with our cloud customers and seeing what tools are most useful for them, what metrics, how can we help them optimize their carbon footprint, whether it's in an automated way.

Through our own carbon intelligent compute system or through the tools that we're providing through the console.

Chris Adams: gotcha. Okay. Thanks for clearing some of that up. And I know that because I'm also in that working group right now, I can actually speak to you and say, quite honestly, that some two years ago, Google started publishing some of the information at a kind of region by region basis, showing [00:35:00] like the carbon intensity or like the amount of power that is considered carbon free for every single region, um, sharing it as like a CSV on GitHub. This has actually been really helpful to provide a kind of starting point for sorting out some kind of consistent metric, consistent way of reporting this or requesting this from different providers. Cause we know that Amazon has a cloud calculator and Google has a cloud one and Microsoft have one, but having a consistent thing to refer to has been really helpful for this and it's made it quite a bit easier to then say. For example, I'm glad that Google has been one of the earlier companies to talk about information, emissions across all three scopes, scope one, two, and three. And this is something that we don't have from all the providers right now. So being able to point to an example and a data set has been really helpful in this scenario here. I wanted to ask you, coming to the end of the time for this chat, and we've spoken a little bit about like changing some of the kind of paradigms around, rather than basically just buying green energy, like essentially changing how [00:36:00] people think about using power to actually incentivize more carbon aware or approaches for reducing the emissions associated technology, for example. I want to ask you, is there anything that you'd like me to draw attention to? Or you, you reckon we should talk about as well, because we've covered quite a ssions ssions lot of ground from like nanogrids all the way up to ginormous data centers that use as much power as small cities, basically. So what else are you looking at or what else would you like to draw people's attention to right now in this field?

Savannah Goodman: Yeah, I think overall we're super excited about the potential for green software to reduce emissions. I think there's a lot of different ways that we can go about making software more green, whether it's through our hyper scale carbon intelligent compute type platforms or even individual developers choosing cleaner regions for their workloads.

We're really optimistic about how these solutions can come together to enable broader capabilities across the GSF community and beyond. [00:37:00] We think that load flexibility is such an important part for the future of the grid and we think software has some really unique Flexible capabilities that other kind of loads don't necessarily have.

And so, that's why we're really thrilled to be part of this community to see how we can really maximize the, you know, level of flexibility that green software can offer to really help drive the energy transition at the broader grid scale and reduce carbon emissions.

Chris Adams: Brilliant. All right, then I think we're coming up to the end of our time. So I just want to ask if people have, if their interest has been peaked by any of this, where would you suggest people look, or if people were interested about what you're doing specifically, where would you suggest people look to follow on for updates about what's taking place in this field, beyond the projects we just mentioned, like the real time cloud thing in GitHub, or like Google's account on GitHub, for example, or some of the other things. So maybe, let's say I'm a developer. I'm [00:38:00] curious about some of this. I don't know where to look. Where should I be looking to learn more about this or continue my research?

Savannah Goodman: Yeah, definitely. So we publish quite a few updates through the sustainability topics in the Google Cloud blog where you can see the updates on the latest work and not just for green software, but a lot of the different sustainability areas that we're developing new technologies for. If you're interested in learning more about kind of Google's overall strategy, not just cloud specific, Sustainability work, then google.com/sustainability

. It's a good place to start. That's where we publish all of our papers and annual reports. But yeah, otherwise, we definitely recommend the Google Cloud blog and following the sustainability topic. Lots of exciting updates to come.

Chris Adams: Brilliant. Okay. And what we'll do now is we'll just try. And if, if you're a listener and you've listened to some of this and you caught your eye, we're going to take a moment now to just get as many links as possible to all this stuff that we've spoke about, because we've covered a lot of ground. All right. Savannah, I've enjoyed this. I've learned [00:39:00] a lot and I think our listeners probably have as well. I want to wish you have a lovely week and yeah. Have a lovely winter break. If you're, if you celebrate your time away over winter.

Savannah Goodman: Thank you so much. Have a good one.

Chris Adams: Okay. Cheers.

​[00:40:00]

View Details

From the recent Decarbonize Software 2023 event, this episode showcases a fireside chat on Responsible AI with Tammy McClellan from Microsoft and Jesse McCrosky from ThoughtWorks. Jesse shares his thoughts and experiences from years of working in the field of Sustainable Tech on the topics of risks, sustainability, and more regarding AI, before answering some questions from the audience. Learn more about our people:* Sophie Trinder: LinkedIn * Jesse McCrosky: LinkedIn | Website * Tammy McClellan: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

Events:* Decarbonize Software | GSF

Resources:* AI Transparency in Practice | Mozilla Foundation [04:19] * Reducing bias and improving safety in DALL·E 2 | OpenAI [09:31] * Responsible AI: Fireside Chat | Decarb 2023 [18:41]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel!

Connect with us on Twitter, Github and LinkedIn!

**TRANSCRIPT BELOW:

Asim Hussain:** Hello, and welcome to Environment Variables brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

Chris Skipper: Welcome to Environment Variables. Today, we've got another highlight from the recent Decarbonize Software 2023 event. We'll be showcasing the fireside chat on Responsible AI from Jesse McCrosky, Head of Sustainability and Social Change and Principal Data Scientist at ThoughtWorks, and Tammy McClellan, Senior Cloud Solution Architect at Microsoft and Co-Chair of the Community Working Group and Oversight Committee at the Green Software Foundation. They are introduced by our very own Senior Technical Project Manager for open source projects, Sophie Trinder, so it will be her voice that you hear first. So, without further ado, here's the Fireside Chat on Responsible AI.

Sophie Trinder: Hi everyone, I'm Sophie, the technical project manager for our open source projects at the Green Software Foundation. Today I'm going to introduce a special fireside chat to our Decarbonize Software event. We're continuing the conversation that began on the 5th of October at our panel on responsible AI. The conversation surrounding responsible AI is dynamic, oscillating between optimism and skepticism. one side, practitioners believe that AI has the potential to drive sustainable development goals, from responsible consumption to waste management and energy conservation. The promise lies in our improvements in measuring software's environmental impacts, and innovation across energy-efficient algorithms, hardware optimizations, and the growing use of renewable energy sources. On the other side, the rapid expansion of AI, particularly large learning language models, and the insatiable demand for this technology, are raising concerns. If left unchecked, the energy consumption and resource utilization associated with AI make many feel like we're endangering a future where software causes zero harmful environmental impacts. To help us explore the path forward, I'm thrilled to introduce Tammy McClellan, Senior Cloud Solution Architect at Microsoft, and Jesse McCrosky, Head of Responsible Tech and Principal Data Scientist at ThoughtWorks. Thanks, both. Take it away.

Tammy McClellan: Thanks, Sophie. And a hello to all you sustainability addicts. Jesse, hello. Let's start the question with, how do you see the relationship between responsible AI and sustainability?

Jesse McCrosky: Hey Tammy, great question and nice to see you all. So at ThoughtWorks we use a framework that I like which we refer to as the greening of tech and greening by tech and I think this is the best lens through which to view that question. Greening of tech refers to the fact that these systems and especially generative AI as we're talking about now have serious energy consumption, they have serious sustainability issues that need to be tackled.

The other side is greening by tech and recognizes the potential that this technology has to actually improve sustainability of other processes, either within or outside of the tech world. And I think what ties these, these two questions together is issues of transparency and information and ensuring that people have the information they need to make the right decisions for our environment.

Tammy McClellan: I like that, greening of tech and greening for tech. It's my new mantra now. So how can, uh, we use this to make more sustainable solutions?

Jesse McCrosky: So it's a big question. To begin with, I think that I refer to transparency, and when we talk about transparency, a lot of people think that means you share your source code, or you share your model weights, and then you're transparent. Or it means you have to explain the decisions the AI is making, and that's transparency. Transparency is more than that. There's a report I did with the Mozilla Foundation on AI transparency, and we talk about meaningful AI transparency that needs to be legible, auditable, and actionable. And this means that we have to consider the specific stakeholders that the information is being provided to, what are their needs, what are they going to do with this information. So it comes down to the old adage that you can't manage what you can't measure. So for example, in order to support meaningful policy, meaningful regulation, we need to have information about the sustainability characteristics of these systems.

Tammy McClellan: So talk to us a little bit about some possible solutions in this area.

Jesse McCrosky: Yeah, absolutely. So when we're looking at solutions, especially using the kind of transparency lens, we can think about who is the transparency being provided to. So, for example, we can talk about consumers. And right now, consumers are very excited about ChatGPT or whatever else, Stable Diffusion, DALL-E, and everything like that. It's a lot of fun to play with. And they do not have meaningful information about the carbon implications of that play. So someone was suggesting to me that ChatGPT should have a real-time counter across the top somewhere that's telling you how much carbon have you emitted so far in your session, how many, you know, gallons of water have been consumed, whatever else. And it is not a matter of just shaming people, but it's helping people make the right choices, because there might be applications for which ChatGPT is really worthwhile to use, but there's other times that somebody's just idly playing or something like that, and if they realize the implications of doing, they might make other choices. This becomes more interesting when we talk about communication between, for example, model developers and model deployers. So, for example, if somebody is using the OpenAI APIs in their product, they need to be able to have information about what the implications are of those API calls so they can make good choices in how they build their software.

Tammy McClellan: So awareness is key, absolutely. So Jesse, what is the potential for Gen AI to support greater sustainability?

Jesse McCrosky: Yeah, it's an exciting question, and I think there is some potential here. There's a case that ThoughtWorks took, it's a couple years back now, I think, in which we worked with a international manufacturing and services company. They were interested in finding solutions to meet their sustainability goals, and they just weren't sure which way to go.

They weren't sure, "should we start sourcing our energy from a different place, or using different sorts of transportation, or using different industrial processes or offering different products?" And so what we did for them was built a mathematical model of their operations and their supply chains. once we had that mathematical model, we were able to build a sort of scenario modeling dashboard where we could show them like, "hey, if you switch to delivery trucks that are using electricity instead of gas, this is what happens to your emissions, this is what happens to your bottom line, this is what happens to your customers."

And likewise, depending on / considering different product mixes, considering different sourcing, whatever else. So the mathematical model here was not rocket science, to be honest, it was fairly simple stuff. The hard part of this engagement was really understanding the business at the level that we needed to in order to build that model. There were many hours of interviews and poring over notes and internal documents and everything else, as well as actually some basic desk research to determine the necessary carbon emissions factors, that sort of thing. I'm excited at the potential of generative AI to make this sort of process more accessible and more scalable. And I think that we've seen evidence so far that these models do a very good job of looking at these sorts of documents, looking at recordings and interviews, and it may be possible that you could create this model semi automatically with far, far less of the kind of very heavyweight and expensive all sorts of interventions. As well, it was challenging to understand the exchangeability. And so, for example, if the company is buying cotton in one particular country, it might be obvious to us that they can instead buy the same cotton from some other country, and that's the only possible change that could be made. But it's not so simple for the model to figure that sort of thing out automatically.

Whereas GenAI, I think when we connect to these sorts of emissions factors databases, has the potential to make this process much easier.

Tammy McClellan: Yeah, awesome. Let's move a little bit and talk about risks. How do you think businesses can manage the risks of AI?

Jesse McCrosky: Yeah, it's it's a big question. I think everybody's talking about this. And I think what I would say is it's critical to understand that risks must be mitigated, not removed. I think a lot of people are talking, for example, about bias and discrimination, and they say, okay, we're going to produce a model that's perfectly fair and perfectly unbiased, or we're going to eliminate this bias from our model or whatever else. And this is just not the way things work. We live in the real world, and these systems are based on data from the real world. And the real world is unjust, and so we need to be able to be ready to tackle that. So, one example that I like is OpenAI with their DALL-E interface generation system. For a while, maybe some months ago, I think, if you asked it for pictures of lawyers, it was going to give you eight pictures of white men, basically.

And OpenAI recognized that there was a problem there, as did the community, of course. So eventually, OpenAI had a short blog post where they talked about how they were going to fix this. And it was apparently fixed, so when people tried to get pictures, they would see pictures of lawyers, and some of them would be women, and some of them would be of different ethnicities, and everything else. So People were curious how this had been fixed and it turned out that all that OpenAI was doing was just randomly appending words like women or black or Asian or whatever else to these prompts and people were not super impressed with this solution but I think it's an important illustrated example, because it's a mitigation, there was a problem with a model, there was a problem with the data, this is not a problem that can be solved fundamentally, it needed to be mitigated, and they found a way, they said, "here's the harm that's going to come from the system. It's going to not be producing an adequate representation, and we found a way that we can show more representation." So this is the sort of mitigation that companies need to take. So when there's issues, and this is where transparency comes in around the carbon impacts as well, so that they can be mitigated, so that if I'm an engineer sitting in front of my laptop writing some software, I need to have awareness that if I call this Gen AI call or whatever else, I have to understand this is going to spike the carbon emissions of my product, and I need to find another solution.

Tammy McClellan: Gotcha. Yeah, that makes sense. Tell me. So are you optimistic or pessimistic about Gen AI at this point?

Jesse McCrosky: I think I'm mixed. I think that ultimately solving the climate crisis means simultaneously solving a social crisis. And I think it's very hard to solve climate change without also solving issues of social justice globally. And I think that Gen AI is a tool that might enable some of these conversations to be tackled in a more interesting way.

So I think as long as we're mindful and honest and clear eyed about how we apply this technology, there can be some optimism there. We need to ensure that we have adequate transparency so that people understand the carbon implications of the choices they're making when they're using these systems, but given that, there is potential to do better.

Tammy McClellan: Gotcha. So I know when you and I chatted before, you said that you had a fun story of AI. Did you want to tell us what that is?

Jesse McCrosky: Ah, so actually, I think there's a misunderstanding. The fun story was an expanded version of what I was talking about before, but

Tammy McClellan: Gotcha.

Jesse McCrosky: if we have a moment, I think one thing I want to add when we come back to the idea of how, how transparency can help Gen AI be used more responsibly. So, a lot of people are familiar with the concepts of DevOps or MLOps or CD4ML, these sorts of processes. And I think this is a really critical place for transparency around carbon emissions to be integrated. I think the point I would make is that right now, a software developer that's working in kind of a modern setup has the ability, as they're writing code, to see immediately if the code that they're changing is causing some test to fail, or is causing some performance degradation, or is introducing some bug or whatever else. And I think we need to have the same process for carbon so that it if an engineer is making a choice and for any devs out there, maybe you have a case where you need to use a regular expression, but it seems like too much work to figure it out. "Hey, I can just call a Gen AI model and it'll do it for me as well."

It'll work just fine. And you might make that choice because it saves you a couple minutes or whatever. But if you then see that all of a sudden your dashboard turns red and says, okay, your carbon has just increased like 100 percent or whatever, you're going to come back and you're going to revisit that decision. And also your team is going to see that, the trail of what's happening because of what you've done. And so it creates this sort of accountability in the development process.

Tammy McClellan: All right. So I'm curious. What are the top three recommendations you would give to people who are interested in reducing carbon emissions of AI?

Jesse McCrosky: Good questions. And yeah, I think that's something I didn't really touch on so far, but there are a lot of choices that can be made when applying AI. So we don't need to use the biggest general purpose models for everything. I think that there are cases where a general purpose model is really needed. But um, I think that in most cases, no. And so we can talk about using much simpler application-specific models. We can talk about using a smaller model and fine tuning it for the particular task. There's processes like quantization and distillation that can make models much more carbon efficient and nearly as effective. So investigating these options, and again, I think this kind of hinges on the MLOps setup where you need to be ready to evaluate performance. You need to be able to say "how small can I make this model and still actually meet the requirements in my product." Beyond that, I think it's a matter of providing transparency to the end user. So if you're producing something, if users understand the choices that they're making when they're using that product, there's a lot of different ways this can play out, and this can mean some Gen AI chatbot or something like that, but this also can be, maybe you have an e-commerce product. platform and you're using AI to make recommendations to your users and the recommendations that you make can influence their behavior and it can encourage them to buy more products that are disposable or made in very carbon-intensive ways, and so considering these sorts of externalities as well is really critical.

Tammy McClellan: Gotcha. I'm curious, do we have any questions from the audience at this point?

Sophie Trinder: Yes, we do. And thank you so much, Tammy and Jesse. It's been a really great session on AI here at Decarb, and it really shows the passion in the industry for these technologies, plus the responsibility that we all must take when it comes to AI. I know we'll be hearing a lot more in the coming months. But yes, we've got a few questions from the audience. I just want to shout out first, Jesse, thanks for the fun story on OpenAI, how they were mitigating the problem with data to show more representation through mitigation. It was a really interesting insight, thanks. So one question from the audience, how important is prompt engineering for improvement of AI efficiency?

Jesse McCrosky: Great question, yes, and it's it's really extremely important, because the energy being consumed by the model is going to depend in some complex ways, depending on how many tokens are coming into it, and in quite a direct sense, how many tokens are coming out of it. So if we can reduce the number of tokens going through the system, we reduce the carbon emissions. And this again, I know I'm sounding like a stuck record, but it really depends on the MLOp setup, where we should be able to test and see how short can we make our prompts and still accomplish what we need to do. And this is both the length of the prompt itself and the length of the output. So for example, go back to that example I was talking about where maybe ChatGPT has a little indicator at the top telling you how much carbon has been emitted in your session so far. Maybe if you see that number growing as you're chatting with it, you're going to say, "hey, ChatGPT, please be a little bit more brief with your answers. I don't need the whole kind of colorful language and going on and on about everything." So yes, it's very important.

Sophie Trinder: Super interesting. Thank you. We've got another one on training the AI ML model, which obviously takes a huge amount of data and processing, which in turn causes a lot of emissions. How do you think that we could best counterpart the same?

Jesse McCrosky: Yeah, good question. And I think that I have an article out where I actually talk about how the comparisons are a little bit overwrought, talking about how training a model is equivalent to driving a car some distance or whatever. I think that, um, the comparison, at least so far, thankfully, is not quite accurate because we have many cars on the vehicle and a relatively small number of models being trained. I think the important thing is to keep it that way. I think the important thing is that we need to encourage use of open models and shared models rather than every single organization in the world trying to train their own LLM. And this is why I would be a strong supporter of open-source models. I think it's nice to see that movement.

I think it's potential. It means that organizations, first of all, save their money, but also save their carbon when they want to be able to explore elements in their business. And there's always the potential for fine tuning, for whatever other tools need to be applied to open models to make them suit people's applications.

Sophie Trinder: Amazing. Thank you. And jumping back to sort of problems on data and representation, we've got another question centered around that. So do you think we should promote digital humanism and ethical AI to raise awareness about the need for sustainable AI?

Jesse McCrosky: Yeah, absolutely. I think we're existing at a moment where responsible AI and such is being discussed everywhere. There's very active regulatory work in many different regions of the world. There's many people in academia, in civil society, and in industry doing this sort of work. And I think that green AI should come along for the ride, so to speak, and it should be an important part of how we think about the risks and the potentials of these models.

So, yes.

Sophie Trinder: Amazing. Thanks very much.

Chris Skipper: So that's all for this episode of Environment Variables. If you liked what you heard, you can actually check out the video version of this on our YouTube channel. Links to that as well as everything that we mentioned can be found in the show notes below. While you're down there, feel free to click follow so you don't miss out on the very latest in the world of sustainable software here on Environment Variables. Bye for now!

Asim Hussain: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show and of course, we want more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation Thanks again and see you in the next episode.

View Details

Chris Skipper hosts this episode of Environment Variables with guests Sophie Trinder and Adam Jackson to discuss the unveilings, questions, and highlights from the recent Decarbonize Software 2023 event. The GSF has announced its Impact Framework during the event that had taken place in November, and together with Chris, our guests discuss the realities of (and dreams for) the state of green software in this recap of Decarb 2023.

Learn more about our people:* Chris Skipper: LinkedIn * Adam Jackson: LinkedIn * Sophie Trinder: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Driving Climate Change Solutions with AI | Decarbonize Software 2023 [07:13] * High-quality energy data for emission optimizations | Decarbonize Software 2023 [11:54] * Impact Framework Demo | Decarbonize Software 2023 [14:57] * Engineering Excellence with GSF Principles & Patterns | Decarbonize Software 2023 [18:27] * Emissions Impossible: From home insights to a greener workplace | Decarbonize Software 2023 [30:55]

Events:* UN World Environment Day: The Green Software Revolution (Virtual Event) - Monday June 5th [31:27]

Resources:* Software Carbon Intensity (SCI) Specification | GSF [11:02] * Impact Framework | GSF [12:48] * Introducing the Impact Framework | Decarbonize Software 2023 [13:04] * Green Software Practitioner [17:37] * State of Green Software | GSF [21:02] * Green Software Patterns | GSF [29:38] * Opensource / Carbon Aware SDK | GSF[30:43] * Dan Benitah's Projects and Posts [35:52] * Decarbonize Software [38:19]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

**TRANSCRIPT BELOW:

Sophie Trinder:** We've also had some big tech companies adopting the Carbon Aware SDK, which has been great, including Microsoft and NTT Data to shift some of those high workloads, like training machine learning models to a different time in the day, potentially even a different location. So yeah, it was really great to see the Carbon Aware SDK being talked about at Decarb.

Asim Hussain: Hello and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode we discuss the latest news and events surrounding green software. On our show you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host Asim Hussain.

Chris Skipper: Welcome to this episode of Environment Variables. I'm your host, Chris Skipper. And in this episode, we will be doing a recap of the recent Decarbonize Software 2023 event with the Green Software Foundation's Community Project Manager, Adam Jackson, and Sophie Trinder, Senior Technical Project Manager and Relative New Face at the GESF. Hello, Adam and Sophie, and welcome to Environment Variables.

Adam Jackson: Hi Chris, it's great to be back.

Sophie Trinder: Hi, Chris.

Chris Skipper: Great. So before we dive into the meat of this podcast, for our listeners who don't know you, could you please introduce yourself? And let's start with Adam, seeing as you are a well-seasoned veteran now of environment variables.

Adam Jackson: So I'm Adam Jackson, and I'm the Community and Tech Culture Lead at the Green Software Foundation. And once again, it's, I'm very excited to be here. I look after our community working group, and also many of our projects and programs, including our meetup program, Green Software Champions, and our recent Decarbonize Software event. Plus in 2024, I'll be leading the efforts on our Carbon Hack and our GSF Summit.

Chris Skipper: Great. Thank you. And Sophie?

Sophie Trinder: Yes. Hi, I'm Sophie Trinder. I'm the Senior Technical Project Manager at the Green Software Foundation. Excited to be here. Recently, I've been focusing on the tooling pillar of the Green Software Foundation's three pillar strategy, known as the Theory of Change. Alongside tooling, we also have knowledge and tech culture.

Like I say, I've been focusing on the tooling and driving forward the open source projects that sit under the umbrella of the open source working group. This includes tools for measurement, like our Impact Framework, and also tools for reduction, like our Carbon Aware SDK.

Chris Skipper: Awesome. Thank you, Sophie. And how long have you been in the GSF now? When did you join?

Sophie Trinder: Just over a month ago,

Chris Skipper: Just over a month ago. Great. Great. Cool. So exciting things to come. And for those of you who don't know me, my name is Chris Skipper. You've probably heard my voice before on this podcast. I am the producer of Environment Variables. And recently I found out that Environment Variables is the top podcast for 55 amazing listeners on Spotify, thanks to Spotify Wrapped. Just a note that spotify is not the only platform that environment variables can be consumed on. And if you want to listen to it directly from the source, please go to podcast.greensoftware.foundation to listen there. Um, anyway, so, uh, I feel like I've, I've spoken enough about that before we dive into the actual topic of today's podcast, which is the debrief, uh, which will be the title of this episode. Just to remind everyone, everything that we talk about in the show will be linked in the show notes. So, to kick us off, I have a few questions about Decarb 2023, seeing as I wasn't there. We'll be going in sort of a, uh, tit for tat. That's a bit, that's a wrong phrase. I'll be asking one question to each of you at a time, which we, we've kind, you've kindly delegated out to each other. So my first question is, Decarbonize Software 2023 was an overwhelming success in the eyes of the Green Software Foundation. Let's start with some statistics, seeing as we've been talking about statistics, just in my little intro there. How many people attended and how many talks were there? Did it meet the goals of the GSF's intentions with this event? Adam?

Adam Jackson: Yeah. So, uh, well first of all, Chris, no, no pressure that you weren't there live because it was the middle of the night for you. And I wanna start by telling everyone that it is available on demand if you haven't watched it already, at decarb.greensoftware.foundation. But yeah, let's jump into the numbers.

So we actually had five community talks and we had three talks from the GSF itself, announcing new programs. And yeah, we had, I think we had a really brilliant event. We had over 2, 500 viewers and almost 400 live questions and comments. And it wasn't all just "hi from London" and stuff like that. It was actually, there were some really great and deep questions.

Also some challenging questions as well, pushing the boundaries. So it's not just the quantity, it's also the quality of those questions that really stood through. But what's really important to me is that we didn't just connect with folks who are already members of the GSF, but actually brought in lots of new folks from the community. And they're the folks who'll tell their friends and colleagues about green software, as well as getting involved in our open source projects in the future. So, yeah, excited about how we did number-wise, but also excited about the type of people that we met along the way.

Chris Skipper: Wow, amazing. So yeah, I didn't expect to hear that statistic of that many questions. That's really great. And hopefully I know that a few of those questions were answered live on stream. Obviously there wasn't time to answer all of them, but hopefully there will be a source for people to go to. I know there's talk of there being a document or an article to do with the questions.

Adam Jackson: Yeah.

I think it's, I think it's actually published.

And we'll put that in, we'll put that in the notes. But there's an article where we, we pick up on some of the main question themes. Yeah, it's tricky, isn't it? You want to get in all of these different community stories, and we were really careful to get a good balance of different stories from across Green Software. And then we had five minutes for Q& A, and really you can only ever get into two or three questions. And Sophie and Namrata and I were there in the background trying to answer as many questions as we could in the, in the live chat and Asim was there as well. But yeah, we thought it was best to actually look at what, what the main themes were and try and answer as many of those on demand. And, and it's actually also given us some ideas as to the sort of video content we want to create in the future and probably might even spawn a couple of Environment Variables episodes as well.

Chris Skipper: Yeah, well, I was just going to say, if there are any unanswered or burning questions that haven't been answered, perhaps we can rope Asim into answering some on this podcast. So that would be cool. Anyway, let's move on. Sophie, so can you share a standout moment or a particularly surprising insight from decarbonized software 2023 that really stuck with you?

Sophie Trinder: It's so hard to pick just one. But yes, if I have to, one interesting insight that stuck with me and actually that gives me optimism is from a talk given by Diana Ditrimova, managing director and partner at BCGX and Charlotte Degot, CEO, and founder at CO2 AI. So to give a little context for those who may not have joined us at our Decarb event.

Diana and Charlotte shared some of the key findings from their joint carbon emissions report, which is called 'Why Some Companies Are Ahead in the Race to Net Zero.' So, this report is a survey incorporating feedback from 1, 850 organizations across 23 countries. And they estimate that all of the sort of organizations represents about 40 percent of global emissions.

So, we're looking at a good representation of global emissions here. And one interesting insight for me that stood out was that 40 percent of those surveyed estimated an annual financial benefit of at least $100 million for meeting emissions reduction targets. And so often at the GSF we hear the question, "what's the business advantage associated with making greener choices when building software?"

And I think that this stat, it gives a really interesting insight that helps form that answer.

Chris Skipper: That's, yeah, it's interesting that you mentioned that talk in particular. I'm hoping to get them together for an episode of Environment Variables to talk about that in particular, that study, that that's incredible, that, that reach that they have of 40%, yeah, of, yeah, I don't think, I think that's the one thing that that's been covered a lot on, at least on Environment Variables and my engagement with the Green Software Foundation is just having the sheer amount of data is sometimes it was probably the biggest issue out there with any sort of measurement to do with carbon emissions. So, and software in particular, if you haven't seen the Decarb 2023 video, you should go back and check that talk. Cause I think it's only about 10, 15 minutes long. So it won't take a lot of time out of your day if you want to have a look at it.

So.

Adam Jackson: Yeah, we're really hoping to actually make all of that content available in bite sized chunks as well. So, so that people can find that on demand. And one thing I like as well, just to add on what Sophie said, is that Um, that talk was beyond just green software itself, but it was also "how can you use software to further sustainable outcomes?" So that's, that's another thing that we don't directly cover every day at the Green Software Foundation, but a lot of our members and our community are really interested in.

Chris Skipper: Yeah. And it goes to show also the diversity of just how big the community has become in the last sort of two years, just because of the existence of the Green Software Foundation, it's attracted people outside of the software industry, which is fantastic, and I'm sure this probably echoes what Adam is fighting for is we want people from all walks of life to join the cause and come and talk and just increase the dialogue around it.

So that's fantastic. Anyway, so let's move on. I'll pitch this question to you, Adam, given the emphasis on measurement at Decarb 2023, what's one common misconception about carbon emissions measurement in software that was debunked or clarified during the event?

Adam Jackson: It's a really good question, Chris. It's actually quite a challenging question as well. So one of the biggest misconceptions that I see is that it's from people that are coming new to the GSF, is that it's been easy to do measurement at all. It really isn't. Measurement isn't easy today. It's about to get easier.

We're definitely on a journey, but it's important to look at the very short history of measurement. What we have today is some amazing standards, such as the Software Carbon Intensity or SCI standard, which, which actually has been submitted to ISO. Hopefully we'll get an approval and see that in the catalog very soon. But we're still super early days. And we're also going to be talking about, um, some of the, some of the key elements in producing tools that can actually do the measurement for us. It's been very manual working out. We'll see spreadsheets or a few people we've seen have implemented some dashboards. I saw a really great talk from Amadeus, which is one of our GSF members, over the summer at a conference in Berlin, and they'd done some really, really great dashboards, but it had all been very much custom work for them to get to that stage. And yeah, what is great to see is, particularly this year, we're actually seeing a lot of effort put in to measurement and visualization. And if I bring it back to the Decarb event, we did see a wonderful talk from Yvette and Johann. They're from CODE University in Berlin, and they've been building a measurement project. It's really focused on measuring consumption of energy. So if we think about the SCI equation, for anyone that's familiar with that, is the letter E in the equation. If you don't know what the equation is, take the Green Software Practitioner training and it shows you all of that. Anyway, these folks from Berlin, they've actually implemented some visualization. To that energy measurement and it was really great to see because visualization is hard and not everyone agrees on it. And there was a lot of, there's a lot of chats during the event on visualization as well. So, but the important thing is we'll need to see folks like Yvette and Johann. And they'll have to show us what we can do with that visualization. And it's also going to help us build out the capabilities of things like the new Impact Framework, extending it, show us what's going on as well.

Chris Skipper: Yeah, yeah. I just mentioned that data was hard to come by, but yeah, measurement, itself, obviously, is a big challenge. And if you are interested more in the measurement and the struggles of measurement, we actually have a previous episode of Environment Variables with Srini Rakhunathan and Navveen Balani with Asim talking about all the other attempts that have been made at measuring carbon emissions of software prior to the SCI.

So that's a really fascinating episode if you are interested in that. And yeah, it's great that you mentioned visualization as well. I know you love a dashboard, Adam. So that's something you mentioned last time you were on the pod. So I'm just going to bring that up again.

Adam Jackson: Yeah. Actually, one interesting thing is you measure, you mentioned data. Obviously, you need data in order to be able to measure. But also the act of measuring puts pressure on others to produce data. And we do hear, and I'm not going to single out any GSF member, but we do hear, "Ooh, why doesn't company X provide this data?"

And actually a lot of the time it's because people haven't asked for it yet, or people haven't shown that they have a need for that data. So, so I really do truly believe that the more we measure, the more data sources will become available.

Chris Skipper: Yeah, absolutely. Good point. Cool. Okay. Switching back over to Sophie in this game of question tennis. The next question I have is, we just mentioned the Impact Framework and that was obviously the big surprise that was the big mention that was going to happen at this year's Decarb 2023. So for our listeners who don't know what it is, Sophie, do you mind elaborating, please?

Sophie Trinder: Yeah, of course. So, yes, you're right, it was the big unveiling of the Impact Framework in our introduction at Decarb this year. So, the Impact Framework is one of the Green Software Foundation's open source projects. We have been working on it for almost a year now, but it's still in incubation, which is one of the project life-cycle stages.

And that basically means it's still evolving, it's still in its explorative stage. But we did manage to do an alpha release in November ahead of Decarb, which is where we introduced it, and showcased it through a live demo of the tool. So the framework itself is an extension of that software carbon intensity standard, the SCI, that Adam just mentioned.

So just to dig a little bit more into what that covers, the SCI is this equation, which is the energy consumption times the emissions factors plus embodied carbon over a functional rate. So this is the what we should be measuring when considering negative environmental impacts of software. And then the Impact Framework takes that equation and provides a tool into how we can measure that impact.

So if we think about some modern applications, they're composed of many smaller pieces of software, which we call components, running on many different environments. For example, private cloud, public cloud, bare metal, we've got mobile, laptops, desktops. Every environment requires a different model for measurement.

So the Impact Framework provides a framework for running all these different models using model plugins to calculate the output of impact through that SEI equation. So right now at the, the GSF, we've got a standard library of models and a repository of community models, and we envision a future where the number of models just keeps expanding out into the thousands to cover all those different environments.

So it is an open-source project, like I just mentioned we're welcoming contributions in fact, our hackathon, which is happening next February, is Impact Framework focused. So that's where we're hoping to see lots more of these models get made. The opportunities is endless that we see in the ways that we'll be able to start improving the measurement of the negative environmental impacts of software.

Chris Skipper: Great. Yeah, that's amazing. And yeah, I love the community focus of it. I think that we, we talked about the importance of open source in general, and I think everything that the GSF has done has been open source. So the possibilities are endless when we all join in and, and I think the hackathon, which we'll talk about a bit later in this podcast as well, next year is going to be phenomenal, especially when there's a bit of incentive behind it. So yeah, it'll be really interesting to see what comes from that. Moving on, let's talk a bit about the Practitioners course, the Green Software Foundation's Practitioners course, which you mentioned, Adam. This, obviously that's where you can learn more about the SCI, but it's trained over 50, 000 participants in less than a year, which was something huge that was announced also at Decarb 2023. What do you think is driving the surge in interest and how can more professionals be encouraged to participate?

Adam Jackson: Yeah, I've just literally opened the stats. 55, 000 now, so yeah, doing really well. We need another 5, 000 people to do that in the month of December, so we end on a nice round number. And actually, we know that some more people have enrolled as well, so another good thing. One of the cool things we've certainly got some people that have started the training and hopefully they'll, they'll come back to it as well.

But, uh, yeah, it's interesting. If we think about, uh, Chris's talk, that's, uh, another Chris, Chris Howard from EPAM. EPAM is a GSF member. So his talk at Decarb really showed us how important the knowledge, this knowledge is. And why it's so important for both individuals and also organizations. So I've no doubt that a lot of people do take the practitioner course because they're concerned about what has happened, happening to the planet. And they're worried that we're experiencing our hottest year ever, which was just announced at COP, and they're concerned that software is between 4 and 5 percent of global carbon emissions, and that's twice that of air travel. But I think there's something more than just an individual concern. I think that concern is becoming more than something that people worry about, or campaign about and actually, it's starting to turn into something that's also becoming a business driver in a way that, a way of individuals distinguishing themselves in the job market, so to speak. So for companies like EPAM, which is a consultancy, they don't just want to develop their staff. They also see the difference it makes to the organization, um, when winning a customer.

Because their customers are demanding green solutions. Um, and it's also, of course, it's a massive motivator for their employees. You know, they've a fantastic internal community who want to learn these things. But yeah, I'm not surprised we've seen this growth. My, my colleague, Russ, who leads our knowledge efforts at the GSF, he says it's just the beginning, and I think we will really continue to see us moving from just being worried about the environment to actually having people that really want to do something, they really want to take action, learn more about it, and then really measure and reduce.

So, yeah, I'm looking forward to seeing six figures on number of people taking that course, hopefully at some point in the early months of 2024, and I think we'll continue to see both that individual and that organizational pressure to learn and then be able to take action.

Chris Skipper: Yeah, amazing. Yeah, it's gone up to four to five percent already, the emissions of software.

Adam Jackson: Yeah, yeah, That's right. That's actually a stat that we, that we announced during our State of Green Software report back in May 2023. Yeah, it's, I think it's quite startling to a lot of folks because we see, I think most people think it's in the sort of 2%, 2 - 3 percent band, but we actually did a lot of research and found that it was actually quite a bit higher. And I would certainly recommend people go to stateof.greensoftware.foundation to read the report for themselves. But just a reason that it's higher than people think is because a lot of people just think about the data center or the device, but actually you've got data center, you've got all of that network infrastructure in between, and you've got the device. And I can't remember the exact numbers, but actually I think you can even sometimes think of them, depends on the application, but sometimes it can even be a third each. So yeah, reducing, for example, reducing network bandwidth is a good way of decarbonizing software as well. And people never think of that. So check out that report if you want to hear a bit more. Yeah,

Chris Skipper: Yeah. Cause I think it was just probably this time last year that it was 2%, which is quite, yeah, I think we announced that on the podcast, so that's quite, yeah, really scary, but yeah, and also, yeah, sorry to focus on more positive things and the growth of the green software practitioner courses intake or the amount of people that have gone through it, I think. That number is really impressive, firstly, and then secondly, just that more people are going to be using it as a business decision, that's something you pointed out, I think is something that I think might be a great way of people to think about their approach to green software as a whole, because whether you like it or not, businesses are going to have to adapt.

And yeah, so really great that the GSF is leading the way in providing qualification for people, consultants in particular, that's a huge industry consultancy, so yeah, and obviously we have consultancies that are part of the GSF. I think Accenture, am I right in saying that?

Adam Jackson: We've got a few, and yes, yes, so, other consultancies do exist as well for folks, but yeah, if you want to see who, see the, the big list, our membership's grown massively this year, by the way, so just go onto our website if you want to find out who, who is contributing as a member, and that those members really help us set our standards and they're the ones that are very heavily involved in the day to day running of the foundation. And yeah, consultancy is a big part of that. We also have a lot of representation from the, the cloud and tech companies themselves, but also industry, a lot of, banking in there right now, a lot of regulated industries in particular.

Chris Skipper: Yeah. Yeah. Great. So obviously we just talked about the frightening statistics of the amount of emissions that are being created by the use of software. I think part of that is down to the, the rise of AI and the use of LLMs. ChatGPT, et cetera. And so with that in mind, Sophie, I'm going to ask you a question a bit about that.

The relationship between responsible AI and environmental sustainability was a hot topic at Decarb 2023. What were some enlightening points brought up by Tammy McClellan and Jesse Mccrosky in their fireside chat as part of the event?

Sophie Trinder: Yeah, thank you. It definitely was one of the hot topics of the Decarb event. And so many enlightening points were brought up by Tammy and Jesse, but one particular point that stood out, which actually we've touched on already, is that transparency of data and information is key. We touched on this when we were talking about measurement, weren't we?

We were saying the more we measure and we request measurement, the more likely people are going to be to giving us the data we need in order to measure. So Jesse was touching on that transparency of that data. So we need the full picture on emissions of AI systems. And that's not just looking at open source code, but full transparency of what the emissions of AI systems are.

And he was talking about how In order for software developers to make sustainable choices on whether to integrate AI into their products or how to develop the type of AI that they're developing, they need the full picture. Similarly, he touched on how policy makers need that in order to make good regulation and policy on AI.

But also for us as consumers, how we can make sustainable choices when using AI. I like the term, be a conscious consumer. But for us to be conscious consumers, we need the knowledge in order to be conscious. So we need that transparency of data. And Jesse painted this hypothetical picture. What if there was a carbon counter or there was a water gallons clock at the top of ChatGPT?

Would you use it differently? Would you only use it when it was essential? Maybe you would write a shorter prompt. Would you ask it to write its answers briefer? Similarly, he painted another picture where, what if a software developer's screen went red? If the developer made a decision that, yeah, might make them save some time, might make them slightly more efficient, but what if it came with a huge carbon cost?

So their screen went bright red when there was a carbon cost associated with the code that they were writing. I think it was just a really interesting way to start thinking about being more transparent with that data so that we can be more conscious with our decision-making.

Chris Skipper: Yeah, absolutely. And there's also a gap in the market there for perhaps a browser plugin or something that would really inform day-to-day users, because I know people have, well, I've spoken to people that have been using ChatGPT as if it were Google and that's quite worrying, you know, so, um, you know, we've, there's an episode of environment variables where we speak about the environmental impact of AI and, um, just the sheer amount of water that it uses is quite incredible.

So those ideas. That was spoken about during Decarb 2023 were really great. And I think maybe we'll see some of that as a springboard for what will happen in Carbon Hack 2024.

Sophie Trinder: Yeah, definitely. We've seen it in certain other industries when you're buying a flight and you see the little green label now on certain flights where they say if you buy this flight ticket it's going to be better for the planet in terms of emissions. Maybe it's It's going to be a fuller aeroplane, those sorts of decisions, it's, it would be great to see some of those, like you say, user interface platforms where we'll be able to start helping people make those more environmentally conscious decisions when it comes to software too.

Chris Skipper: Yeah. And I think that's one of the biggest challenges facing organizations right now, um, at Decarb 2023, there were a lot of challenges that were raised. Um, speaking of which, what's your take on the biggest challenge organizations face when embracing green software right now, Adam, and how do you think it can be overcome?

Adam Jackson: Yeah, so, well, first of all, we've talked a lot about measurement already, and I do think that measurement is probably the biggest challenge for us all right now, but I want to look at a different challenge that some, that organizations specifically have embracing green software. And I touched on this a little with the EPAM example, but in one of the other organizations we had on the Decarb event was Siemens, and Siemens, they're a brand new steering, steering member of the GSF, they joined in the last few months, but their journey with a sustainable software goes way further back than that. They've spent a long time building sustainability into their entire software lifecycle. And that's what their talk was about. And I think actually that, beyond the knowledge, is the hardest part. Often, I often tell folks when they ask me what green software actually is, that there's a lot of parallels with well-crafted software. So well-crafted software, like green software, focuses on built-in quality throughout the complete software lifecycle. So architecture, development, operations, getting all of the stakeholders together to take responsibility. And we need the same thing for green software. So at the GSF, we often talk about software practitioners, and this is a broad term that goes beyond developers alone.

It includes product managers, program managers, designers, UX, testers, IT operations. And what takes the time, and GSF does have some materials that can help here, is developing the best practice, the processes, and the learnings that bring all of these people together into a really holistic software lifecycle, and I think that's why we're really keen to get organizations to hear and listen to others, even if they're competitors, what's the best practice that we can all share that's gonna deliver green outcomes. And then we also have some materials inside the GSF, such as our Patterns Catalog, which is like a set of best practices and people can use that to, to go beyond just the learning and start thinking about how to integrate it into their organization. So yeah, a bit of a long answer. It's, it's a bit of an abstract challenge as well, and it's different for every organization, but really think, yeah, thinking about how, if we think of the Learn, Measure, Reduce, that reduce bit, it can be, sometimes it can be simple for a single product or a single workload, but when you're trying to think about how to get your whole organization on that journey, that takes a bit longer.

Chris Skipper: Yeah, amazing. And also, I think it highlights, there's been an immense amount of growth in the last year, just in terms of the amount of news and the amount of events that are happening around green software, which is fantastic. So Sophie, with that in mind, what are some of the exciting innovations or projects that are making a significant impact that were highlighted at Decarbonize Software 2023?

Sophie Trinder: Thank you. Yeah. So another project that was highlighted at Decarb that's been having a significant impact is another one of our open source projects I mentioned earlier called the Carbon Aware SDK. So we had two of our principal contributors come and talk at Decarb about the SDK. That was Dan Benitah and Vaughan Knight.

They gave a fascinating talk into some of the use cases of adopters of the SDK. So for a bit of context for anyone who is new to the Carbon Aware SDK, but also to Carbon Awareness, that basically means being aware of the carbon intensity of the electricity on the grid and doing more when and where the electricity is cleaner.

So less carbon intense, i. e. generated by renewable resources, and doing less when and where the electricity is dirtier. So the Carbon Aware SDK is a web API and command line interface tool that helps assist in building carbon-aware software by providing the intelligence of knowing when and where the electricity is cleanest.

So you don't need to do all of that work for yourself. There's a tool out there already that can help, help you work out when and where would be best or cleanest for your consumption. And what was really interesting at Decarb, Dan showed us how he's been adopting the SDK himself at home to successfully reduce his impact by 30%.

So, he used the Carbon Aware SDK to simulate different hypothetical scenarios. So, for example, he was looking at his big consumption uses, his dishwasher, tumble dryer, those sorts of things, washing machine. And he used the SDK to, to simulate Different scenarios of if he was to shift his consumption, so that's the kind of the when part of the when and where of carbon awareness, when you consume, he was, yeah, looking at different scenarios and he learned that if he time shifted by seven hours to time where his electricity was cleaner, then a 7 hour shift would be best.

So that's what he did in order to reduce his impact by 30%. So it just shows that with the right data, like we were talking before, with the transparency of that data, we've all got the potential to make some significant impacts in our reduction of consumption. And so whilst Dan shared this example of carbon awareness in the home, and the small things do add up, we've also had some big tech companies adopting the Carbon Aware SDK, which has been great, including Microsoft and NTT Data, for example, like you mentioned earlier, to shift some of those high workloads like training machine learning models to a different time in the day, potentially even a different location. That was the where part of Carbon Awareness, when and where, time and location. So yeah, it was really great to see the Carbon Aware SDK being talked about at Decarb.

It is still growing. We're just about to do a version 1. 2 release in a couple of weeks. But again, it's all open source, open to contribution. And definitely would recommend people taking a look and seeing if you could simulate different hypothetical scenarios for your own workloads. Be that at home or at work.

Chris Skipper: Awesome. Yeah. I haven't heard that story about Dan using it in his home. That's fantastic. I know we spoke a little bit about how people can make small changes in their own life to do with green, with green software and just being more environmentally friendly as a whole the last time Adam was on the podcast.

But with that in mind, Adam, can you tell us a little bit more about how people can use the SDK in their personal life to become more carbon aware?

Adam Jackson: Uh, yeah, actually, Sophie's already given a really good overview and, and Sophie's quite an expert on, on energy. So I've had some really interesting chats with her already, but, but yeah, the, the added dimension for me, if you, if you actually watch that final session from Decarb, you probably can't help but see how excited I was personally to hear from, from Dan and Vaughan talk about carbon awareness to hear in their own homes. So I have a home assistant set up at home. So it's a Raspberry Pi 4 with the Home Assistant software on and that's open source and that piece of kit talks to all of the, all the smart home, all the, all the devices in my house. And we're getting better and better. I feel like every time I open Home Assistant, I can connect to more data sources in my own home. And that makes me really excited as to how I can not just think about the energy, but also everything that's going on in my house. So, yeah, we touched on, upon how the SDK could be used, and Dan is actually writing a blog post right now about how to integrate Carbon Aware SDK into home assistant setup without doing lots of custom code. And I was going to put a bit of pressure on him because he hasn't finished his blog post yet. So hopefully by the time this podcast comes out, it'll be done or soon after and we'll try and get that linked. So, yeah, I'm excited about this because not only do I want to, I want to understand more about my own carbon impact, but I want to combine that with the data that all of the devices in my house provide. And I want to combine that with my, my battery and my solar setup and think about the dimensions, such as having an electric vehicle. So looking at how I can really balance and optimize my use of electricity. And so, sadly, I live in a, in quite a high-carbon area. So if you touched upon the, the location being a dimension, I can't change where my house is sadly, but the intensity does, the carbon intensity does vary dramatically at different times of the day. So I'm hoping I can take something from my work life and make that work for me at home as well. So you definitely watch that, that short video as well from the end of Decarb about, about Carbon Aware SDK. And yeah, you'll see some of the discussions I had were along these lines as well.

Chris Skipper: Yeah, that's incredible. I only learned about a Raspberry Pis through this podcast and yeah, just the use of it to do that is, is a great use of a Raspberry Pi firstly, but then secondly, also just the application from your, in your personal life like that. Yeah, it's great. It's amazing. I think more people should try and do that sort of thing.

I wish I had more smart home devices. I don't have any, I don't think so.

Adam Jackson: Don't get it. Don't fall down the rabbit hole, Chris. This is never ending. My, my toothbrush can talk to it. It's, it's crazy, but it's testament to what the open source community does when you let them get excited about something, you see something like Home Assistant. And this is why I'm excited about Impact Framework as well, because I'm hoping we'll see the same passion. Being able, being able to talk to maybe not my toothbrush, but certainly things in the cloud, network infrastructure, and the devices that are really creating that carbon impact in our life. And see, let's see what the, what that open source community will come up with over the next few months.

Chris Skipper: Yeah, exciting stuff. We're going to keep, at least on the podcast, we're going to keep track of the work that's being done with the Impact Framework. So that's it for our episode regarding the decarbonized software at 2023 event. Just before we go, I've got two quick questions for you guys. I'm sure Adam, you could probably answer these. If people want to find out more about the rundown of what really happened at decarbonized software, where should they go?

Adam Jackson: Yep. That's a, an easy one. It is decarb.greensoftware.foundation. And we'll make sure we put that link in the show notes.

Chris Skipper: Yeah, absolutely. Link will be down in the show notes. And the next thing is what's the next big event for the GSF?

Sophie Trinder: So up next for the GSF, we've got a hackathon in February 2024. So definitely watch this space and watch our newsletter. That hackathon is all going to be centred on Impact Framework. We're really hoping to see not just carbon emissions being recorded, but also all negative environmental impacts like water, waste.

We've said before, the opportunities are endless with measurement.

Chris Skipper: Amazing. And yeah, looking forward to that and there'll be a pretty big announcement about that hopefully sometime soon. We've come to the end of our podcast episode and all that's left for me to say is thank you so much, Adam and Sophie. That was really great. I personally have learned so much. And, um, if you do want to watch, this is another thing about, um, Decarb 2023.

If you do want to watch it, please head over to our YouTube channel, where you can check out the talks that we mentioned in this podcast. So yet again, thanks for your contribution guys, and we really appreciate you coming on to Environment Variables.

Adam Jackson: Thanks, Chris. Yeah, it was great to come on and talk about the Decarb event and hopefully you'll have me on again very soon.

Sophie Trinder: Yes, thanks Chris. Thanks for having me.

Chris Skipper: Thanks very much, Sophie. Yes. Great. So that's all for this episode of Environment Variables. All the resources for this episode are in the show description below, and you can visit podcast.greensoftware.foundation to listen to more episodes of Environment Variables. See you all in the next episode. Bye for now.

Adam Jackson: Bye.

Sophie Trinder: Bye!

Asim Hussain: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we want more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation. Thanks again, and see you in the next episode.

View Details

Chris Adams is joined by Ines Akrap from Cognizant to talk all-things sustainable web design. Together, they delve into the nuances of designing energy-efficient websites and the challenges of green coding in frontend development. Ines shares valuable insights from her experiences at the Linux Energy Foundation Summit and the SDIA Green Coding Summit. The episode also explores common mistakes in optimizing sites for carbon efficiency and discusses exciting projects in the field of green software that are generating buzz. Resources like Website Carbon, Ecograder, and Lighthouse are highlighted, alongside discussions on the Software Carbon Intensity Specification and the CarbonAware SDK. This episode is a must-listen for anyone interested in the intersection of web development and sustainability, offering practical tips and exploring new research horizons in the quest to decarbonize the digital world.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Ines Akrap: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

Topics:* Designing Energy Efficient Websites | Linux Energy Foundation Summit Paris ‘23 [4:08] * Green Coding in the Frontend: The Good, The Bad, The Ugly | SDIA Green Coding Summit ‘23 [16:15] * SDIA 2023 Green Coding Workshop Slides | Chris Adams Green Web Foundation [23:41] * Mistakes when optimising sites for carbon [29:53] * Which projects in this growing field have you excited right now? [41:53]

Resources:* Website Carbon [10:01] * Ecograder [10:01] * Lighthouse [10:11] * W3C Sustainable Web Design Group [12:19] * Decarbonize Commerce 2023 | Green Software Foundation [18:56] * Careful Trouble [19:57] * How Thoughtworks uses Cloud Carbon Footprint for sustainability | Cameron Casher ThoughtWorks [20:32] * Power profiling with the Firefox Profiler | Florian Quèze [21:34] * Sitespeed [26:20] * Software Carbon Intensity Specification | Green Software Foundation [26:46] * DIMPACT [27:06] * The Week in Green Software: New Research Horizons [27:10] * Netcentric/progux: Progressive User Experience Library [31:42] * COP28 [36:16] * Firefox Profiler [40:30] * Linux Perf | [40:56] * CO2.js [42:12] * The CarbonAware SDK | Green Software Foundation [43:31] * Showcase — lowwwcarbon [45:22] * Sustainablwebdeisgn.org [47:07] * Green Software Practitioner Course | Green Software Foundation [48:13]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
Ines Akrap: You cannot fix something that you cannot measure because you just don't know that you have an issue. So being able to detect this issue and to show these numbers to the decision makers, I think this is something very important.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host, Chris Adams.

Hello, and welcome to another episode of This Week in Green Software, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. In this episode, we're joined by Ines Akrap, a developer who I first met in Paris at the Linux Foundation Energy Summit earlier on this summer, and most recently with whom I shared a stage at the SDIA. The Sustainable Digital Infrastructure Alliance Green Coding Summit in Berlin earlier on this month in November. We ended up talking about digital sustainability for front end developers, and we had such a good time that we figured it might be worth continuing this conversation on the podcast for other people who are curious too.

Ines Akrap: Hi Chris. Thank you so much for having me here. I cannot stress enough how excited I am to be here since I'm listening to you so much that it just came out on my Spotify wrapped at the end of the year.

Chris Adams: Wow, I, thank you, I did not know about that. Okay, so, and for people who are new, or who weren't at either of these events and didn't see you speaking, I figured it might be worth just briefly giving you the floor to introduce yourself and talk about some of your background for this before we dive into some of the specifics about what we'll be talking about for the front end, so optimising for carbon at the front end.

So yeah, Ines, the floor is yours.

Ines Akrap: Sure. So hi everyone. My name is Ines. I'm a web performance engineer and sustainable web consultant and cognizant and centric. And yeah, I've been doing this for a few years now with many different clients and hope that I can share some of these things with you today.

Chris Adams: Cool, thank you for that, Ines. And Ines, now, I know that we met in Paris, which for me felt really quite exotic and exciting. And then we met recently in Berlin, but as I understand it, you're based in Munich, in South Germany. Maybe we could talk a little bit about that before we dive into the inner nerdery of what we're going to be covering.

Ines Akrap: Sure. So actually I'm originally from Croatia, from Zagreb. I lived there and finished my master's degree until I was 20, 23, so more or less. Then I went for actually exchange year to Portugal, so I lived a year in Portugal. I came back and thought, Oh yeah, no, I'm not staying here. I need something more, something different. And I actually ended up in Barcelona. So I lived in Barcelona for five years and then this move happened, which people still think I'm crazy about, but I moved from Barcelona to Munich where I am now. And. I'm still very fond of this move. I am very happy to be here because my mind is way more German than people think.

I really love how things function here, but I'm definitely super fond of my memories in Barcelona as well. So yeah, currently I'm living and working in Munich.

Chris Adams: Okay, cool. Thank you for that. All right, then. So if you're new to this podcast, folks, as I mentioned before, my name is Chris Adams, I work as the chair of the policy working group at the Green Software Foundation, and I'm the executive director at the Green Web Foundation. It's a Dutch nonprofit working towards an entirely fossil free internet by 2030.

And as a reminder for people who are curious about what we discuss. Whenever there is a project or a story or a paper or a project online, we try our best to link to it in the show notes below this episode. So if there's something you hear about and want to learn more about, please do get in touch or please check the show notes because we spend a bit of time to make sure they're useful for other people who come along to this.

Okay, Ines, are you sitting comfortably?

Ines Akrap: Absolutely.

Chris Adams: Well, then let's begin. Okay, so as I first mentioned, I first came across your work when you were presenting with, I believe, your colleague Claire Thornwell at the Linux Energy Foundation Summit in Paris, where you were talking about your experiences building calculators and websites.

Tools to help clients optimize for carbon. Uh, and that was mainly for an audience of energy nerds and techies who don't really work at the web, or the web, website, and were actually really captivated by this. I figured it might be worth just talking about how that even came about in the first place.

Because yours was the only presentation specifically about web. And I enjoyed it and appreciated it. But I'm sure there's a backstory, so yeah, take it away.

Ines Akrap: Sure. Okay. So how long of an origin story would you like? Yeah, actually. So I, I was working a lot years as a front end engineer and with my background, so my master degree is actually in telecommunication and information technology. So I actually do have a background in networks and all these like data transfer. So this was always a very interesting part of a front end for me. So bit by bit, I ended up in web performance also as a person who doesn't really like to wait and is a huge rage clicker. This was a logical way. You know, I want to optimize it for myself as much as for everyone else. And I think it was end of 2020 where I was looking at this, of course it was end of 2020, so it was an online conference that I was looking at from the conf comfort of my sofa about JavaScript and just about this sheer amount of unused JavaScript. And the presenter at that point showed calculated just this rough number of unused JavaScript and started comparing it, of course, to carbon emissions and to trees.

And this was actually-

Chris Adams: Just a quick one, this is JavaScript, when you say unused, like when someone visits a webpage, you're talking about a bunch of stuff that is sent as like dead code that isn't actually used by the browser, is that correct?

Ines Akrap: Exactly that. So there is, these days, there is so much JavaScript that is just not being, well, that's being processed, but it just doesn't serve for anything useful on the website. So he was talking about this because there is this tendency in web development where you just put everything on a website and with the big systems, and of course, people coming and going, a lot of people are afraid to remove these things, you know, so this is how this thing came about and it was a moment of the mind blow turnout for me and for my career, when I realized this is even a thing, no? And then I went a bit like to search into the topic to figure out what, what this sustainable web even is and realize that in my work as a web performance, I'm already covering quite some strategies and optimizations that are leading towards, towards cleaner and greener web. And at this point in time, we already had a small web performance group inside of the Cognizant and Centric and Claire was part of this group as well. So we always function really well together. We are quite a dangerous combination because I'm an engineer and she's a business design person. So especially when we go together, we have the same kind of goal. We can cover quite a broad spectrum of generally topics and like points of view, like storytelling and all that. So we'd started working towards this topic a lot together, of course, with our team as well, who was the web performance team, quite embracing this whole topic. And this is how this part slowly came about. I guess the extra just to add on top is that we were building a tool that was a real user monitoring tool. So we can go a bit inside of that, that later. But basically, this tool was originally supposed to measure, you know, core web vitals, web performance metrics, and all that. However, then we came across CO2.js and we realized that we are already collecting the data that we can just plug in and actually give users, well, give our clients in a way, almost real time assessment of the carbon of their website.

Chris Adams: Okay, if I may just check with you one thing, you use this term real user monitoring, and this is, I think it's referred to as RUM sometimes, and this is the idea that rather than using an entirely modelled approach when you might, say, have a virtual browser visit a web page, you're actually, it's much more tied to having a well, as it says, a real user tracking this, so you've got a much better idea of, okay, you're collecting information about, say, it's this particular browser that's doing this particular work, rather than just a generic browser in that sense.

And that ends up being slightly more accurate than an entirely modelled approach. Maybe we could talk a little bit about some of those things, because you mentioned being able to translate from energy to, say, carbon and stuff with CO2.js, and I'm very happy to refer to that a little bit later, but as I understand it, when you, these two approaches of using, say, a RUM based approach or a kind of synthetic based approach, this brings out this this ends up making people aware that there are assumptions that you might use in a typical kind of website carbon calculator tool that might not be, might not hold true when the real user is accessing a website, like whether they're signed in, or they've got cookies set, or stuff like this.

And this can also have an impact on visiting a site, for example. Maybe we could talk a little bit about some of that stuff there, because I realize that this is something that you end up having to deal with when you're building some kind of, uh, actual tools that provide the kind of more robust numbers for this.

Ines Akrap: Exactly. So this was, to be honest, a bit of a game changer, no? Because when you think about, you explain as well, RUM tool very well. So what happens there is just, of course, you add a very small script to the website, to every single page of a website. And this is the huge deal as well. So when you use any synthetic, uh, monitoring, which is no, things like Website Carbon, EcoGrader, or any of these tools, especially in web performance, we usually, if you're in front end development, it's usually going to be web page test, it's going to be Lighthouse, something from that you're emulating. And what's happening actually recently is that you're emulating such a bad scenario that web performance may be quite good. In the case of carbon, actually, what happens is that there is no interaction with the page. And actually, 90 percent of session is happening in these interactions, no? After this first load. So with carbon and at this point in time, kilobytes transfer being a proxy for carbon, what's happening is that there can be a huge difference in between just this first load and actual number that we get if the user is interacting with page, if they're scrolling. So if the page is implemented well, and please do that, implement lazy loading and strategies like this, if this is implemented. We don't know if users ever loaded these assets or not. And this is where the RUM tools comes very handy. So as you already mentioned, accepting cookies and then starting to scroll, starting to click, starting to open stuff. This is where the number, let's say, of the transferred, transfer size can lead up let's say from, I actually, once I examined the website, It was four megabytes on initial load, five megabytes after the cookies were transferred, and 24 megabytes if you would scroll all the way down because of the amount of images. So measuring carbon by just this first view, by just this four megabytes,

Chris Adams: be five times smaller, yeah.

Ines Akrap: inaccurate, inaccurate, number.

So even though this number is still not super accurate, we are all aware of this, it comes much closer to the real scenario than I would say the synthetic one does.

Chris Adams: Oh wow, thank you. Okay, so that's um, a useful thing to take into account for people who are starting out with this, because yes, there are tools which you can begin, but there's often, there's basically quite, there's quite a lot of depth in this rabbit hole if you were to start doing this on a kind of monthly basis or kind of really use this to manage, um, uh, the performance of a website over an extended period of time.

Okay, cool. I also mentioned, I also saw that you have had some involvement with the W3C Sustainable Web Design group as well. And I figured, and I think I've actually heard you talking about that on one other podcast or seen you speak about some of that before. Maybe we could talk a little bit about that as well. Maybe you could talk maybe about the motivations for that and just show, just show maybe how that's going or what some of this might be, where this might be going in the future. Because we did do an interview, I think a couple of weeks ago, with some of the people who have been very involved, but maybe It's interesting to hear your perspective as well, because I think you're speaking and you're working at a larger organization, and the two people we were speaking to were from a smaller organization there, so I was, it was, I'm, I'd be curious about your perspective and how that's been going.

Ines Akrap: Absolutely. So yeah, it actually, this whole thing came to be because one of my colleagues, he was at the web performance conference and he met Zoe from Google. So she told him about this group even existing. So the moment he came back to Munich, he was like, yes, you have to join this. So this was actually very cool.

This was how I found out about this group even. And I actually came right in time because we were still, it was actually about a year ago. It was right. It Now, I think I'm probably hitting one year mark now in W3C, Sustainable Web Community Group. And yeah, it's been very interesting because there is such a nice diversity of people talking about this topic from different perspectives. So we started first talking a lot of, there was, of course, a lot of. so much for joining me today and I look forward to having a lot of interesting discussions about this approach because of course, as you and everyone listening to this knows, it's a very complex topic, there is like so much to it, so many nuances, and I was so happy to actually be a part of this conversation, especially because I was already working with some of the organizations trying to push this topic, so thank you And yeah, a lot of times it happens. I've seen this in web performance as well. A lot of times happens that it's a, quite a different scenario when you have a control, complete control over the things you're trying to improve. And when you don't, and a lot of times in these big companies, for example, the client I'm currently working with, they don't really have control over whole, like all the code because they're inheriting some of the parts. So this is a very tricky part to be in that you have to navigate around. So yeah.

Chris Adams: So just two things there. So you mentioned, so Zoe, this is Zoe Maria Lopez, I think, at Google. Okay, yeah, she's been on the, I've seen her on the mailing list talking about this and asking some questions already. Okay, and if I understand it, there is one flip side, which is, yes, when you've got, say, a very small organization and freelancers, there is possibly a kind of, people might feel like, okay, yeah, this is very much in line with my values, but you might not have the scale.

And then at the large companies, there's this idea that, well, we have the scale, but we're also publicly traded companies, and they might have different incentives. So the idea of having different people in that group should hopefully mean that you don't end up going more towards something which is really lovely but doesn't achieve any kind of scale, or the other side which is totally scalable but not really, maybe slightly more in the interest of shareholders than the planet, or everyone else, or the entire group, basically. Okay.

Ines Akrap: I think it's a very, again, like same as web performance, like it's very tricky topic because it's such a fine balance. No, it's such a fine balance. And actually one thing that I was just discussing recently with the client is just this. Of course, installing this culture of realizing the cost of something because you see the benefits, you see the business value. However, I think a lot of times. Especially the business perspective does not see the cost when it comes down to performance of the website, UX of the website, and of course, the energy efficiency and carbon of the website.

Chris Adams: I guess it's where the costs are being shifted to, for example. You might have something which means you've got nice developer experience, but if everyone's having to download three or four megabytes of JavaScript before they can use a site, that ends up being pretty ropey experience, for example.

That's like an example of a cost in this scenario. Okay, cool. Thank you for that. And we will probably come back to the working group stuff there, because I think that's something that's of interest. But maybe we could talk a little bit about the kind of fireside chat we ended up doing in Berlin together at the SDIA Green Coding Summit because I had a lot of fun. And we ended up talking about quite a wide range of topics given the time available. And I figured before we dive into some of the specifics about common anti patterns or easy mistakes you might make that you could learn from, or good examples of, say, galleries and things like, or things to learn from other people doing this well, are there any kind of takeaways from the event that you had?

Because I really enjoyed it and it was the first time I've seen where you've got, this was largely funded by the German government actually. They were investing in this particular field in a way that I haven't seen so many other countries doing so far. So maybe I'll ask you, are there any kind of takeaways that you had that, that you'd like to share here? Because you were there for the two days with me and there was a lot to take in, wasn't there?

Ines Akrap: Yeah, I was just going this morning, I was going through my notes and I actually quite like that. A lot of talks just confirm some of the things that I also stand behind that are my opinions as well, which is I would probably emphasize the part of the three important things to to move forward that was know that the fireside chat about how to make people care the way forward is awareness responsibility and regulation, so those three I think are very the three pillars in general that we need know so awareness responsibility and regulations I think those three are definitely a way forward to have it in mind And then, of course, a bit about the fact that companies move very slowly. This is something I felt on my skin so, so many times. So it took actually many months to even put this measuring tool that we offer on the client website, just because of the privacy concerns and all that. And it's actually very, it's made in a way that collects only. So even collector script is open source.

So it's making a way that it's very transparent. It collects only, uh, performance data. However, it took quite some time to get all the approvals to even start measuring this data, of course, calculating carbon. So I guess that one, and what else? Oh, yeah. And a great point from Anita as well, that we need sufficiency.

We need to learn to need and to use less. I think that's like a general, even when it comes to development, even when it comes to general life, we just, I have to have a feeling that we're already sufficient. We have enough of, again, I'm a bit generalizing here. Sorry. A lot of times we kind of especially. In this kind of middle, upper middle class, we have a lot, so just to start living with less and start delivering less.

Chris Adams: There were two things you said that I think are interesting that really caught my attention as well because at various, when you see other conferences take place, and we had Decarb from the Green Software Foundation just run last week, or maybe at the time of recording, when this lands, it'll be a few weeks, so please check the website for more details to check about the dates on that.

The thing that really struck me was A, there was this idea that there were organizations basically saying, yes, we're expecting to be regulated, and we're seeing regulation coming here. And that's something that I've generally seen lots of other organizations been pushing back against. But there was an argument being made that, essentially, you need to have this, to provide a kind of level playing field, for everyone to take this first step because, in the short term agreeing to some of this stuff either will be expensive or will incur some costs that will have to happen. And that was one thing that you tend never to see inside technology companies. So seeing organizations say that for the first time was quite a thing. And also, this idea of the notion of, okay, there is a, I think there's a really lovely quote or there's actually, I've ordered, I've ordered a hoodie from an organization called Careful Trouble, and I think it's Rachel Coldicutt, she mentions this lovely quote, just enough internet.

The idea being that there's a certain amount that you do need, and you, and there, and that's not the same as having to just like, just mash the accelerator pedal and just build as much as you can, basically. This is a interesting, in my view, a contrast to how I've seen other people talk about sustainability where there's this idea that, oh, we're going to have exactly the same kind of lifestyle, and, but everything's going to be electric, for example, and we're just going to keep using more and more.

So this was something that really caught my eye, actually. I think maybe there's actually one thing we might talk about when we were there, actually, was there was a number of open projects that were, that we saw, I think we saw Cameron Casher from ThoughtWorks talking about Cloud Carbon Footprint. And, uh, one thing that he mentioned, and we'll share a link to that, which is an open project that people in the GSF may be familiar with.

That kind of caught my eye. I can't remember where, there were multiple tracks and we'll share a link to this. Were there any other kind of talks by particular people that really caught your eye that you'd want to mention? Because the cloud carbon footprint thing was interesting to me because when we had one of the financial institutions listed there, they basically came out and said about half of our emissions are associated with ICT, and we're using tools like this to track this because we are getting numbers from different providers, but we also have things on premise, and this is one of the only ways we have right now to end up with some kind of numbers that are comparable across all the different providers and organizations we do have.

Ines Akrap: Yeah, I would say that my favorite deep dive tech, tech nerd talk, uh, was the one from Florian from Florian Quèze,

Chris Adams: Ah, yeah.

Ines Akrap: pronouncing your surname wrong Florian, but yeah, it was meeting him and talking to him. So he is working on Mozilla Power Profiler. And that was for me, it was just so many insights.

I love that tool and

Chris Adams: That was really deep.

Ines Akrap: out. Yeah, that was super deep and, but it's, it was super amazing for me personally, it was like, again, I'm familiar with this tool, so learning what's behind and then also getting an opportunity to pick his brain, I think that was one of my highlights of the event.

Chris Adams: His story about reverse engineering every single operating system to come up with some numbers was like, pretty like, wow. I didn't realize there was, it was that involved to do this. We'll share a link to both his talk to the slides, and I'm not sure when the recording will be online, but we definitely can share a link to the slides straight away, because that was actually a real, that was a real faith for me as well.

And later on, we'll talk a bit about that, because well, we basically did a workshop as well, and maybe that's one thing we'll spend a bit of time touching on. So, I actually ended up leading a workshop that Fershad, one of my colleagues, Fershad Irani, had designed with me. Basically giving people a way into looking at tools around optimising for carbon on the front end.

So we spoke a little bit about coming to some of the forcing factors that you might have in terms of basically there's regulation driving some of this, like in Europe you have the CSRD, the Corporate Social Responsibility Directive, which ends up manifesting in the laws in all various countries. But even in California, there is the, there's a recent law passed with a similar alphabet soup acronym, which I'm afraid I can't remember off the top of my head as I speak, but I'll add it as soon as I can to the show notes.

But we also speak a little bit about introducing people to tools like CO2.js. And other ones, which basically track this. So we started with that. Then we showed website carbon. Then we actually did a bit of a deep dive into the profiler as well. Actually, maybe I'll ask you actually, like you, you were in that workshop with, although all the way through with me and, uh, I, I realized that you also, you helpfully shared some specifics about the differences between cookie websites and stuff like that for people.

Are there any things that you might share for other people because we've made this an open source workshop and we'll link to the all 100 slides that we did for this. But for people who were about this and coming into this front end developers, are there any things you might share for other people who are coming to this for the first time and trying to talk about, like, maybe the, their first steps of tracking this or what kind of the common things you might need to take into account, for example?

Ines Akrap: Like first and foremost, I love the workshop. So for me as well, like there was a, at the same time on the, so on the green coding summit, they were on the second day, there were different workshops at the same time. So that was the, the worst part because I wanted to see them all. I gave that as a feedback. I was like, please give me, give me time to see them all. Of course I chose as well, I chose to be at yours to see as well how you approach this. So hopefully I can as well serve as an advocate for something like this because this was something I was doing this whole year was trying to raise awareness of this topic and I think what you did as well, did an amazing job. So for me, I knew most of these things. However, I think it was very well done. It was very like comprehensive and it was very, I was going through these basics of how to actually understand it and calculate it. And I think this is the biggest issue that we generally have is that people just not being aware and just not knowing how to do it and then where to start.

Chris Adams: Yeah, I think, I, thank you, first of all. The thing I, one thing that we were trying to do was give people an idea that, yes, there are models and there are tools, but there's also a lot of uncertainty in a lot of this, and there's a really nice quote that I think was shared, that Fershad added in, but that Simon Wardley has used in multiple places and goes back to the 80s, which basically says, all models are wrong, but some models are useful, with the idea being that, yes, we spoke about data transfer as a proxy right now because we currently do not have that much access to the information that you might need to come up with some more to draw more rigorous conclusions when you're trying to track the power used on a website.

And this is partly why we started with high level models, then moving into some tools like Website Carbon that you might be familiar with, and then diving into the profiling tools, because, to my knowledge, they're one of the only ways that you can get actual resource consumption figures from end user devices.

And before that workshop, we hadn't actually realized that these are usable for mobile devices as well. So that was actually a really nice thing to take away. One thing we got was that we had a couple of people from Mozilla, people who work on the Firefox profiler themselves. They joined the workshop to basically help figure stuff out.

And I think actually one thing that happened is over the weekend, the manual profiling steps we were demonstrating during the workshop, by the following weekend, some pull requests had been opened to fix some of the tools to automate this, and now there's a piece of software called Sitespeed, which now can run these on an automated basis.

So, that was actually quite cool, but it means that me and Fershad will now have to redesign the workshop for this, actually. There was also a really nice, it was a good chance to actually talk about some of the other models that we do have that are in the community right now, because we spoke a little bit about the Software Carbon Intensity, which is used by the Green Software Foundation, but it was also useful to be able to compare that to some of the other models that you might see, like the Sustainable Web Design 1 and the 1 byte model, or even Dimpact, which is like the digital impact one, where we had Daniel Schien come on a few weeks back to talk about that in a bit more detail. We'll link to that in the show notes as well for other people. But while I'm here, I figured I could ask you, are there some, there are ways we can do it right, but there's also, there's also some kind of common mistakes that you might see people making when they, when they take their first steps in this field, and I figured it might be asking you while you're here, and when you've seen people do some of this, are there like mistakes you might want to be looking out for if you are first taking a step into this field that you would give people a kind of heads up on if they were maybe a special, they know how to build websites, they might know a little bit about web performance, and they're trying to figure out how to transfer some of this knowledge into this kind of slightly new or updated domain.

Ines Akrap: Yeah, sure. I think the most important thing to have about this topic is that this topic is very vertical. So it's not one role in the development process that is responsible, which usually comes towards the developer. It's, oh yeah, they didn't implement it well. Yes and no. No, like it depends. It could be implemented, potentially not in the most optimized way.

However, a lot of times what I've seen is that no matter how good the implementation is, the moment the content comes in, it's when the things start shifting. No? Because we're talking again, there is just this sheer amount of assets, a lot of times of images, of fonts. I have a feeling that this overconsumption that we were already talking is happening without thinking what is actually beneficial to the user because now working in, in, in, in field of, well, I'm just going to call it now sustainability because the web are sometimes used interchangeably, however, green. Of course, just goes towards just reducing the energy and carbon footprint and sustainability goes more towards people as well, designing for the people, for the planet. So includes stuff like accessibility and in the end of the day, good user experience. And I think this kind of benefits the business a lot as well, because if you design something in a way that's fast, that's responsive, that's efficient, it's probably going to be better user experience, which will potentially convert into better conversions rate into better, which it's something that business is probably trying to do. So I guess my first advice here would be involve everyone. Make everyone in the process aware and make it a joint goal and not just the fight between developers or designers trying to optimize something and then let's say business kind of stopping them because it doesn't make sense on the business. It does, however, everyone has to understand how it actually does.

Chris Adams: Okay, and there was also one thing we spoke about, um, during the fireside chat was that let's say you're going to be doing some things with, say, carbon aware, this idea that websites might change or respond or functionality might be different based on the amount of fossil fuels on the grid, because this might be one way to materially or measurably reduce the carbon emissions in aggregate across a number of users, for example.

Uh, we spoke a little bit about there's some pitfalls and pratfalls around that. Yes, it's a cool idea and you can start using this, but there's, it feels like it's quite important to provide maybe a way to override some of this in many ways. You might be setting a default, but you're not setting a concrete limit in some cases because you might not understand the full context of a user.

Maybe that's something that you, we could talk a little bit about because I've, this is something we've seen done right, and then done poorly in some places, or maybe it's not done poorly, done in ways which, where there's a lot of room for improvement perhaps,

Ines Akrap: Yeah, for sure, because so this is something that I definitely advocate for is this progressive enhancement, which also goes towards the part of respecting your user's decisions, like what your user wants, what their current status is, because of course there is such a differentiation between the user, like just put yourself in the place of a user, which is something I usually try to do, since I'm quite a user of internet myself. It's just when you see this point of just trying to get this information. No, I just need an address of the place I want to go to on my phone. That's let's say in a Metro and my battery is dying. And then it's definitely not the same if I'm planning this trip in advance and I can see this website, whatever it is on my M1 MacBook Pro with my wifi in Germany.

So these are definitely different conditions that users have, and I have a feeling that this is something that's not being accounted for at all in general and going towards this road where we decide to design in a way that progressively enhance, that kind of respect these usual decisions, because not only this, so I worked on a small open source project that's called ProgUX, so of course it's out there, it's on the NPM, we can also link it.

So. Its point is that it adds to your website, adds a few of these parameters. So it adds the user network conditions. It adds data saving mode, if it's on or off. It adds the prefer, reduce motion. It's very important because some of the animations can trigger medical conditions at people. And not respecting this

Chris Adams: Wow,

Ines Akrap: only be mindless, but can be dangerous for some people.

So people can access this so they can enable this on their devices that they don't want the motion to happen. And I'll, well, most of the website now may, there may be some, some edge cases, but most of the website don't respect this. So what we created is just, it's very just few lines of code that just add this to your, to your local storage as well to CSS, however, the useful part is the developer part, which offers you a bit of a simulation of changing between these modes to help you develop faster, switch into these modes. It's been a while that we changed anything because it's, again, it's quite simple. It's quite straightforward. So we didn't improve it a lot, but again, feel free as well.

It's open source. Feel free to build on top of that. So having something like this, where we take these choices into consideration, know the network, the phone, the memory, the current data saving. And of course, these reduced motion stuff could make a huge difference in user experience and of course, with that, no, if we respect data saving and reduce, no, amount of processing, we're also again, reducing amount of energy consumed and working towards something greater.

See, okay.

Chris Adams: I can see a scenario where you might use some tooling like this to essentially simulate, okay, here's what someone's going to experience in a kind of low carbon version or a high carbon version, because one thing that we've seen is that, uh, either people might look at, say, a low carbon version of a website as an afterthought, rather than being something you progressively start with and then progressively enhance, like you mentioned.

But there's also this idea of, like, the ability to override is actually extremely important, because we, as designers or developers, we don't or we don't always know the context something's being consumed in and uh leaving the leaving that at the end user is actually very important and there's a really nice example that i think from Apple was that's worth looking at so Apple rolled out carbon aware charging leeron this year for all their phones which sounds like a cool idea with the idea being that on average, if you were to use this, what happens is that Apple devices, if the energy, if the grid has a particularly high amount of fossil fuels being burned on it, Apple's devices won't try to charge up right now.

They'll wait for the grid to become a little bit cleaner. So, over time, the average carbon intensity for the power you're using in a phone becomes somewhat lower. The thing is, when this was first introduced, because people were by default opted into this, the idea was that if you maybe were to go home, you plug your phone in, or which like you said, is on a really low battery, you leave it overnight, and then there's a like high amount of carbon, high carbon hours when you're asleep.

When you wake up, your phone isn't charged in anymore, and then you've basically had a really, really terrible experience of anything related to grid aware or carbon aware usage of tools. This is why this override seems like quite important. And being able to, like, make this more accessible to users, so they can see what it might be, think through some of the edge cases, actually sounds very helpful, actually. I didn't know that existed. Thank you for sharing that.

Ines Akrap: Yeah, yeah, I completely agree with you. And I think again, it's super important to stress without naming names as well, is that this progressive enhancement is more important than graceful degradation, where we do want to serve the lightest version first and then give an option to enhance it. You can, let's say.

Not serve images and then give users options. Okay, you have data, you have whatever you want. Do you want these images? Yes or no? Yes. Okay. No worries. We'll deliver them to you and not other way around because once the images are downloaded, the fact that you hide them, you didn't do much. No, in a way of this kind of processing power and transferring and all that, because they're already there. So they might as well be there.

Chris Adams: Okay, I work in a non profit and so there's, so I can say this, the, we're just about, I think we've just started COP28 and COP28 is a really good example of this right now. COP28 is the, for the first time we've ever seen, is a very high profile website that has a kind of green mode for this. But unfortunately, the way it was initially implemented was basically to serve the full fat version of a website so that any device that has actually used it has basically done all the hard work and used all the energy for the first time.

And then once you've done it, you've got the option to switch off the images, which does feel like it defeats somewhat some of the point of some of this. And I feel like this feels like a kind of concrete example of the opposite of this progressive enhancement. The idea would be that rather than do that, you would have a nicer experience where you start, and then you would gradually layer on the kind of more consumptive and resource intensive elements.

Is that what you're referring to here?

Ines Akrap: Exactly. That's the exact one, because let's go again in the, for example, the off motion, there's so many, for example, animations on the page that can trigger some people conditions, like you already triggered a condition. So the option that you can turn it off, it doesn't really make sense. The point would be like, okay, you don't serve them at first, but then if someone wants this kind of enhanced performance, no, and again, there is definitely a cool ways to automate that.

No, it's one of my favorite example is that like for shots Carbon Aware Edge Delivery, which is also a very cool thing. Link in the notes. So yeah, which is basically on the edge, it decides how clean or dirty your energy is. And then depending on that, it delivers something different. So you are already taking into consideration user's journey, user's conditions.

And of course, you will get a notification that says you're seeing the downgraded version. Would you like to be, so it leaves this decision to a user, which I think it's a very crucial part in this designing for people part. It's give users a choice. Yeah.

Chris Adams: We'll link to that, that thing in particular, the one that Fershad Irani has worked on, because this was something he did in his spare time, which I think is quite cool. It's essentially some of this carbon aware stuff, but rather than happening at the, um, client side inside the browser, it happens at the server side, so it decides to make a decision to possibly change some of the functionality at that point, rather than having to do something at the client side, where All, in some cases, you might have already downloaded all the information, so it's a little bit late at that point.

Okay, I'm really glad you mentioned that, because I was playing with that last night, and I thought, wow, that's cool. You also said something interesting about motion, and this actually made, it reminds me of one of the things that Florian Quèze, Florian, I'm so sorry if I've mispronounced your surname, Florian's talk, when he was talking about the profiler, yeah, about, he was showing that there is a, he was talking about how basically, depending on how you see these CSS gradients sometimes, like you might have a page which gradually changes colour over time.

He was saying, how basically, if that's done incorrectly, you can essentially cook a laptop, because you're just changing the colour of so many pixels and, oh, so many times, uh, in a given, uh, uh, If you're changing something maybe 120 times a second, and it's a 4K display, and you don't have any way of knowing what you had changed before, something just as innocent seeming as like a CSS transition can end up generating like a lot of power usage.

And like, that was cool, but the thing that was really exciting I saw was the fact that he was able to share a profile of this. So you could visit the page, and we'll share the link to the page so you can cook your own laptop or trigger your own fans if you want to, but he also shared a profile showing exactly where the energy, where this was happening.

So if you don't want to cook your own laptop, you can basically see a jump in power usage as reported using his profile run. That was so, so cool. I hadn't seen, I didn't know that was actually possible.

Ines Akrap: I love that, especially also because it shows as well a bit of this limitations at the moment with the models now, because what we were saying that also you still don't know this processing energy of the laptop and like basically one kilobyte. I don't think the CSS code was big, so I think it was around, no, like the CSS transition could have been like a kilobyte or two and it cooks your laptop.

So this is again, I think this is a huge topic to move forward with now, like to actually figure out how do we see that? But it was quite a cool thing to see with all of also with all of these, his gadgets, he has such a cool gadgets.

Chris Adams: Yeah, we didn't, I, the thing that really blew my mind was him explaining how, now that he's built these profiling tools, he's using it for all kinds of unexpected uses, so the profilers, so we'll show a link to the Mozilla Profiler for this because it's an open tool that you can use on any website, but the thing that was actually interesting is that it It doesn't just work for websites.

So he was showing how he can use it for basically Linux. Linux has a performance tool called Perf. So you can use it to track any kind of piece of software. And he was talking about how, yeah, you can use that. But after this talk, he said, well, Chris, I've also used this to profile my own house. And, uh, it turns out that if, because he knows where the data is from, say, a fridge, or solar panels on his house, or stuff like that, he's been able to just have a track, so like you see a track for, maybe, a web renderer, or something like that, he's got fridge, solar panel, front room, or something, and he's been using this to figure out, okay, well, where are the power hogs in my house, for example?

And the idea that you've actually been able to use, essentially, industrial grade profiling tools to figure out how to optimize your house was I think that was the nerdiest point of the entire conference, but that was pretty mind blowing when I saw that. There's a blog post about it that has to come out, and I think he might be presenting about FOSDM about some of this, because I didn't know that was possible, but it was very fun to see that.

Ines Akrap: Yeah, absolutely.

Chris Adams: Okay, we're coming up to time, and we've been, we've mentioned in a few, we've been nerding out over a couple of projects that we've that's been, that we're both excited about, but I wanted to give a bit of space. Which projects, open source projects, are in this kind of growing field have you excited right now that you would like to give a bit of time to talk about before we wrap up for this?

Ines Akrap: Yeah, I don't know. It's a on the spot. Well, I guess like my still all time favorite and again, like huge kudos to you is co2.js. No, I'm, I'm actually super excited as well about the prospect of having some more time towards the end of the year and to help out possibly with some. And what I've seen now in the pipeline of doing this no actually making it even better and better in a way of providing better carbon intensity data, so I think that's a huge thing no, specially with someone who actually uses this in real life . Also having this huge conversation with the client yesterday, about this measurement reporting and like let's say correct air quotes, correct these number from the ROM tool that we built are actually are having this underlying technology, which in our case is CO2.js getting more and more precise and giving us more and more power and flexibility. This is something I'm super excited about, because again, you cannot fix. Something what you just said with Florian, like you cannot fix something that you cannot measure because you just don't know that you have an issue. So being able to detect this issue and to show these numbers to the decision makers, I think this is something very important. And then improving these tools, especially again, I'm working the front end. So this is for me, big deal. I'm also quite, quite sure that the Green Software Foundation is, is doing quite an amazing job.

Chris Adams: The CarbonAware SDK, which is, which is on the server side primarily. Uh, so that's, uh, there's a somewhat slightly different area that they tend to do. But, and there's a couple of other projects. There's one called the Impact Engine Framework, which was actually introduced at Decarb conference, which does actually, which is extendable in this way.

So it can take data from a number of different providers or models or things like that. But yeah, thank you. That's very nice of you to actually say. This ProgUX thing, I I didn't realize there was actually a tool to make it that easy to simulate these different scenarios in such a fast way. Uh, we definitely should share a link for that one, actually.

Ines Akrap: It's not a simulation of actually how it's, how this reflects, but it's just a simulation of an implementation. So basically the small simulator just changes these CSS classes so you can see, of course, how your implementation changes in different scenarios.

Chris Adams: I see. Okay. Thanks, Ines. So, we spoke a little bit about ProgUX, and you mentioned CO2.js, and we spoke a little bit about the CarbonAware SDK, which is looking to graduate, to be a kind of graduated project inside the GSF, and we also mentioned the Impact Engine. I wanted to ask, if you're coming to this field for the first time, one thing that, maybe I'm showing my age when I say this now, is that when I was first messing around with CSS and realizing I didn't need to use tables for everything, was a website called the CSS Zen Garden that let me show and learn from other people.

And there was tools like CodePen and stuff where I could view source and understand this. I haven't been able to find something for sustainable web design, or kind of low carbon design, or anything like that. And I figured I might ask you, have you seen anything that you might direct people's attention to so they could learn from copying, or at least, or try and figure out where they start, because like we all know, this is open source. We learn from imitation before we create something ourselves for the first time, for example.

Ines Akrap: Absolutely. I'm actually very glad you asked because I just found out recently about this site called A lowwwcarbon. Link in the show notes. And yeah, it showcases all of these low carbon web designs and developments. So it's very cool. I haven't had time to see how I get featured there because I tried to do that with my website, but yeah.

Chris Adams: Okay, so this is low carbon, so it's low with three w's, like the www, so low www carbon dot com. That seems what it is. Okay, wow, this is cool. This is actually really nice, because it's These are real world websites, and some of these are run by actual large companies, as well as just personal pages. So this might be a thing for people who are curious, and want to look at this and see for the first time, see how it's being done by other people, if you're looking for inspiration.

Okay, well, thank you for that, Ines! All right, Ines, we're coming up to time now, and I just want to check with you. For people who are interested in some of the things we've discussed, we'll be talking, we'll be sharing these things in the show notes, but if people want to follow your work, where would you direct people's attention to if they wanted to do this?

Ines Akrap: Sure. So if you're interesting, of course, I'm always happy to answer any questions about web performance, about sustainable web. So I guess, of course, LinkedIn, Twitter, because I just still refuse to call it X. And as well, so also you have my, my, uh, my personal website. So it's InesAkrap.com. However, there is a shortcut to it, which is Ines.codes. So it will also redirect you to there.

And.

Chris Adams: Ines.codes?

Ines Akrap: Exactly. It will give you the bigger URL, but yeah, I have that domain for a while now. So yeah, but also I would definitely, if you want to learn more about this topic in general, I would direct you to W3C Sustainability Guidelines. So again, I think this is a great place to start.

So we put quite some, like a lot of effort in this. Also sustainablewebdesign.org Implemented recently these guidelines. So in the last podcast I was giving, I was, I said, bear with us. It's going to be implemented. So a kudos to sustainablewebdesign.org team. They implemented these guidelines. So it's a bit more user friendly because as you may imagine, W3C documents are not really a beach read.

So it takes some time to go through everything. So it's actually 93 guidelines. So there is quite something, but it's also, it's segmented by roles. So every single role can find their own starting point and to see they're also quite, they don't have a way, like it's not one, two, three, four, five, it's just. Pick one that you like, I guess our personal goal on this would be like, choose the one that says high impact, low effort. This is a pro tip, but yeah, basically I think this is the first place that you can of course learn something. There is also a huge pool of resources added to the guidelines that we used in shaping them.

So I think this is a good place to start familiarizing yourself with the topic.

Chris Adams: Brilliant, thank you for that Ines. I will also mention that for people who are coming to this, the Green Software Foundation actually has a free course available which will get you a kind of nice certified badge with a series of videos to provide a bit of helpful context for this. That's something that's of use, but Ines.codes, I N E S dot C O D E S. Okay, excellent. Thank you so much for this. I really enjoyed this, Ines, and um, thank you again for taking the time to, well, share a stage with me and share a podcast with me. Thank you.

Ines Akrap: Thank you so much for having me.

Chris Adams: All right, have a lovely weekend, Ines. Bye!

Ines Akrap: You too. Ciao!

Chris Adams: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts.

And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware. foundation. That's greensoftware.foundation in any browser.

Thanks again, and see you in the next episode!

View Details

In this episode of Environment Variables, we dive into a key highlight from Decarbonize Software 2023, featuring Asim Hussain's talk on the Green Software Foundation's newly introduced Impact Framework. This innovative framework aims to model, measure, simulate, and monitor the environmental impacts of software. Asim begins with an insightful overview of the framework's capabilities and objectives. Later, project leads Srinivasan Rakhunathan and Navveen Balani join the discussion to delve deeper into its applications and potential. This episode offers an essential understanding of how the Impact Framework is set to revolutionize the way we assess and mitigate the ecological footprint of software development and use.

Learn more about our people:
* Asim Hussain: LinkedIn / Twitter * Navveen Balani: LinkedIn * Srini Rakhunathan: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

The Impact Framework:* https://if.greensoftware.foundation/

Events: Keep an eye out for the announcement about CARBON HACK ‘23* - coming soon!

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Asim Hussain: Send us a manifest file so we can see not only how much is this thing going to cost us and how are you going to architect it, but what are the carbon emissions of your proposed approach? And let me compare versus the other people proposing approaches and not just compare on cost, but compare on carbon as well.

And I thought that was really, every time we talk to people about Impact Framework, people always come up with Another use case.

Hello and welcome to Environment Variables brought to you by the Green Software Foundation. In each episode we discuss the latest news and events surrounding green software. On our show you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.

I'm your host Asim Hussain.

Chris Skipper: Hello and welcome to Environment Variables. Today we've got a highlight from the recent decarbonized software 2023 event. We'll be showcasing the talk from Asim Hussain about the recent Impact Framework, which is a framework to model, measure, simulate, and monitor the environmental impacts of software.

That has been introduced by the Green Software Foundation. To begin, Asim will do a brief overview of the framework and later on he will be joined by the project leads Srinivasan Rakhunathan and Navveen Balani. He is introduced by our fabulous director of communications and member relations, Namrata Narayan. So it'll be her voice that you hear first.

So without further ado, here's the introduction to the Impact Framework.

Namrata Narayan: It's the moment we've all been waiting for. Well, one of many. I'm delighted to introduce our chairperson and exec director, Asim Hassan, back to the stage. The GSF believes the most important step in greening software is measurement. An Impact Framework will enable us to measure software across environments and software types. But don't take my word for it. Asim, over to you for a full, brief, and exclusive look.

Asim Hussain: Thank you so much, Namrata. And I was really excited today to see several talks now focused on measurement from Siemens, we just heard from, and from Code University. We're all aligned, and we're all converging to the same point. 2024, I believe, will be the year of measurement. That doesn't surprise me, because when we first launched the foundation, We asked all of our members what their pain points were, and the overwhelming answer was measuring.

And we've been trying to explore all the different avenues of measuring over the last three years of the foundation's existence, and we've made lots of progress. And I mentioned earlier on, we, the stuff, the standards working group launched the software carbon intensity specification, which has reached ISO.

We're very excited about that. It should be in the catalog shortly. We've incubated, incubated various data projects because we knew data for measurement was a problem. And we've drove the creation of, of a number of case studies, software measurement case studies. But now we're in the next evolution to have software measurement be and mainstream activity.

For this to be an industry with thousands of professionals working to decarbonize software, for businesses to grow and thrive in a commercial software measurement ecosystem, we need to formalize software measurement into a discipline with standards and tooling. And we believe Impact Framework is the tooling and SCI is one of the standards.

Today I'm going to explain a little bit about Impact Framework now, then I'll give a demo. I spoke to some of our other co leads on Impact Framework about potential future use cases for the tool last week when I still had some hair. And we'll play that afterwards. So Impact Framework aims to make the environmental impacts of software easier to calculate and share.

Impact Framework allows you to calculate your application's environmental impacts, such as carbon, without writing any code. All you have to do is write a simple manifest file. Sometimes we call it an IMPL. And Impact Framework handles the rest. I want to be very clear. It's called Impact Framework, not Carbon Framework.

Some of the things I'm going to show you today is about measuring carbon, but our goal for the framework is to go beyond carbon, to start measuring all sorts of different environmental impacts. There are three concepts in Impact Framework. There's the manifest file, which contains either raw data or information about where to get the data from to do your measurements.

Then we have models. How do you get from that raw data to, let's say, carbon or water or some other impact? To do that, we need to use models, and we can chain models together to calculate your impacts. Just in a pipeline, just like a Unix pipeline. Then we have Impact Engine itself, which is the CLI tool, the command line interface.

You pass the manifest file to it, and it computes your impacts of your software application. I would say it's saying transparency builds trust. You don't just calculate and share the number, the final number that the Impact Framework gives you. You share the manifest file. You share your workings out. You share.

You share all of your data, all of your assumptions, all of your coefficients so other people can verify it, can challenge it, can compute it themselves, can fork it, can adjust it, can change some of your values and run it again. It's all about being transparent. Only when you share your working out can anyone trust your calculation.

The project is entirely open source and composability is a core design principle. We want you. To be able to create your own models and plug them into the framework or pick from a broad universe of open source models created by others. We've got some to show you right now, which I can do in the demo, but our goal is for there to be thousands of models all working together.

What I'm going to show you today is a result of almost a year's worth of effort. We first started a talk at this project was proposed in December last year as an incubation project, and as it evolved into something incredible. And today we're ready to release the alpha version. Alpha. Means use with extreme caution.

There are bugs. I was trying it for the demo today. I found some more bugs. This is a buggy product. We are looking for early adopters who are comfortable with buggy software, non backward compatible changes. It's moving very fast, but if you are, if this is something that you're interested in, please try it out and please give us some feedback.

But you understand you're on the bleeding edge here. The sense of excitement from everybody involved is something I've rarely seen in this space. It's a bit nerdy. I'm about to show you a bunch of YAML files and get really excited about it. But trust me, these YAML files, I think are going to change the world.

One of the things I say about... My long term goals, and I hope the Foundation's long term goals, to do with sustainability is that we want to do to sustainability what open source did to software. I'm not talking about small, iterative changes. I want to change the game, and I think the Impact Framework will do just that.

You can find more information about Impact Framework at if. greensoftware. foundation. That's if.greensoftware. foundation. IF will also be the main focus of our yearly hackathon, which will be coming in February 24. We'll have all sorts of prizes this time around, including an under 18s prize and prizes for non technical contributions, so watch this space.

So now let's start the demo. So I've got an empty folder here. Well, it's not empty, but first you would create an empty folder where we can do our work. Impact Framework is built in TypeScript, so you can either use NPM or Yarn to initialize a space to work in. So I'm not going to run these commands in the space of interest, but you would probably run Yarn in it to initialize the space.

And then we want to start adding the CLI and the framework itself. So we do Yarn, Add. Run soft slash Impact Framework would bring in the framework itself. And we're also going to be using some models, some of those models I spoke about. So we've built some of our own models and we would install them in using IF models.

All of this, by the way, this is a tutorial at if. github. com. greensoftware. foundation. So you don't have to be furiously writing this out. And we've also got some other models in an unofficial models package as well. So after you've run all of that, what you need to do is you need to create a manifest file.

I mentioned that manifest file earlier on. Now I've already got a manifest file written here, so I'm just going to open it up. Here we go. So, this manifest file is a very simple one. It's going to compute the carbon emissions of a server we have running on Azure. Manifest files can be much more complicated than this.

Compute different software components, compute network, front end servers, user stories, campaigns, whatever you want. But for this demo purpose, we're keeping it very simple. Just one server. Let's walk through the YAML file. I'm just going to show you, let me just make some space here for a second. I'm just going to go through a couple of the aspects, the areas in the YAML file so you can understand it, the manifest file.

I'm going to first go through the initialize. So this is where we load up and globally define all those models that you want to use in your application. I'm going to go through some examples of this. You're going to see what I'm talking about. You would define where you're loading this from because you can, you could create a model.

Which you install. This is not, we expect a universe where there are thousands of models and you're just cherry picking which models you need to use to calculate your emissions. Some are loaded from unofficial models. We're not Microsoft, so it's unofficial for us to maintain the Azure model. But some of these are from our official models.

If it's coming from IF models, we're going to maintain this. We're committing to maintaining this. So this is the path of the module where it's coming from. This is the name of the class you're loading. And this is just how we're going to refer. to this model in the rest of the YAML file. Let me scroll down to another area, which is called a graph.

So this is where we describe all the software components we want to measure. In our case, we just have one server. Uh, cause again, we're keeping it very simple, but you can have dozens, hundreds of software components in it. And it, but it's up to you how you want to group them. Do you want to group all your servers by region?

Do you want to have a front end, a back end networking? Database, however you want to split it up and group it is up to you. We leave that very much up to you. It's just different components. Um, let me dig into my server then. So, this little, we call it a component node. This component node contains all the information required to measure this.

Server. I'm going to start from bottom to top. So I'm first going to start at this node called inputs. These are the inputs. These are the things you've gathered and measured about the server. What we call a key concept in Impact Framework is something called an observation. This is one observation. An observation is just something you've measured about your running system at a given time and for a given duration.

And these are the parameters of your observation. You can actually have multiples of them. We would expect you to have, maybe you grab observations every five minutes throughout the day. So we'd have a large array of observations. I've just got one here. The next thing to really explain is this thing at the pipeline at the top.

I mentioned before that we were all about models and a pipeline of models. The data here is passed in to the first model at the top, and it's just a piece of code. It's just a piece of code. And you pass in that observation and whatever outputs it passes it to this model. And whatever that outputs, it passes it to this model, to this.

And the game we're playing, the game we're playing is we've got this data here, this observation, some data about a virtual machine, and we want to convert this in this use case into carbon. And in order to do that, we chain these models together. They all work and play nicely together to convert all of that data into carbon.

Now to explain this all, the best thing to do is for me just to comment out. Some of the other models, I'm going to go through it one at a time, and I'm just going to run. The command, which is impact engine, you pass in the input file and you pass in an output file and you just let it run. The final thing I'll just measure, talk about while, while that's running is this config section here.

There's a bunch of different places you can configure models. This is one of the places you can configure models. And here. We just have some configuration values, which we're passing into some of those models. And this configuration here is specific to this component. So different components can have different configurations.

There's also a global configuration as well. So you can see here that file has completed, that execution has completed. I'm going to open up the results on this slide here. And excitingly, what we've got at the bottom is it's the same file, but as well as inputs, we now have outputs. And what the Azure importer model does is we've passed it some data.

To, to query and it's going into the Azure Monitor system and it's extracting out information about CP utilization, the memory available, it's 'cause this has all been captured on Azure and we're extracting it as a series of time stamps. What I've said here is, for a one hour period of time, give me 12 five minute buckets of the average CP utilization and, and other data.

And it captures other data as well. And a very important piece of data is what is the instance type of this Azure, the Azure machine that I'm running on. What is the instance type? We know it's Azure because the Azure instance, the Azure importer gave us that data. We know the instance type, but in order to calculate emissions, we need to know what processor is this instance type.

What processor is it? And for this, what we've built is another model called Cloud Instance Metadata. I am going to just run this whilst I talk. So cloud instance metadata is a module we're actually maintaining. There's actually very challenging, there's no real globally maintained database of telling you this instance type is this processor.

Every cloud provider is different, every cloud provider has lots of different rules. So we tried lots of different solutions, but what we ended up with is we're actually maintaining this model ourselves. We're maintaining a database of, we've only got Azure for now, but for Azure. This instance type is this processor and other information about that, and we will, we commit to keep maintaining this for the long term, and hopefully it's all open source, so if you see something missing, please write a pull request and add it yourself.

So you can see now it's complete. I'm going to go into the results. And in the outputs, again, you can see a couple more bits of information have been added. For instance, the physical underlying processor and another very important value, which is the thermal design power. So you can see here, very interestingly, that one instance type, if you actually look at the Azure documentation, it doesn't tell you exactly which underlying processor you're going to use.

Because when you use the instance type, you may get one of these three, one of these underlying processors. So it's quite challenging then to figure out what to do. So we have certain rules and logic which we've Worked with the community to describe and we effectively picked what's called the most energy hungry processor of that list because it's always better to overestimate energy than underestimate energy.

But now we have physical processor, we have thermal design, we have a bit more information from that cloud instance metadata. We still need, we need to convert this into energy to get to carbon. We need to know energy. What are some models that we can use to convert this data into energy? Now a really, uh, popular model that people use all the time is tes.

It was generated by a gentleman called Benjamin Davies, who worked at tes. It was a couple of years ago. It was published, and he figured out a, a, a generalized power curve by analyzing hundreds of servers, different types of servers, and it's quite well used. It's using a lot of our case studies. It's used in a lot of places is, is this tes curve and what Tes Curve needs in order to estimate energy is it needs a C utilization and it needs to know the thermal.

Design power of the processor. Now we have that data, we can run the script and it will effectively do a lookup of both of those bits of data to generate some energy. And, uh, EagleEye, if you would probably see that I also, uh, uncommented sci e. Sci e is just a little helper function that we have to, to copy some data into other, into an energy field, which is useful for the following models.

And you can see now we've calculated energy. So we've basically now, we've got to the point of... We know how much energy for this five minute period we are consuming. And this is in kilowatt hours, 0. 00284 kilowatt hours. This is one of the bugs. I don't, I want to make sure there's one of the bugs we discovered today.

That's slightly off. We will be fixing it tonight, but this is the, now we have energy. Now we have energy. How do we get from energy to carbon? Now, what you need to get from energy to carbon, operational carbon, I should say, is you need to know how clean or dirty was the energy. That is something called grid carbon intensity, and you would need to know every grid has a different measure of grid carbon intensity at different times, and we have several models that we can use in order to calculate grid carbon intensity.

There's a supplier, one, uh, Two electricity maps on Watttime are two of the biggest suppliers of this data. They're both members of the Green Software Foundation. We could be using the Watttime model because we've created one, but just to demonstrate another piece of functionality, what we've done in this case is we've actually just hard coded it.

There are some cases where you want to actually know what the grid carbon intensity every five minutes. There are other cases where you just want to use an annual average. And here's something that's very important. We've put in here 951 grams per kilowatt hour. This isn't hidden away in Appendix 96C of PDF 43.

It's in the YAML file. It's transparent. You don't, when you're being shared this YAML file, if you don't like this, you can go, Well, you know what? I actually want to use the Watttime model to actually get the real time energy or real time carbon intensity. Or actually, I don't agree with your value. I think it's 951.

This is what's so important. Transparency builds trust. We want to share everything, all of your workings out, all of your coefficients, all of your data. That's what you share, not the final number. So now we've run CIO. If we go back to the results, you can see at the bottom, we now have operational carbon.

So we finally got some carbon value. So for this five minute period, it's 2. 7 grams of carbon. And let's scroll down, that's 2. 708. And I think there's, hopefully there's one that's a bit lower to prove that it's working. Hmm. Well, it is working. It just says 2. 7. That's because it's hard to find the peaks right now.

But it's there. 2. 7 grams of carbon per five minute period. But we also want to include embodied carbon. We want to include embodied carbon. We want to include other types of carbon emissions. So, other... Components of the SCI calculation. So obviously being a GSF, we focused on SCI. So now we've also got SCIM, which is, it gives you the embodied carbon.

It's very basic right now. You have to provide a lot of data manually, but we're looking in the future, some of the things we're looking to expand is to, is to make this a bit more automated. So again, it tries to figure out what the embodied carbon is from the instance type and just calculates it more manually.

And SCI then actually calculates a SCI, a SCI score. Thank you. So let me run that again, and then now I have a slight, uh, awkward pause, I'll wait for that to run. And again, it's just that this, the really important, I was trying to, I cannot reiterate it strongly enough, you do not share the final number, you share the manifest file.

Manifest files are executable, there's no need to share the final number, you just share the manifest file and the next person just runs it, and they, and it gets the same data. You can actually hard code the actual data, you don't need to put the Azure, So you can actually put the results of Azure as inputs, and then that would actually be a static file that you could share.

So now that it came through and we can see, here we go, we've got the size score, we've got the embodied carbon per 5 minute period, and we have a size score of 32 grams per hour for that 5 minute period, and a 32. 4 per hour for that 5 minute period, and a 34. 2 per hour for that 5 minute period. So now we've got it.

We converted some raw imports into carbon emissions. Okay. So that is the very final thing I will just mention really quickly is, let me talk about another model that's been built by Intel called IEE, Intel Energy Estimator. Intel Energy Estimator is a drop in replacement for other energy models like TEEDS.

It just has much more accurate energy estimates for Intel policy. It actually has a... Data for each and every Intel chip type. Um, but the, and this is how you would configure it. And the power of IEE is that I can just go into here. And just drop in IEE. Each of these models has standardized interfaces and standardized parameters.

Standards is what creates the ecosystem. By having standardized models, we can plug and play, we can cherry pick, we can tune it and get exactly your calculation pipeline that works for you. So let me run that. Really quickly, and as it's running, I'll just talk a little bit more about how it actually works, because you can see here, it's a little bit different.

I mentioned that Impact Framework is TypeScript, and that means that, um, every model that we've seen so far has been written in TypeScript. They might call out some API, but it's written in TypeScript. You can see here that the IEE was built in Python, and what you can do with Impact Framework is you can actually call out to a CLI tool and do a shell command instead.

So you don't have to write your models in TypeScript. You can actually write your models in any language that you want, as long as you can create a CLI tool, which adheres to a specific open standard that we've created. It will plug and play into the Impact Framework, which is really exciting. That's all for the demo today.

You can find more information again, as I said, at If. greensoftware. foundation. And as a reminder, also in Feb next year, we'll be hosting rCarbonHack again, and Impact Framework will be the focus, so please watch this space. Next up, I spoke to Navveen and Srini, two other co leads of the project, about potential future use cases.

That was last week when I still had hair. Roll the tape, please. So with me today are two of two of the co leads of Impact Framework, Srini and Navveen. Navveen, why don't you give a quick introduction to yourself?

Navveen Balani: Yeah, thank you Asim. Hi everyone, I'm Navveen Balani. I'm a Chief Technologist with Technology Sustainability Innovation Group, working at the intersection of technology and sustainability. I've been involved in the foundation right from its inception and leading various projects in the foundation. Over to you Shimi.

Srinivasan Rakhunathan: Hey, thankNavveenen. Hi everyone, this is Srini. I'm part of Microsoft. I've also been with the foundation since the beginning and really have got an opportunity to do a lot of learning, multiple projects, all open source, so many people, so just love the energy here.

Asim Hussain: I remember the journey of all the projects that both of you have been part of since the very early days, and we've all started working on kind of measurement with the SCI, and you both started looking at... To calculate carbon emissions of software, we needed, we knew we had a data problem and you both went away and started taking the lead on the SCI data project and really started becoming experts in just the data aspects of software.

I won't go into all of the iterations, but we had a couple of iterations there until we landed on Impact Framework. I think everybody's just seen, we've just given a demo of Impact Framework to a lot of people out there in the world. And they've probably seen like how it works, like in a very practical sense.

But I wanted to just have you two here so we can talk a little bit about future thinking. This is what the Impact Framework is right now. What do we think it can be used for in the future? It's a very generic, it's very low level. So I'm going to throw the floor to Navveen probably to start off with.

Maybe just give us some ideas. Like what, what are your, what, what, what inspires you about this? And what do you think about applications for the future?

Navveen Balani: Yeah, so I think the future roadmap, uh, I think would be to extend the back engine framework for measuring the SCI scores for an AI application, uh, both during training as well as inference. And, uh, from a carbon emission measurement, uh, like during the training phase, uh, so we need to capture the server types like, uh, GPU and TPUs, have data for embodied emissions and capture various utilizations like, uh, memory and CPU. Uh, I think next we need to look at how we could integrate with available models or build models that provide the carbon emission calculation based on available data and obtain the SCI score. And also include various other factors like data processing and storage as part of the SCI functional boundary for overall AI training. And for the inference part, I would say, uh, this might be a bit, uh, tricky, uh, based on your deployment model. Uh, for instance, uh, let's say if you're hosting and have a control of the servers, uh, you can follow a similar measurement approach as in training, uh, and using function units, uh, such as number of, uh, inference calls. But if you have a deployment model, And let's say, which involves maybe a generative AI system, like sending prompts to a charge GPT or any LLM models. You basically need to rely on some proxy data such as API latency, maybe a number of iterations to get the right prompt response. Or overall prompt, uh, context and maybe the length and so on. So this is an area of exploration, uh, where we need, uh, open source, uh, communities to collaborate and contribute models, uh, based on various, uh, research and findings. Probably in the end, our goal is to basically look at impact engine framework to realize the SCS specification and make it easier to report SCS code for any software workloads.

Asim Hussain: Would you imagine a future where, as people develop papers and as they develop more advanced algorithms for AI, alongside this research, you deliver a manifest file, an impact manifest file where you're, you're explaining, this is this new type of AI algorithm, and this is the impact that the algorithm might have.

Copy it, fork this file. Play around with the numbers, see how it works for you. Do you see something like that as well in the future?

Navveen Balani: Yeah, definitely. That's a good point. Having all the research. Papers, right? Have this manifest file, right? And which can make the research also more compatible. And this can be a framework, right? Which can be used by any practitioners, right? To, uh, deliver their CS code.

Asim Hussain: Yeah, great. Yeah, we definitely need to apply this to AI. It's a big burgeoning field out there and it's a lot of computes going into that space. Shrini, what about you? What thoughts have you been given to this? What have you given to this area?

Srinivasan Rakhunathan: I think AI is a fantastic concept because both the Impact Framework and AI can learn and build and evolve and emerge together. That's a great synergy opportunity, but also on the, the enterprise side, or even the consumer side where you have multiple devices, multiple environments, multiple cloud providers to hyperscale providers. There is a big opportunity. With Impact Framework, because it truly is an open architecture of bring your own model or bring your own calculation algorithm. And at the very, I think when we spoke about it at the inception, the very concept we wanted, we wanted to do is to make it as granular as possible. So you have building blocks on top and any technology, whether you have Node. js, you have React. js or on the server side, anything that you can. You just have to make sure that the granular component is straightforward so that you can apply it for any kind of architecture, whether it is mobile or desktop or cloud provider. And that's a beauty of the model. And that's the beauty of the architecture I feel so that it can scale to any use cases, whether it is a consumer use case or an enterprise use case.

Asim Hussain: Yeah, I love that term, bring your own model. I think let's put that in all the material. I think that's a really good way of explaining it, isn't it? Bring your own model. Yeah, I remember when we were, like, one of the things, like, both of you have been also to the people who've been really at the cutting edge of actually calculating software.

There's not many people in this world who've actually. Put the time and effort to really dig deep and figure out the emissions of, of, of a piece of software. And I think one of the things that we discovered throughout our entire process is, as you're saying, Srini, everything's a little bit different. One model does not work for everybody, you need to tweak it a little bit for every single use case and every single, yeah, there's a lot of tweaking and can bring your own model to the situation.

Navveen Balani: Yeah, absolutely. I think the other area is how do you make sure that you get more people to do case studies, which we had been doing through manual calculations. And that's where the open source community can bring in user models for all their use cases. And we can learn.

Asim Hussain: Yeah. Oh yeah. There's been so, so many conversations to, to get us to this point where this Impact Framework, it's, yeah. So many things we can talk about. One of the things I've, I, I found quite interesting. I, I was chatting to a large enterprise organ, an airline, a large enterprise organization that's an airline.

And they were describing, and I was explaining Impact Framework to them. And they were quite interested 'cause they were, because they obviously put a lot of RF qs out, a lot of requests for quotes, requests for business. And what, and they also have stringent rules regarding the carbon emissions. They won't have carbon limits on the software that they build.

And what they were proposing is when an organized, when they put an RFQ out and they get a bid back from an organization, they were suggesting as well as a bid, send us a manifest file so we can see not only how much is this thing going to cost us and how are you going to architect it? But what are the carbon emissions of your proposed approach?

And let me compare versus the other people proposing approaches and not just compare on cost. But compare on carbon as well. And I thought that was really, every time we talk to people about Impact Framework, people always come up with another use case, which is what gives me so much excitement about this project, because people are seeing solutions that we didn't think about when we've been talking about this for as long as we've been talking about it.

Navveen Balani: I think this is definitely a good use case, uh, think of this as a calculator, right, which you can first create, right, how much emissions, uh, your infrastructure will take, and maybe that can be integrated with your CI, CD, Terraform, just to know upfront, right, what would be the impact. And if you can make it simplify this whole integration via plugins or calls, right, and make it native to each, uh, programmers, right, the tools that they use, I think we'll achieve what we want to achieve.

Asim Hussain: Awesome. I think we're coming up, coming up to time now. So one of the things I wanted to make sure. That we cover is actually we're going to be running a hackathon. We ran a hackathon last year. It was very successful. It was the Carbon Hack with a Carboner SDK, but the CarbonHack will be coming again.

First quarter of next year. And the main theme of the carbon hat will be measurement and measurement with the Impact Framework. And we're going to be looking for people to build models, that'd be cash prizes. People build models, build impulse, and we're going to have. prizes for best documentation, non technical contributions, all sorts of different prizes.

And I'm going to have an under 18s prize as well, which I'm really excited for. So we've got the Carbon Hack also coming up next year, which is, and the main theme is going to be measurement and Impact Framework. And I'm just so excited to have. Have that on our agenda. I just want to thank again, Navveen and Srini, you both have been just key players in the Green Software Foundation since day one, this project evolved on all the work that you've done from the start.

And I want to thank you and I'm really excited to, really proud and excited to have you here working all of us together on this project.

Srinivasan Rakhunathan: Thanks, Asim.

Navveen Balani: Thank you, Asim, and thanks to the community.

Namrata Narayan: Thank you. Okay, so really excited to finally see Impact Framework. I hope everyone sees why we're so excited and hopeful about the impact this open source tool will have on the industry. We've got a lot of questions, so we're going to try and get through, um, two of them, um, as best as possible. So, as an Annie panel asked, Would Impact Framework be recommended for use on a simple website, or is it better applied to a more robust application? And Neil Clark added to that question and asked if a website is hosted via a CMS hosting partner, like Acquia, abstracted quite far away from the actual server, how can we capture observation data?

Asim Hussain: Yeah, and to the first question, absolutely. Impact Framework is very general purpose. Even right now, I've been talking to you about how to measure software emissions of a server. One of the samples we have in the repository, I believe we still have it, is measuring our website's emissions, which website is built using GitHub Pages, it's a static website.

And obviously it's like a normal website. We haven't actually built the models that are required to measure that. Unfortunately, that's a limiting factor is you need models. You need models that convert network bandwidth to, uh, CO2. We were going to use CO2 JS. We need models that perhaps take data from, uh, Google analytics to help then use other data to figure out, well, what are the, what is the energy consumption on the client side?

So it's all limited by models. That's what we're limited by. But yeah, you can absolutely, uh, measure, measure websites. In fact, we've had the spoiler alert. You can measure anything with it. You can measure physical products. And I think the last question was around, yes. How can you measure when you don't even have access to the server?

Absolutely. That comes up all the time. We're building this thing. You build what's called an adapter model. So for instance, there's a lot of things, even in the service base, you don't have access to, like when you're running like, uh, serverless functions, you don't know the server. You just have some other.

bit of information like gigabyte seconds. Again, it's limited by models. We need models that convert gigabyte seconds to carbon, but we've started to think about how to create those models. And again, as we come on to carbon hack next year, we're really hoping the community comes together and starts filling in those gaps.

This is what I'm talking about. We need thousands of these little models. We want to fill those gaps and build those models. And you can cherry pick them together in order to calculate all sorts of carbon impacts. And other impacts, my dream is to like add water, add other impacts. I want to, we, it's called Impact Framework, not Carbon Framework.

Namrata Narayan: Thanks, Asim. Another question from Cristiano Elias. I hope I did not butcher your name. Is certification support of the results output in the roadmap of Impact Framework?

Asim Hussain: It's not currently in the roadmap of Impact Framework, but it is something that we've discussed. For instance, one of the things that's been, we imagine is the models that you use, perhaps in the future, we will generate some official models. which may be used more in a certification, but essentially if there is any certification, it's a certification of the models.

So you might get a whole bunch of models which are useful for a variety of use cases, only this, this certification agency will only approve this small set of models or for this type of. Computation. We only accept this model pipeline. We imagine it's going to evolve something around that, but we're a little bit early.

We're just alpha today. So we're a little bit early on to have any kind of specific roadmap items on certification. But it's something that we've thought about.

Namrata Narayan: Thank you, Asim. I hope everyone was happy with those answers. We did get a lot of, many more questions, but we will answer them at a later time. So stay tuned, subscribe to our newsletter.

Chris Skipper: So that's all for this episode of Environment Variables. If you liked what you heard, you can actually check out the video version of this on our YouTube channel. Links to that, as well as the Impact Framework, can be found in the show notes below. While you're down there, feel free to click follow so you don't miss out on the very latest in the world of sustainable software here on Environment Variables.

Bye for now!

Asim Hussain: Hey, everyone. Thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we want more listeners.

To find out more about the Green Software Foundation, please visit greensoftware.foundation. Thanks again, and see you in the next episode.

View Details

This Week, host Chris Adams is joined by TU Berlin researcher Iegor Riepin to talk about the benefits - and trade-offs - associated with load shifting over both space and time. Together, they nerd out over the specifics, discuss numbers, and weigh alternative methods of computing with green energy all around the globe. Iegor and his team did a study alongside Google, where they modeled the entire European electricity grid in order to study the effects of different types of load shifting, and how it can be most efficiently applied to the world of Green Software.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Iegor Riepin: LinkedIn | GitHub | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* https://pypsa.org/ [03:21] * RE100 [09:47] * What? The sun isn't always shining?! - by David Roberts [10:16] * XFaaS: Hyperscale and Low Cost Serverless Functions at Meta [47:30]

Resources:* https://github.com/PyPSA [03:21] * An introduction to energy's hottest new trend: 24/7 carbon-free electricity * System-level impacts of 24/7 carbon-free electricity procurement in Europe [11:22] * The value of space-time load-shifting flexibility for 24/7 carbon-free electricity procurement [13:24] * PyPSA · GitHub [22:20] * GitHub - PyPSA/atlite: Atlite: A Lightweight Python Package for Calculating Renewable Power Potentials and Time Series * Electricity Maps [50:40] * GitHub - PyPSA/247-cfe: Explore the impacts of 24/7 Carbon-Free Energy PPAs [55:55] * 24/7 Carbon-Free Energy Compact [56:25] * Open Energy Modelling Initiative * PyPSA meets Earth * PyPSA-Earth: A flexible Python-based open optimisation model to study energy system futures around the world.

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:
Iegor Riepen: Capacities of wind, solar, and storage required to achieve hourly matching of demand with carbon or clean electricity are reduced when we increase the share of computing jobs, and that means the share of power loads that are flexible. So, in short, demand flexibility makes carbon-free computing more resource efficient.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host, Chris Adams. Hello, and welcome to another episode of This Week in Green Software, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. When we talk about green software, we often talk about code efficiency, because it's something that we're often already familiar with. But as you learn more about integrating sustainability into software engineering, you end up learning more about the underlying power systems that all our servers and end-user devices like laptops and phones rely on too. And because the power systems we rely on are in the middle of a generational shift from fossil fuels to cleaner forms of energy, there are changes taking place there that can inform how we design systems higher up the stack. This summer, a team of researchers from Technical University Berlin published a study in collaboration with Google to help shed light on this emerging field. They modeled the entire European energy grid with open-source grid modeling software written in Python, along with a set of internet-scale data centers, to better understand how scaling their use of compute to match the availability of clean energy can affect the associated environmental impact with running this kind of infrastructure.

If this was interesting enough, But the modeling also revealed some interesting findings about the cost of transitioning to digital services that run on fossil-free power every hour of every day. This sounded like absolute catnip for sustainable software engineers, but because this is also one of the first open studies published around carbon-aware software, it's possible to understand the assumptions behind these results and figure out how they might change in future. So if you want to learn a bit more about this, to help in this quest, joining me today, we have one researcher from the Department of Digital Transformation in Energy Systems at the Technical University of Berlin, Iegor Riepen. Hey, Iegor.

Iegor Riepen: Hi Chris, thanks for having me today.

Chris Adams: Iegor, it's lovely to hear from you again. Before we dive into the world of grids and carbon-aware software and the like, can I give you just a few moments to introduce yourself?

Iegor Riepen: Yes, of course. Hi, everyone. I'm Iegor Riepen. I'm a postdoc researcher at the Technical University of Berlin, where I'm part of the Energy Systems Department. In our department, we use methods from operations research and mathematical optimization, researching the cost-effective opportunities for climate neutrality.

This means I spend most of my time writing, solving, and debugging mathematical models of energy systems. Our research group also maintains an open-source Python environment for state-of-the-art energy system modeling, which is available at pypsa.org and GitHub/PyPSA.com.

Chris Adams: Okay, cool. Thank you for that. So, I know that I actually met some other folks in the same department as you from actually an event called Clean Coffee that I used to run at ClimateAction.tech. Tom Brown came along to one of those Zoom calls back in 2019 and from there we just kicked it off. So, And that's how I found out about anything going on in Berlin. And I understand that you've been in Berlin for a while, but you weren't always studying and working in Berlin. You've been in other parts of the world as well, correct?

Iegor Riepen: Yes, that's right. I'm originally Ukrainian. I lived up until I was 20 or so, and then I moved to Germany to make my masters' studies, then academic career. Before Berlin, I was doing my Ph.D. in the Brandenburg Technical University, where I worked with Professor Felix Müsgens, and I worked on my Ph.D. in various questions of modeling energy systems.

When finishing Ph.D., I joined, as a postdoc, Tom Brown's group in TU Berlin.

Chris Adams: Cool. All right then. And that's how we ended up here then. Okay, so we're just about to dive into the meat of the show. And here's a reminder that everything we talk about will be linked in the show notes below in this episode. So if there's a project mentioned, or a site, or a paper that we refer to, please do write in and tell us so we can update the show notes for other curious souls and help you in your quest for knowledge. All right, Iegor, are you sitting comfortably?

Iegor Riepen: Yes, I am standing comfortably.

Chris Adams: Okay, all right then, let's begin. So it's really tempting to jump right into the nerdy specifics about this research and so on. But before we do, can you share a little bit about the background from your current research for this to provide the context for the work that we're about to discuss?

Iegor Riepen: Yes, of course. So over the past year and a half, my colleague, Tom Brown, who is the head and the heart of our research group, and I have been working on the open-source, model-based research dedicated to various aspects of 24/7 carbon-free electricity matching. This concept usually goes under the name hourly CFE matching.

The 24/7 CFE is a new approach for voluntary clean energy procurement, where companies aim to match their electricity consumption with carbon-free or clean energy supply on an hourly basis and around the clock.

Chris Adams: Okay, so let me just check if I understand that. So normally when people say they run on green energy, they might be talking about things on an annual basis. And this is so hourly, so it's what's 8, 760 hours in a year. So it's 8, 760 times higher resolution. So you don't have this whole thing where if you say you're running on green power, you're not making a claim of running on clean energy at night, for example, something like that, right?

Iegor Riepen: Yes, exactly. That's pretty much about that. So, it's interesting because the 24/7 carbon-free energy hourly margin aims to eliminate all in-house gas emissions associated with electricity use of an energy buyer. So, the strategy also aims at addressing the main problems that exist in much in demand with clean energy supply.

When using so-called Established Certification Schemes, the audience of the Environmental Variables might know all this pretty well, but I'll just name a few to outline the context. So, companies who would like to demonstrate their sustainability credentials might opt for buying the guarantees of origin, this has a story related to Europe or the renewable energy certificates or renewable energy credits.

This is a story related to the United States. A common feature of these schemes is that renewable energy credits are, so to say, unbundled from megawatt-hours of energy. When using the schemes, there could be several problems that would arise. So one of the problems is that assets procured with these credits, or the credits you procured from certain assets, this might not be additional to the system.

This means if you buy renewable credits or guarantees of origin from an asset located in a particular system, Norway, and the asset was located in Norway, is located in Norway, and will be located in Norway, no matter what your procurement, it's hard to claim the change of the system associated with your matching strategy.

The second problem is typically arising with using guarantees of origin is so-called mismatching location. So if demand is located in Germany, and the energy asset generating the Renewable Credit is located in Spain, there will be hours when the grid between Spain and Germany is congested. So it creates an accounting problem.

It's likely not those electrons were consumed, that were produced. So, these two are the so called additionality problem and location matching problems that arise.

Chris Adams: Okay, so if I just check if I understand that. So one of these issues was about additionality you mentioned. So if I understand, what you're saying is, let's say that you got some form of generation. Yes, you get paid for the power you generate. But there's another thing that people are paid for, which is like the kind of greenness of it. And this, as you say, ends up being unbundled and traded separately and there, you, basically a bunch of problems tend to happen once they're unbundled in that scenario there.

So you spoke about something in Spain like, yes there might be a grid where you could theoretically have a solar power, solar farm in Spain generating electricity, but whether it's actually really deliverable to somewhere in Germany is another matter, because it might not be physically possible to deliver that power.

So there's, this is some of the kind of complexity that it's trying to address here, if I understand that right.

Iegor Riepen: That's correct. And some energy buyers do think about this and recognize these problems, and they opt for power purchase agreements. These are bilateral contracts between buyer and supplier. And when signing power purchase agreement, these companies would pledge to buy both the energy, so megawatt-hours and the environmental credits bundle to it. The problem here is that under power purchase agreements, renewable energy supply is typically matched over a long period of time with buyers energy demand. So, for example, there is plenty of companies who are joining the known Renewable 100 group who claim to procure right enough renewable electricity to match their consumption on an annual basis.

The problem here is, guess what, renewables are not generating at all hours throughout the day. And this concept is sometimes called in the literature as renewables are non-dispatchable. Sometimes it's called that they're intermittent. Sometimes people say that renewable energy is variable. There was a recent awesome podcast from Volts, where host, David Roberts, had Jesse Jenkins, who suggested the term weather-dependent fuel-saving technologies, which I think is an excellent way to put it forward,

Chris Adams: yeah,

that's

Iegor Riepen: the way we will likely use it today. So when energy buyers sign PPAs with weather-dependent fuel-saving technologies, there definitely will be times when generation is low, so energy buyers have to depend on procurement from the local markets that likely have some carbon content in it in a given point of time.

Chris Adams: Okay, so, just a quick translation. You said weather-dependent fuel-saving technology. That's opposed to, essentially, if I'm going to be burning gas or coal, I don't have to care so much about the weather, but I'm having to burn a bunch of stuff, and the whole combustion of fossil fuels is one of the problems we have here.

So, that's how you might frame it, right? So, because once you've built something, you don't, presumably, once you've got, say, wind or solar or something like that, it's renewable, so you're not having to purchase the fuel. That's the distinction that we have there, right?

Iegor Riepen: So the term which I referred, which was coined by Jesse Jenkins in that podcast, referred to as dependent fuel-saving technologies, refers to the content that when we use renewables, we do not have to buy fuel, which comes at cost. We do not burn fuel, which comes with carbon emissions associated with burning it, and we don't have to think about the fuel.

Chris Adams: Okay. All right. Thank you. Now we've got a kind of, we've got some of these terms sorted out now. Now we can talk about how some of this might work in the context of data centers and things like that. So maybe I should ask you a little bit about this study. So we've, we've done this work now. Now maybe you could just talk a little bit about what the study that you were doing with Google and with TU Berlin was about for this.

Iegor Riepen: All right, so we have an ongoing research projects where we collaborate with Google. As audience might know, the company has claimed a commitment to achieve 24/7 carbon-free electricity matching in all of their data centers worldwide by 2030. And from our side, we bring an academic look to a broad range of questions relevant for making data centers, and more broadly, any consumers from commercial and industry sectors carbon-free. These questions are like, how can one achieve hourly matching of demand with carbon-free electricity? At what cost this comes? How can advanced tech help? Or what would be the impact on the background grids? We released a series of open studies aiming to address some selected aspects of this complex question. So, where demand flexibility comes to the story? Demand flexibility is the degree of freedom that companies pursuing their goal of reducing carbon emissions can use and benefit from. This refers to a broad range of companies with various degrees of flexibility, which takes many forms and colors, mostly of temporal demand management, and perhaps even more interesting, this refers to the demand flexibility of computing infrastructure or data centers that can be geographically scattered and managed collectively by one entity or one company.

So, data centers as electricity consumers have some special perk. They have an ability to shift computing jobs and associated power loads in space and time. And in July, this year, we released a new study where we focused specifically on space-time load-shifting problem. So we look at the role the space-time load-shifting can play in reducing the costs and resources needed to achieve perfect 24/7 matching.

We thought about the signals that companies can use for shaping their load, and we also looked at the trade-offs and synergies that arise from co-optimization of spatial and temporal load-shifting.

Chris Adams: Okay. So I'll just try to make sure I follow that from a kind of layperson point of view. So there's basically maybe two things that came out of that. So one of the, one of these things is this idea that in addition to, if we know that the amount of power we might have be generated from clean sources might change over time, it sounds like there is a chance to, rather than have to generate more, just actually make supply and demand match just by scaling back some of your own energy usage.

And this is something that isn't just done inside the technology sector. For example, I know that buildings might do this to cool a building down where the energy is cheap, for example, at night, so that when you walk in, it's nice and cool, for example. Or if you're in Texas or somewhere, where it's a, it's a nice, comfortable environment.

So it's taking, that's the kind of moving things through time. And that's one temporal thing, but there's something special about computers and data centers in that. Rather than just moving the energy, you can move the work to somewhere else where they have an abundance of power. And that's the kind of special thing that you ended up doing a bit of study, studies into, right?

Iegor Riepen: Yes, exactly. We focused both on space and time flexibility. We write in the study that space-time nowadays mostly is a story of computing infrastructure, data centers. Temporal flexibility applies to a broad range of companies who have various forms of temporal demand management.

Chris Adams: Okay, cool. All right, then. So we've spoken about that. And as I understand it, maybe I should just ask a little bit about, so what's the benefit of doing it this way? Like, why would you even think about trying to match some of this stuff up rather than just buying a bunch more green energy for example or a bunch new solar farms.

Iegor Riepen: Well, thinking about this, imagine a company with an inflexible demand wants to match its own consumption with carbon-free electricity. It could source carbon-free electricity from various sources. This would be a combination of re-imports if the grid is clean or clean enough for your purpose. Uh, it could be generation of renewable generators procured with power purchase agreements and dispatch of storage assets. This is a pretty challenging task, since battery storage is helpful for bridging some hours of no wind, no solar, but it's not the right technology or better frame, not the right economic technology for times when you need to firm weather dependent wind and solar over an extended period of time.

So, pre research done by Princeton University, NetZeroLab, folks from Peninsula Clean Energy, and also from us last year, did show that 24/7 CFE hourly matching is possible with commercially available technologies like wind, solar, and lithium ion batteries. But it comes at large price or cost premium and with some curtailment of renewable electricity.

If consumer following our imagination have an access to advanced tech like hydrogen storage or clean firm technologies, their price premium could be reduced. Data centers could use this special perk, so the ability to shift loads over space and also time, to relax this problem of matching demand with carbon-free electricity supply.

Chris Adams: Okay, so what I think you might be referring to here is the fact that because there's this flexibility that reduces the amount that you need to buy to have ready, uh, to match the entire time. So it may be that you don't need to buy so many batteries or have so many wind turbines or something like that.

Yeah.

Iegor Riepen: Yes, so put it simply, you can move loads from the places where you have access to the loads where you don't have enough carbon-free electricity, and by moving the slots you could possibly save potential storage needs, and you can also save or reduce the amount of excess electricity you would have that you might have curtailed otherwise.

Chris Adams: Okay, and by when we just briefly touch on curtailing, that means that rather than just wasting, just not being able to use this energy, you're, you're able to put it to use to some kind of productive use, which basically improve the economics means like you might reduce the cost of running something, for example, so it might pay for itself doing something like this.

Iegor Riepen: Exactly. If you have signed PPAs with an asset or you built an asset on site, you likely have some access of energy in some uh, hours. You could sell this access to the background grid, if the background grid takes it at a price, you could potentially store it, but you would store it up until point. The storage is economical and some part which you would not store or you would not sell.

You would typically curtail.

Chris Adams: Okay, cool. And curtailing for the purposes here is basically having to throw it away because you can't use it productively. All right then. Okay, thank you for explaining that. So we spoke a little bit about some of the details on this, and it might be worth just briefly touching on some of the open approaches for this, because you've mentioned a tool called PyPSA, which I think is Python Power Systems Analysis?

It's something like that, right? And this was, there was a the open part of the study is quite a key thing for, for this project. Is that correct?

Iegor Riepen: Yes. So we use um, um, PyPSA, which is an open-source Python environment for state-of-the-art system modeling. This is a tool which our group develops for and maintains for our own research, but also it's been used by wide range of companies, institutions, NGOs, TSOs, by some others who might find a use in open-source tools.

So PyPSA itself stands for Python for Power System Analysis, as it was originally scoped for the power system analysis. However, nowadays the tool is used for many other applications, but for Power, which includes transport and heating and biomass, industry and industry feedstocks, some carbon management, sequestration, hydrogen networks, and what else.

So the open-source Python environment which we ship or which we maintain includes PyPSA itself, which is a modeling framework, but it also has several individual packages that make it possible to go all of the way through the data processing, such as calculating renewable energy potentials in different countries that we model or collecting energy assets data to creating and solving complex energy optimization problems.

So why would open-source modeling be interesting? There are a couple of things which usually comes in place answering the question. This could be transparency and credibility. So by doing open-source modeling, we show that we have no cherry-picked assumptions. In our, um, studies that would drive certain results. Open-source is also pretty useful for reducing wasteful multiplication of work. We can think about it so there is plenty of energy modeling groups in academia worldwide, but also energy modelers in consultancies or in industry. All of us are doing basically the same job, but if all of us have to create an

Chris Adams: your own model. Yeah.

Iegor Riepen: Before we fly the airplane, we are not progressing much, and doing open-source is quite helpful too.

Sometimes you can just copy from somebody who did a good job and put it in this open license and go ahead.

Chris Adams: Okay, cool. That's actually, so that sounds quite exciting. So essentially, if someone's going to say, "oh, I think we can decarbonize this industry by this date." You can essentially model it and say, "these are the assumptions I'm making. This is why I think it's possible. This is why I think we can afford it. And, uh, this is how much I think it would cost," for example. And, uh, the idea that because it's open, it becomes easier for, say, policy makers or civil society to basically say," Hey, you've made a really weird assumption here. I challenge that and vice versa." And with it being modern, open, there were, although we've mentioned Google a few times, this could be used by any company or any organization that might also want to see if this would be applicable to them for in running any kind of infrastructure themselves.

Is that about right?

Iegor Riepen: Yes. When we do, for example, our study, which we today talk about, which is released in GitHub is on a special kit release. And everybody who can run a Python script could reproduce our results, could see how our assumptions are formed, what we put into our optimization problem as parametrization, and if you wish, you could basically get the same result on your local machine.

If you have this way, you can be pretty sure that we did not do some cherry pick stuff to, to shape or drive results in one direction.

Chris Adams: cool. That's really interesting. I didn't know that I could model the entire European grid on my laptop to actually try and settle a bet in the pub. That's quite cool. All right then. So maybe we just, let's go back to this study then. So we've spoken a bit about this and we haven't actually discovered or discussed the findings.

So maybe I could actually ask you, um, are there any particular key findings you'd like to share so far? Or is there any nuance we should be, be aware of before we dive into some of the kind of juicy results here, for example?

Iegor Riepen: Um, yes, sure. I think we could address this nuances topic first. We could just briefly go through the study design and key assumptions driving our results, so the audience would understand where from are. So, for this study, we used the computer model of the entire European electricity system. With this model, we simulated the early operation of the electricity system and the so-called system development, so we looked at the cost optimal investments the system would have in generation and storage assets for the model tier.

We placed five data centers in and we chose the regions where we placed our data center source to capture grids with different sets of features, unique renewable resources, and national characteristics. We assume the data centers have a nominal load of 100 MW for simplicity. This assumption of "What is the exact nominal load of data centers doesn't play any big role in the results?"

If we have smaller or higher capacity assumption, we would observe the same trends.

Chris Adams: Ah, okay.

Iegor Riepen: we And we configure our mathematical problem that all datacenters follow 24/7 CFE goal. So, to achieve this goal, datacenters can co-optimize electricity procurement from the local grid and procurement of additional resources such as storage, wind, PV generators that are additional to the system and located in the same meeting zone.

And we assume that datacenters have some degree of load flexibility, which we vary with scenarios. Stepping from 0%, which would mean that there is no flexible workloads, so all loads are inflexible and must be served at places of data center location, up to 40%, meaning that 40 percent of data center loads are flexible and can be shifted to other places or delayed to other times.

This is what we do. What we do not. First, we do not quantify the actual costs and technical potentials of achieving certain share of flexible workloads, we just say, "hey, this data center fleet have some share of flexible workloads. How would you optimize the flexibility utilization and what benefits it might bring?"

We also treat data centers simply as large consumers that can shift a certain share of loads, which is not too far from reality. But what I mean here is that we abstract from the technical aspects and properties of flexible workloads and some physical constraints of quick ramping. There is, uh, tech folks who could focus on these topics with their, uh, uh, with their, uh, knowledge.

And we base our model inputs only on freely available raw input data. So for electricity systems, we parametrize the system mostly from Danish Energy Outlook. And for data centers, we assume pretty generic transparent assumptions. Where, so we by, by this, we try to keep our study design broadly applicable for other companies who might have their specific flexibility shares or forms or shapes.

And we try to keep our workflow available at GitHub for everybody to access and reproduce.

Chris Adams: Okay, so if I understand that correctly, essentially, you're doing this with as much open stuff as possible so that someone can reproduce this, and the assumptions you're making about these data centers, it doesn't, although the size doesn't matter that much, 100 megawatts is about, that's like a medium sized to large hyperscale data center. So this is, again, it's, it's somewhat reflective of the reality. And you also mentioned that they're in different parts of Europe. So I, from memory, I think this was like Ireland, which is like windy and in the West, Denmark, which has loads and loads of wind, there was like a few other places in Europe as well with different kind of generation and different geographics.

So they're in different places. So it was somewhat representative of the regions we might use in cloud, right?

Iegor Riepen: Yeah, so data centers, eventually we scatter it in Ireland, Denmark, uh, west one zone, uh, Finland, Germany, and Portugal. Uh, the idea was that we would take regions with different renewable resources. First, regions that would be pretty far from each other, and also we would take regions where there is data center consumption in national energy mix.

And by that we take different enough regions and we would capture all the system dynamics that we would want to.

Chris Adams: Okay, cool. That sounds somewhat, I can recognize that with my kind of cloud hat on, thinking about running something in Ireland versus running it in Germany in this scenario. Okay, well, that sounds like we've given enough background for this. Should we dive into some of the findings? Is there anything you'd like to, so yeah, maybe I should ask, what was maybe one of the first findings that really caught your attention that you'd like to share from this?

Iegor Riepen: So I think we could go through several steps. That's the first finding that usually has been caught by people looking at our study is this topic of resource efficiency and cost reduction. Just for audience to understand, from our model, as a result of optimization, we get procurement strategies for each data center, which optimize to match demand with carbon-free electricity around the clock with some desired quality score.

So the cost optimal technology mix that we get as an output depends on various factors, for example, renewable resource, this would be wind to solar average energy yield, or cost assumptions and many more. So the clear trend that we observe across all scenarios is that capacities of wind, solar, and storage required to achieve hourly matching of demand with carbon or clean electricity are reduced when we increase the share of computing jobs, and that means the share of power loads that are flexible.

So, in short, demand flexibility makes carbon-free computing more resource efficient. What we also could do, we could retrieve the cost of any procurement strategy from our model, and thus we can map the resource efficiency to the cost effectiveness, meaning you pay less to achieve exactly the same. So the degree of this cost effectiveness scales with the level of flexibility that we assume.

So for the corner scenario where we assume that 40 percent of flexible workloads perfect hourlCFE matchaging and co-optimized space for achieving the overall energy costs of the model data center fleet are reduced by up to 34%. So this refers to the cost saving of an individual data center, but it refers to the cost saving of a group of data centers scattered geographically and managed together by one company.

So these data centers consume basically the same amount of megawatt hours, but do shift their consumption in space and in time to optimize the resources.

Chris Adams: Okay, so if I just, maybe I'm just trying to run that by you so I understand. So essentially, you model different amounts of flexibility in a system if you're controlling multiple data centers here. And essentially, the more flexible you make it, the more you can actually reduce the amount, the cost of actually having to buy all these solar farms and wind turbines and batteries and all the way that, all the way up to the point where, if you're doing 40, if you're got 40% of your loads being flexible, then it reduces the costs by about a third, essentially. That's what I think you're saying there.

Iegor Riepen: Yes, that's right, but we should see it in perspective that this 30 percent cost saving is basically our corner scenarios. We scale the cost very up, so scaling very up means we look at the perfect matching between uh, demand and carbon-free electricity. 100 percent that you are not allowed to have any gram of CO2 peak allowed hour of consumption.

And also we assume in this scenario that 20 percent buyers only have access to wind, solar, and lithium ion storage. So this is a palette of commercially available technologies which are just hard to use out of these technologies to make 24/7 strategy. If these two are right, then your costs are reduced by up to a third, and the costs are reduced less than that for all palette of asset technologies and scenarios that we considered in this study.

Chris Adams: Okay, cool, well thank you, that's, that was bigger than I was expecting it to be. Uh, that's, that's, that's, that's, that's pretty impressive if you're going to be spending, um, literally billions on power, like some large, uh, data center providers or data center users will be using. Okay, then, um, Iegor, so, if I understand correctly, the amount of flexibility you might introduce, this kind of carbon-aware computing, that, if you say that you need to be running everything on 100 percent carbon-free or fossil-free or clean energy, based on this, then this will reduce the amount that you need to purchase, which essentially makes it more affordable or more accessible to a wider number of operators, I suppose. Are there any other findings that you would draw attention to in this study?

Iegor Riepen: Um, yes, of course, what we do in the study, we take a look on the signals that companies might use to shape their load following strategies. So to discuss the signals, we could firstly go for special shifting story and then for temporal shifting story. So for the special shifting story, the one signal which comes up front is the fact that hourly profiles of wind power generation have a low correlation over long distances due to different weather conditions. So as a rule of thumb, you can think of the following. If two generators are located as far as 200 kilometers from each other, the hourly feed in from these assets have very low correlation, and data centers could arbitrage on this effect, or put simply, they could move load to locations when and where there is a high wind generation.

That's saving the cost of energy storage and thus reducing the amount of solar curtailment. So, the hourly profiles of wind generation is not the only signal. Another signal that we discuss in the study is the difference in quality of renewable resources in regions where data centers are located. So, the quality of local resources, or in other words, the average capacity factors of Solar PV in a given region, they translate to the cost of electricity.

The higher the quality of renewable resource, basically the lower the average cost per megawatt hour. Special load-shifting is possible. A rational buyer could just adjust own procurement strategy to contract generators in better locations. So those locations where renewable assets have lower costs and co-optimize special shifts accordingly.

In the study we illustrate this mechanism with a data center located in Ireland, so it's not the most sunny region in Europe, that would tend to shift loads away during daytime through mid spring to mid autumn. So data centers located in Germany and Portugal, the regions with much better solar resources than in Ireland, they would tend to receive loads during this period.

This feature would just work about reciprocally for wind-related load shifts. Data center in Germany would benefit from having partners in Denmark or Ireland that have much better quality of wind resources. And, so there are two signals for spatial shifting. There is one more, which we did not put much of focus in our study because of our geographical focus scope, but it could play a role for spatial load-shifting.

So if you look above Earth from the North Pole, and the Earth would rotate counterclockwise from West to East. And we are pretty sure that it rotates with a constant predictable speed, roughly once per 24 hours. So if data centers are scattered across the globe in distant locations and operated by one company, one could imagine a load-shifting strategy where loads would follow the sun.

Chris Adams: Yeah.

Iegor Riepen: So these are basically three signals for spatial load-shifting for temporal load-shifting story, we illustrate cases when the variability of the regional grid emission intensity could drive the carbon-aware temporal load-shifting. So the grid signal can play a role in load-shifting strategy if data centers have electricity imports from the local grid in their energy mix.

And the temporal flexibility could also be helpful in aligning the demand in time with the generation of procured renewable resources.

Chris Adams: Okay, so it sounds like there's almost two kind of scales you're working at here. So the first thing you spoke about was like, say, Ireland and Germany and Portugal. Essentially, so basically Germany and Portugal are sunnier, and Ireland is windier, and during the summer, they're going to be, Germany and Portugal are way sunnier, so if you were running say computing in these three places, you might choose to run more of it in those two during the summer, and then as it gets a little bit darker, you basically choose to run everything in Ireland instead, and that's going to be a much more efficient way to actually, essentially run, maybe, if you're going to run computing jobs at 100 percent carbon-free energy, that's a way that you can do that at one of the lowest costs.

So that's, there's one thing happening at the annual level, but you also said there's a kind of another thing which is much more tied to the kind of, you know, day and night cycle that you're referring to as well there. So there's different speeds that you might be thinking about, different trends that you might take into

Iegor Riepen: consideration.

Yes, we talk about pretty complex optimization problems that spans across space, spans across time, and the signals that would drive optimal utilization of flexibility through this space-time graph have various shapes. Some signals have stochastic pattern, like wind and feet, um, which is uncorrelated over long distances. Some signals have predictable pattern, like solar profiles that follows the Earth's rotation. And some, um, some signals have something in between predictable and unpredictable.

Chris Adams: Oh, cool. Wow. That's, I wasn't expecting that. Yeah. So we spoke before about, okay, one thing that you could do is essentially during summer, you're running your computing jobs in Germany and Portugal where there's loads of sun and loads of clean energy and that's relatively cheap. And then in winter, you'll choose to run it maybe Ireland, or somewhere where it's a bit darker, a bit gloomier, but way windier. And, uh, where there's loads, oodles of green energy there. But you certainly have some trade-offs that you have to make here, if you were to choose this. Maybe you could just expand on some of that a bit more, so that people understand, so that it doesn't sound too good to be true, for example.

Or people understand some of the specific nuances here.

here

Iegor Riepen: Yes, very right. What we do in the study, we take a look on scenarios where we co-optimize um, and Isolate Utilization of Spatial and Temporal load-shifting. So these scenarios with isolated flexibility can be seen by just academic exercise, but it's pretty useful for us to take a look on the system mechanics and get a feeling of the numbers.

So as a result of utilization, we can retrieve the value, which would represent something like reduction of the overall annual energy cost of a carbon-free electricity supply. If a data center utilizes either spacial load shifts or temporal load shifts or both, if we compare the value of spacial and temporal load management, uh, when, um, spacial and temporal stories are isolated, we come to the numbers of something from 6 to 1, depending on the scenario, in favor of spacial load-shifting.

So this means, spacial shifting workloads across locations brings you 6 to 1 high amount, high value. And this takes place because datacenters can arbitrage on differences in weather conditions and take advantage of. So this is a mechanism which we have just discussed. Shifting workloads across time to bring a higher value, uh, requires a few things.

So for that to, to have a high value, datacenters would need to buy electricity from the background grid, which is high variability of the original grid carbon emission density. So if a local energy mix is flat, dirty, or flat, clean, there is no, basically, value to shifting workloads from one time to another.

And the tr-de offs would appear uh, between spatial and temporal load-shifting when both are implemented together. So one can think about this in this way, if you have a certain share of flexible loads and you would like to shift some in space and some in time, but whatever you shift from other places and other times cannot exceed the upper cap, which would be the computing capacity constraint.

And whatever you shift away, that means to other places or to later times, cannot seek the lower cap, which would be the flexible workloads cap. And, uh, one thing on synergies, what we do show is that co-optimization of space and time load-shifting can yield benefits that go beyond the value of each of the two individual mechanisms could bring alone.

It's sort of an expected outcome for any operation's research problem. If you have two degrees of freedom, and you co-optimize them, uh, you could co-optimize in a way to get the benefit from synergies of them both. So in the study, we come to this point from various angles, but here's just a good example.

Imagine if you have, say, three data centers scattered far from each other and operated by a single entity. Then imagine we have each data center, which has a mix of wind and solar capacity built on site. Let's assume that this data center can shift workloads with any fixed volume of flexible workloads.

Now, somebody comes and says that, "hey, we have one long duration energy storage asset that we could place in either of the three data center locations."

Chris Adams: A big-ass battery, basically. Yeah?

Iegor Riepen: Yeah, the question is here, where would you place it to reduce the energy cost of the entire system? If you would write an optimization problem for this, solve it uh, we would tend to see that the optimization problem suggests us to harvest renewable electricity in the best locations. So those locations where the lowest cost per megawatt hour is achievable. For example, Denmark, Ireland, with good wind conditions. And integrally opening access to this cheap, clean electricity for all locations through the spatial load-shifting.

Chris Adams: So that thing you mentioned there was, you've got this notion of moving things spatially or moving things temporally through time. So it's, essentially, you get more of a gain from moving things geographically, spatially, if you're going to do nothing, if you just only do one. But that can be a little bit harder for organizations. So there is some gain from doing things temporarily, but on the temporal scale, you do need the grid to be a little bit more volatile, moving back and forth between very suddenly and then not very suddenly, for example, so they start using back, go back to dirty energy essentially, but the thing that you can do is these do work together, so you can move through time and space, and you do end up with a, basically the benefits do compound in this case here.

Iegor Riepen: Yeah, and it's worth saying that the benefits actually do not compound simply together, because the spatial and temporal stories are subject to the shared set of computing capacity constraints. So when you co-optimize both, you inevitably have to trade off among them.

Chris Adams: Okay, compound is the wrong word then. All right. But basically, the, by doing the two things together, you can get, you can get a better saving than just doing one of them by themselves, for example.

Okay. All right then. So we've spoken about this, how it's been applied to one company. And we've said that this could be used for multiple organizations. Um, presumably, if you... If someone was to do this, you could do this for an entire sector to figure out what the power might be needed for an entire sector to see how much you might need to deploy to, to displace all the kind of fossil-based energy generation that data centers use, for example. Is that plausible that you could do something like this with this kind of modeling?

Iegor Riepen: Um, well, in our study, we try to keep our assumptions on carbon-aware computing, in the way how we treat data centers, how we treat flexible workloads, as general as possible. So the study results should be applicable to the broad range of companies operating data centers, with their specific features and their specific workloads.

And as well as the study should be applicable to a broad ranges of companies from commerce or service or industry sectors for which, say, only a temporal story is relevant. One cool thing here is that data centers can pave the way for space-time load-shifting applied for other industries. Other applications we are not yet even aware about.

So just to mention, I recently visited, um, the group in the University of Wisconsin, Madison. It's Victor Zavala, uh, Scalable Systems Lab. So this is a bunch of awesome people. I spent with them three weeks. I'm not really sure what they work about, because they work about computational chemistry, on energy systems, on graph theory, optimizations, programming.

I think they crush every problem that people are throwing at them, and when I was there, they were launching a new project which was focused on exploiting space-time interdependencies between electrochemical manufacturing and power grid. So the idea here is that the electrochemical industry would shift loads so as to co-optimize the economics and to reduce the carbon emission intensity of the electrochemical manufacturing, which is pretty dumb.

Uh, because before I thought that, that space-time shifting is more about data centers only. But now, well, there are applications beyond only this sector. And I think this is a future where we are going to.

Chris Adams: Okay, so basically, as more and more, as more and more clean and, what's it, variable fuel saving technologies come onto the electricity grid, it's going to get more and more kind of upy downy variable. And it's not just data centers this would be applicable to. So electrochemical stuff would be like synthesizing fuels or making plastics or things from carbon captured into, by the, from the air, for example, or things like that. I think Tom Brown mentioned a little bit about making methanol in this kind of way, or some of the green hydrogen stuff around splitting water into hydrogen and oxygen for creating chemicals that way. So is that what you're referring to in this scenario?

Iegor Riepen: well, I don't know what they will do in the project. It will be very interesting to take a look. I'm not sure that it's very simply mapping one to another. So for data center special shifting means that you move. Workloads and associated

Chris Adams: space, that

Iegor Riepen: one place to another. But this moving means that just, um, computer jobs are being executed in one data center and not in another data center.

While the end consumer is somebody waiting for the YouTube video to be rendered, consuming the goods at the place it would be consuming no matter the shift. How exactly it works for the electrochemical industry, not sure, but we will see once the project is developed.

Chris Adams: I see. Okay, cool. All right. You mentioned one thing about this being something which is more generalizable to a wider set of technologies, and one thing that actually this makes me think of is a new paper that was published by Facebook. They have a serverless platform which they call XFaaS, and one of the key things that they were doing is actually having this kind of geographically movable computing that they refer to, and one thing that, what really strikes me is that Facebook basically said by allowing the actual computation to be flexible in terms of where it's actually run, they were able to massively increase the use of the data centers they were using.

So if you think about it, for most data centers, there might be a single digit percentage utilization. So most of the time, not doing very much. Cloud might be estimates of around 10, 10 times more efficient. So maybe 20 to 30 percent efficiency for most very well-run hyperscale data centers. Facebook themselves say that we've, by introducing some of these ideas, we've been able to get up to 66 percent utilization, which basically means there's a bunch of extra hardware that they don't have to buy and build, which is good because they are spending lots and lots of money building with data centers in lots of places and anything that you can use to reduce the number of data centers you need, in my view, is a good thing because that's a lot of buildings that don't get built, for example. But the key things they mention in the paper, and we'll share it in the paper, we'll share the link to the paper, is that if you have maybe a computing job or you've got a function or anything like that, you basically have like, they make this stuff possible by adding kind of deadlines or saying how tolerant of being moved through time or moved through space a particular job might be. And this feels like, this kind of hints that this might, might be a way that might become a norm for working with computing, where if you, if you don't need to have something happen right away in the same place, then you can basically get all these extra benefits by being a bit more flexible about this and saying up front, saying this stuff up front when you submit a job to a computing cluster or something like that.

Iegor Riepen: And it's pretty relevant to ask the question, it's not only how, what are the benefits for the operator of the data center, but what are also the benefits more broadly to the background system in terms of costs and emissions.

Chris Adams: All right. Okay. So we've, I know that you've just, you released a study in the summer and there's some stuff which people can refer to here, but I also am aware that we are in a fast moving field and you just mentioned some work in the University of Wisconsin, I think. Are there any other things you would like to have included into this kind of research, or you think people should be looking at over the next 12 to 18 months inside this, that might influence how people might think about carbon aware computing or set of changes? So, flexible computing like this with a view to reduce the emissions associated with running infrastructure that we all rely on right now.

Iegor Riepen: Maybe one study or research paper which I would love to see is that if somebody would take the courage and to illustrate the system-level benefits of carbon-aware computing across different contexts and different states of the system. So by system-level benefits, I mean from a society perspective, so we look at the costs or total carbon emissions or total curtailment of renewable energy and so on.

And by different contexts and states of the system, I mean the following. Let's think, nowadays, there are mostly companies who buy electricity from the local grid, they have some flexibility, they would go to the data providers, such as electricity maps, providing the short term forecasts, or carbon emission intensity, and they would factor it in, into their load following strategies.

This can work for the temporal shifting, also soon will work, I believe, broadly for the spatial load-shifting. So in this case, space-time shifting can help if you just buy from the grid. So there is a follow-up to this, so some companies might go beyond that and buy additional resources to eliminate all of their carbon footprint completely.

So for that, space-time shifting could also help, and this is basically what our study is about. It would help you to be more resource efficient, it would help to be more cost effective, it would open 24/7 cFE for a broad palette of companies who would not maybe jump there otherwise because of high cost premium.

And in the future we will hopefully be reaching the net zero electricity systems or more broadly net zero energy systems. And space-time shifting can be of help there too. So we would need some set of solutions where we would firm the variable wind and solar. We could think about a palette of solutions on the supply side.

It could be grid connected battery storage. There could be hydrogen storage if in the region where there are salt caverns. Or there could be even energy storage in the liquid hydrocarbons like methanol storage. My colleagues Tom Brown and Johannes Hump recently published a paper on this. But these are all the solutions from the supply side.

There could be solutions on the demand side, where there are large data centers that can move large loads across space and time. They could help the system to firm the variable wind and solar and provide the service for the system and get some sort of remuneration for that. By the way, Victor Zavala's group has also published a research paper where they make a mathematical modeling sketching out what type of remuneration they can get for providing the service for the system.

Chris Adams: Okay, if I could just quickly stop you there for a second because I want to check I understood it correctly. You're essentially saying that rather than it just being about looking at the cost only to say, in this case, it was like one tech firm looking at how much it would cost them, you're essentially saying it's possible to model this to say how much this kind of flexibility can save everyone else. If you actually had these providers, like a data center as a kind of active participant inside the grid, because that might reduce the amount of generation that the grid might need or that society might need. So essentially, it's like flipping it around saying, well, actually, is there some kind of value that can, or are there benefits that could be shared just outside of just the corporate, just outside of that company? Can it benefit other people as well?

Iegor Riepen: Yes, exactly. And more, more than that, so whenever we look at this context, either your company buys electricity from the grid and tries to move load across space and time, either to reduce costs or to reduce emissions, depending on what signals the company takes. Or if the company goes 24/7 and wants to eliminate all of the emissions and have a high impact on the background grid.

Or even if we even reach net zero systems, in all of these contexts, space-time load-shifting might be of help and might bring benefits, both for the companies operating it and also for the background systems. So if there is a study who would take courage to highlight all of this transition phase and illustrate the benefits for systems, this possibly would be a really good read.

Chris Adams: Cool. All right. Well, that sounds like something for people who are curious about playing around with this on GitHub or want to mess around with some of this modeling themselves to see. And I know there are a number of organizations and people like in software development houses who are actually trying to extend various tools like Kubernetes to incorporate some of this stuff so that you can actually see, so you can essentially design from a very, from the get go, just like I mentioned with Facebook.

So like Facebook's XFaaS paper talks about how they encode a degree of tolerance into this. But I believe that Intel is doing something similar to this for their versions of Kubernetes. There's, I'll share links to that for people who are listening. This has been pro, possibly one of the nerdiest episodes we've ever done, but I've enjoyed myself for this, Iegor.

Thank you, Iegor. But before we wrap up, are there any things that if someone. So, if someone did, if someone has followed this and was able to keep up and was really curious and would like to learn more, where would you direct people to look if they wanted to dive into this some more themselves?

Iegor Riepen: Well, if people would like to know more about our research on spacetime shifting or more generally on 24/7, they could possibly visit our GitHub page. So it's github.com/pypsa/247cfe. There in readme we explain what other research we're doing, how to clone our work on how even to reproduce it.

If people are interested in PyPSA ecosystem for open-source energy modeling, they could visit PyPSA.org or more generally if people are interested in the open energy research in general, it is living an open mode initiative do to which collects various research groups and open models all about energy.

And finally, if com, if there is somebody interested in voluntary energy procurement, one could visit 27 Compact, which is gocarbonfree247.com, which is place collecting people and companies working on this.

Chris Adams: Great. And Iegor, if people want to find you or follow some of your work directly, is it TU Berlin the best place or is there an Iegor Repin on LinkedIn or something that you would direct people to for future questions?

Iegor Riepen: I have my LinkedIn, which I could attach and there is TU Berlin email.

Chris Adams: Brilliant. Okay. Well, Iegor, I've really enjoyed this. Thank you so much for diving down into the depths of CarbonAware and time-space shifting computing like we did today. Oh yeah, and happy birthday, by the way. I forgot. Yeah.

Iegor Riepen: Thank you, Chris. Thanks for having me today.

Chris Adams: All right. Take care of yourself and yeah, have a lovely week. Cheers, Iegor. Hey, everyone. Thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware. foundation. That's greensoftware. foundation in any browser. Thanks again, and see you in the next episode!

View Details

TWiGS host Chris Adams is joined by special guests, Anne Faubry and Alexander Dawson of the W3C Community Group. This week, they discuss the Web Sustainability Guidelines as well as the Content Accessibility Guidelines. Web standards as specified by the World Wide Web consortium, play a huge role in shaping expectations about how the web is supposed to work, and for whom. This week’s guests talk about their respective roles in the W3C and in publishing the guidelines, as well as how they came to be part of the group. Listen in to learn more about the differences between standards and guidelines, and what the Web Sustainability Guidelines aim to achieve.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Anne Faubry: LinkedIn * Alexander Dawson: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* Main Site for Guidelines | W3C [21:27] * Supreme Court hands victory to blind man who sued Domino's over site accessibility [27:06] * Greening government: ICT and digital services strategy 2020 to 2025 - GOV.UK [31:56]

Resources:* afnor spec 2201 [10:37] * Référentiel général d'écoconception de services numériques (RGESN) [10:53] * Web Sustainability Guidelines (WSG) 1.0 at a Glance [22:28] * Checkboxes | W3C [23:40] * JSON API | W3C [23:58] * GitHub - w3c/sustyweb: Sustainable Web Design Community Group [24:16] * Web Content Accessibility Guidelines (WCAG) 2.2 [26:31] * GRI - Standards [29:49] * Issues · w3c/sustyweb · GitHub [38:05] * Sustainable Web Design Community Group [38:30] * Sustyweb Community Home Page * public-sustyweb@w3.org Mail Archives [38:51] * The Tarot Cards Of Tech | Artefact [39:37] * Sustainable Web Design Community Group Wiki [42:02] * Frequently Asked Questions - Sustainable Web Design Community Group [42:11] * The intro guide to digital eco-design | Designer Éthiques[42:57]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Anne Faubry: This is what is called externalities. It's a debated word. It's a bit controversial because it's, it comes from an economic background, but it's important to have this in mind when you design a product because sometimes you might have the best intentions, but when it comes to environment, you can sometimes make things worse than what you wanted to do.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host, Chris Adams. Hello, and welcome to another episode of The Week in Green Software, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. When you're building digital services, a lot of the time you're relying on standards up and down the tech stack to ensure that each component works the way it does. And if you work with the web standards, as specified by the World Wide Web Consortium, the W3C, play a huge role in shaping expectations about how the web is supposed to work and for whom. Earlier this year, the W3C Sustainable Web Design Community Group published their first, and now second, draft of the Web Sustainability Guidelines, a wide range of recommendations for making websites and products more sustainable. So this now means there's guidance from the W3C, not just about how JavaScript and HTML should work, but also how they should work sustainably. With us, today, we have two key members of the community group behind its publication. Alex Dawson and Anne Faubry, I hope I pronounced it correctly, to learn how it came about, a little bit more about the guidelines and what they recommend, and what's coming next. So, going in alphabetical order, Alex and Anne, I'll give you folks a chance to introduce yourself. So, Alex, um, the floor is yours first, if you'd be so kind.

Alexander Dawson: Yep, okay. I'm Alexander Dawson, and I'm a freelance web developer from the UK. I also am a part-time sustainability researcher and writer, and lately I have had the pleasure of being the co-chair of the Sustainable Web Design Community Group, and I'm a co-editor and contributor to the Web Sustainability Guidelines, which of course we're all here to talk about today.

Chris Adams: Thank you, Alex. And Anne, the floor is yours.

Anne Faubry: Hello everyone, I'm Anne Faubry, so your pronunciation was great, from France, I'm a UX/UI designer. I work as a freelancer for environmental projects like NGOs or public services, and I try to implement accessibility and eco-design in all I do. And I also work part time for an association called Designer Éthiques, Ethical Designers in English, which tries to research the field of responsible designing and also more specifically eco-design. So we published the guidelines on this topic and, and that's how I ended up joining the W3C group and becoming the community co-chair of the UX part.

Chris Adams: Okay, cool. Thank you, Anne. All right. For folks who are new to this podcast, I mentioned my name, Chris Adams. I am the executive director of the Green Web Foundation, a Dutch nonprofit focused around an entirely fossil free internet. And I am the policy chair for the Green Software Foundation, the large industry body that publishes this podcast. Before we dive in, there's also a quick reminder that everything we talk about to the best of our ability will be linked in the show notes. below in this episode. So if there's a project that's mentioned or a site we discuss that isn't in these show notes, please do write in and tell us so we can update these for other curious souls and to help you in your quest for knowledge around all things sustainable and digital. All right, Alex, Anne, are you folks sitting comfortably?

Anne Faubry: Yes, we are.

Chris Adams: Okay. All right. So the first question is that sustainability on the web. This has been a long time coming, and I know the W3C Sustainable Web Design Group, or Sustyweb, if you look at the URL and it's to its friends, it's been around for a while with varying levels of activity. And I've got to ask, why did you look to the W3C group in the first place? And maybe one of you might help explain what the W3C is in this kind of context, because we've done a bit of an introduction, but it might be useful to give your understanding, and for one of you to show your kind of story about why you got involved.

Alexander Dawson: I guess the best way to start things off is to, well, essentially mention that we are effectively a community group, so we are not governed by the W3C. That's an important point to underline from the start. Community groups are a great incubator for groups that are effectively volunteers to gather together their collective experience and to talk about how they want to improve parts of the web and to look at topics that interest them and to progress those subjects further. And obviously our group, the Sustainable Web Design Community Group, it was started in 2013, and it really started as a link sharing group where anything to do with sustainability, people were passing useful bits and pieces to do with research and interesting URLs and such.

But it was really around the time of the pandemic hit that people started to sit up, take notice and think, "actually, something could really be done in terms of sustainability on the web and real improvements could be made." And we had a real influx of new members. And the community really blossomed in terms of life.

And it was around that time that myself and Tim Frick, who's the other

been an

Chris Adams: institution over this,

Yeah,

Alexander Dawson: we got talking with all the other members in the group and it came to consensus that maybe looking to other W3C bodies like the Web Accessibility Initiative, they've done such great work with things like the Web Content Accessibility Guidelines in terms of improving accessibility on the web, that actually being able to produce some good solid guidelines that are evidence-backed and collaborate in terms of producing evidence and research, and hook into policy and all the best practices that are out there, all within one collective source, that having something out there that people can quickly and easily reference would be a good way for people to make their websites more sustainable.

So over the course of coming up for two years, we worked very hard and, using various different groups, so we had groups for user experience, which of course Anne was involved in and I was involved in web development and we had groups for business and we had groups for metrics and we had another group which was for hosting and infrastructure and people effectively took their choices as to where their expertise lay, and we built up a huge big collection of these Google documents, these drafts, filled with all of these different guidelines and they've effectively been formatted into the guidelines that we now see today, and that's pretty much a good jumping-off point where I can pass over to Anne to give her experience as to how she found it and what her experience has been throughout the creation process.

Chris Adams: Yeah. Go for it, Anne.

Anne Faubry: Thank you. Indeed, I jumped in the project much later than Alexander. So for me, it was a whole new experience. It was my first contribution to the W3C, but it was not my first contribution to this kind of guidelines and standards because I had done this work previously in France on governmental standards and also by writing the Eco-design guidelines for designers. So, my point was to take this experience and help the group move forward by contributing with all the work we had done in France already on this topic so we didn't have to start from a blank slate and that was really exciting because it was also taking things to a next level, to a worldwide level, and, and so it's not only France in its little part of the world working by itself, and it was contributing and also challenging sometimes the guidelines with people from all, all different countries. So it was very exciting. And how it worked was a lot of collaboration with online tools, frequent video conferences, sharing tools, and contributing on the guidelines all together, and commenting on each other's work, and it was a lot of live exchange, and overall very efficient. Also thanks a lot to Tim and Alexander's work, who overviewed all of it.

Chris Adams: Okay. And this is Tim Frick of Designing for Sustainability, uh, that he wrote in 2016. So it's, uh, nice to actually see this kind of path all the way through. And if I may, I just want to touch on a couple of things that you said there that sounded interesting. You said you did some work earlier in France already, and I understand, would that be a I know there's one organization there, and I think you mentioned Eco-design as in Eco-design FR.

Could you maybe touch on some of those two points, please?

Anne Faubry: Uh huh, so there's actually a lot of different guidelines existing in France, and they are now converging. So there are two governmental ones at the moment, one by the AFNOR, which is the French Standardization Organization, and it's now being taken to the European level. And there's another one, which is the RGESN, which is more, like, only guidelines at the moment, not necessarily a standard so far. But it's, I was actually this afternoon working on this project again. They are now consulting a lot of different professionals and experts on this question to take it to the second version and to make it eventually, if also the legal context and political context allows it, to a standard level. At the moment, it's just guidelines, but we can see in the digital sector industry, it's still, it's already much used by many organizations to promote what they're doing in terms of a sustainable responsibility. And then there's different guidelines, most specific for developers or designers who are more focused on the web, easier to implement. So that's what we've done also with the, within the association for designers. Green IT is a great association doing this for developers and other, also other profiles. And so a lot of associations have popped up within the last years to help understand those guidelines, because they're not necessarily easy to handle.

Chris Adams: Or in English, yeah, as well. Okay, so, it's, I didn't know there was such a strong francophone influence, and it's, this is one thing that we found with the Green Web Foundation. We end up working with Gautier, whose name I never pronounce properly, for the Fog of Enactment, specifically because there's so much good work being done in France, that in many ways is quite a bit further ahead than some of the things that might have been outside of, say, the francophone, like, in, in particularly in primarily English-speaking communities, for example. And maybe this actually speaks to one of the things we might talk about later because there is something in the region, I think it's 93 separate recommendations in the guidelines, or is it 93, Alex? It's more than 90 at least, isn't it?

Alexander Dawson: Yeah.

Chris Adams: it's a lot here. And the thing I was going to ask you is, these guidelines cover a wide range of topics, as you mentioned, so like UX, business, web development, just, and they also don't just talk about carbon, because at the Green Software Foundation, there's a focus primarily with the, on software carbon intensity, and that's the actual specs specifically speaks to this. And while there is an interest in addressing some of the other kind of dimensions of environmental impact that you might care about, that's been the focus for the time being. I wanted to ask, Alex, if I could put to this, this to you first and then come to Anne. Could you maybe talk a little bit about the reasoning behind this decision to cover a number of different areas and then some of the trade-offs you'd have to, you had to make while deciding this kind of scope?

Because you can go wide or you can go narrow and they both have pluses and minuses.

Alexander Dawson: When we came to the decision of producing the specification, we really decided to go with an ESG approach. And obviously with ESG, it's not just about the environmental factors, it's also about social and governance and also economical. And... One of the things that we came to realize when also incorporating and looking towards things like the web content accessibility guidelines, especially for myself, I come from a inclusive design background, and it's often in the cases of things like inclusive design and climate change, the people who are most risk of being affected by subject matters such as climate change, those in at-risk scenarios, so older generations, younger generations, people with accessibility issues, people from low-income backgrounds, they're the individuals who are most often affected by climate related issues, such as people in developing nations and people, as I said, who may have accessibility needs often can be the ones who are at the blunt end of the climate related instrument. So it's one of the areas that we wanted to implicitly tackle with the guidelines to be aware of the human factor. So incorporating people and the planet within the scope of the guidelines. So things like accessibility, privacy by design, security measures, and well, um, there has been debate as to whether these things should be covered within the scope. There's a very good argument that obviously taking into account things like accessibility, for example, if a website is accessible, then it's going to actually reduce carbon emissions by default because someone with accessibility needs is going to be able to access that information much easier and they're going to spend less time on their screens or scrolling through information or having difficulty encountering barriers to access.

And that's going to waste less, not only time actually on the screen, but their device actually having to work around the barriers trying to get through those particular issues so there's a multitude of complexities and variables involved but implicitly working around all these issues such as security issues and privacy issues and accessibility issues, actually, as a secondary factor, can help reduce the carbon factor.

So it's something that we wanted to include within the scope. And it's something that we've run through, not only with the benefits, as can be seen throughout the guidelines, but it's something that we've integrated within the, the ESG measurements.

Chris Adams: Okay, so you're speaking not just about carbon and there's almost, it sounds like in sustainability lingo people talk about co-benefits, as in something that might help the climate but it also has a, kind of a societal good as well. That's one of the angles that you have there. And, Anne, I want to give a bit of space for you to talk about some of this as well because I I do know that France has had a typical, has a history of speaking about more than just carbon. Possibly because of the fact that the energy is already very clean, but it also means that there's other things we need to take into account like water and the material depletion and I forget that, I can never remember the other one that we actually refer to for this, but I know this is some stuff that you might be talking about.

Maybe you could talk a little bit about the range of different communities that you're coming from because you're a UX and UI designer and that's not the same as development and these cover quite a broad range of functions I suppose is the way you might talk about them.

Anne Faubry: That's a very good point. As a designer, you have to think, all the jobs to think about maybe even more as a designer, think about the externalities of what you're designing. And of course, I'm not going to come back on what Alexander said. It was, uh,

Chris Adams: a second, sorry Sam, and externality in this case, that's like shifting the cost outside onto outside of the organisational brandery? Maybe you could just touch on that because I think it's a word that people might not be so familiar with.

Anne Faubry: So, when you design a product, sometimes you're going to have some rebound effects or other effects which can be good or bad, but which were not anticipated. And this is what is called externalities. It's a debated word, it's a bit controversial because it's, it comes from an economic background. But it's important to have this in mind when you design a product because sometimes you might have the best intentions, but when it comes to environment, you can sometimes make things worse than what you wanted to do and what was the previous case. And that's what happens sometimes, if you only look at carbon, you might have some pollution transfers, especially indeed if you have a clean energy. I don't want to get into the nuclear debate, it's not that simple, but indeed regarding the carbon, it's pretty clean. And what we can totally see in the digital industry is people tend to replace devices for new ones because they're more energy efficient. And they tend also as designers or developers or architects to make their choices regarding a lot of the energy consumed. And uh, if you look at the other planetary boundaries, there's nine of them, carbon is only one of them. But there's also the water use and the pollution of the water, the soil, uh, the air. So if you only look at, uh, energy consumption and carbon related to it, you might forget the mineral extraction and all the biodiversity, uh, destroyed with that. And, and this relates also to the human aspects Alex was mentioning. So it's very important not only to look at carbon, but also to look at different environmental indicators, like water or resources consumption, to make sure you don't have these pollution transfers or bad externalities, eventually even the best, which might be IT for good and everything, but if it's not useful, or if it's actually consuming more resources to run, like with the AI or 5G, then it might be worse than the previous solutions.

Chris Adams: Okay, thank you for explaining that. So it sounds like there's a number of different criteria or dimensions that you're looking at rather than just looking at carbon. And there may be different degrees to which they may be easy to act on or even measure the impact on for some of this stuff. But one thing that I was aware of and one thing that I think was high tied in the second part of this was actually trying to make these standards something a bit more easy, a bit more usable for people. And like we can talk about some of the specific things, the nuances around, say, carbon and water and stuff like that. But, Alex, I thought I might just ask you a little bit about this because this is the first time I've seen some of these standards where they're designed in such a way that they can be consumed by other digital tools so they can, some of this can be surfaced. Maybe you could talk about some of the process for trying to find ways to make this stuff easy for people to see because I know at the Green Web Foundation where we work, us having a really simple check has been a really good way to start a conversation over something that is incredibly nuanced when just talking about energy, for example, just like Anne mentioned. But, yeah, there are some really cool things about these draft guidelines that I haven't seen in a spec before, so maybe I'll just give you the floor and let you nerd out on some of this bit.

Alexander Dawson: Yeah, absolutely. One of the things obviously that we wanted to do after getting the draft specification out was to focus on trying to make this as easy for people to consume as possible because obviously we want people to start looking at the work and trying to start implementing these practices.

Obviously, as it stands, the specification is a really long document. So I think if you include all the stuff that can be expanded on, it's close to 300 pages in length. So quite a lengthy piece of work for people to scroll through. But...

Chris Adams: including the references, right?

Alexander Dawson: we've got supplementary documents which we are consistently working on to help people digest that material and to help other toolmakers and people who want to utilize it to actually take advantage of that work and to more easily consume it. For example, one of the first things that we produced alongside the very first draft was an at-a-glance document. And essentially it works as a functioning summary of the guidelines themselves.

So just giving a brief overview of exactly what is contained within the guidelines. And it's something that the Web Content Accessibility Guidelines also has. And within the second draft, we also released a quick reference guide. And the quick reference essentially boils down all of the guidelines into a easy-to-reference sheet which

Chris Adams: A TL:DR version, right?

Alexander Dawson: Yeah exactly, which people can just scroll through and get the gist of exactly what they need to do in order to complete and work through each of the individual guidelines.

Obviously there's links through to the full in-depth guidelines, if people want to get more detail onto them, but we're obviously trying to help people get through these guidelines as easily as possible. And there's a PDF checklist to go along with that, because obviously we know people like checklists and we know that it's helpful for taking to meetings, being able to highlight and work through it with clients and be able to mark off your progress and such. And we do have a JSON API as well, which is something that got launched with the second draft, which is really useful because it's a JSON file that contains the complete unabridged form of the guidelines in full, which can be queried against via our GitHub repo and people can remix it, utilize it, do what they want with it to be able to use or implement our guidelines, as they wish.

A few people have played about with it, showcasing some of their favorite guidelines within their website. We've got a copy of it, which is going to be used on the Sustainable Web Design website, which we're going to be relaunching soon. So there'll be the ability to filter the guidelines by tags, by specific disciplines, being able to search through individual guidelines, so that will actually make looking through the guidelines much easier, and for helping people to be able to work through the content as well.

Chris Adams: Okay, cool.

Alexander Dawson: And also we've got some additional stuff which is on earmarked in the GitHub repo, which we're going to be working on in the future as well. Things like we're going to be producing an introductory document, which will give a generic sort of overview to web sustainability and why it's important and guiding people into the guidelines and effectively working as a good solid standardized overview, and also a test suite which will provide implementability.

So it will provide some actually measurable impact reporting for how effective individual guidelines are and hopefully some guidance regarding tooling and user agents. Because hopefully we would like to see our work implemented in things like Google Lighthouse in the future as well. So a lot of

Chris Adams: linters things

Alexander Dawson: come.

Chris Adams: Okay, cool. Thank you for that, Alex. All right, we'll link to a few of those things for any people who are interested in this and might want to have a go at building some of that stuff. I'm just going to touch on the next question. So, we've heard the Web Content Accessibility Guidelines mentioned a few times, or, I don't know, WCAG, is that how you pronounce it? I can never remember. Yeah. So, these have been useful for helping people, basically, make space for accessibility, so making sure people allocate time and money to this stuff in a project, and they've been useful, uh, for courts, uh, to actually recognize the rights of people with disabilities to access services, for example.

Like, we've seen cases of government, uh, websites mandating this has to happen, and we've also seen pizza websites being sued for not having accessible websites, like the examples of Domino's and stuff like that. Maybe we could talk, Anne, if I start with you, then maybe we could hand over to Alex. Could you maybe talk a little bit about how much this might have influenced the creation of these guidelines?

Because this is, it's been cited quite a few times now, and this is one thing that I really, that really leapt at me when I was looking over the guidelines.

Anne Faubry: The WCAG is, is indeed a, a reference, um, it's crazy to see how in France it became a compulsory as a law. And currently there's also other companies being sued for not respecting it. So it's really moving forward finally, because for a long time it has been in place, but it was not acted upon. And there was just threats, but nothing was happening.

So nobody really cared, uh, regarding the companies. And, and so you can see how it can shape the online environment and if we can do the same with the sustainability, which is actually a broader, broader side of accessibility because as Alex said, everything is intertwined, if we can do the same, then it can be extremely powerful. It can go up as high as governments, but it can also give very practical guidelines for the designers, the developers, everybody working on digital services. So it was definitely an inspiration. The other thing, which is great with the WCAG is the fact that you can check box and that it's very powerful to see if you're making improvements and how you can compare to each other.

And the comparison is also a very strong drive for many organizations and people. And, and again, to see the W3C publishing these guidelines, it's really accelerated also what happened in France, in the government because they, they saw that they were being caught up worldwide.

Chris Adams: Okay, and I, Alex, I might hand over to you for some of this, because when you work with web accessibility, there's this phrase, POUR, perceivable, operable, understandable and robust. And we've done some work, we being Green Web Foundation, we did some work with Wagtail, a content management system, to work on something we were referring to as GOLD, which was Green, Open, Lean, and Distributed as a way of talking about some of these things you might want to design for in a kind of somewhat memorable fashion. Maybe you could talk a little bit about how, how you might make some of this memorable for people or easy to actually talk about because as Anne just mentioned, when you can make it really explicit when something is or is not, isn't being done, it becomes very easy to actually then specify as a product manager or someone along the way to say, "here's what I'm asking for. Can you please deliver this or deliver that?" And I think that might have influenced some of the reference to, actually we'll talk about a little bit later, about the global reporting, the GRI, because that's something that's referenced. So maybe we talk about POUR and some of those things there, and if there's anything like that you've seen in sustainable, in the world of sustainability, then we could talk a little bit about this other reference because this is something I haven't seen in the, in guidelines before, a reference to other global standards, for example.

Alexander Dawson: Yeah, certainly there are quite a few of guidance out there, as Anne mentioned, things like AFNOR and RGESN, which we've certainly tied ourselves and linked up to whenever possible. And we've hooked ourselves, as we're going to be mentioning later, to GRI. But as far as sustainability goes there aren't a lot of catchy acronyms or things which we can say to people that "you need to do this or do that."

So what we've tried to do is really focus primarily on providing people with things that can be implemented. Much of our work is obviously based on things which people are hopefully already doing, good accessibility practices, good performance practices in terms of web performance, things which are usually, in a good agency setting, things that web developers were already trying to be integrating with their practices, all we're trying to do is showcasing it from a sustainability angle and trying to reinforce it and showcasing how it can actually reduce emissions and where those additional performances can be measured and where the best practices could be additionally tweaked, as it were, so hopefully the work that we're doing can actually be utilized alongside the standards and best practices and actually be used to, um, the benefits with any additional legislation that's coming out, because obviously the EU is seeing legislation as we speak, things like, um, CSRD, which is going,

Chris Adams: what that means, because that's, so the Corporate Sustainability Reporting Directive is what the CSRD stands sorry, we're trying to avoid alphabet soup.

Alexander Dawson: yeah, sorry. Yeah. And obviously with this upcoming legislation, one of the things that they have mentioned is that they are actually going to be aligning this directive with the GRI standard as a measurement of implementation, effectively for people who are listening, if you want to conform with this piece of legislation, what the EU is saying is, "if you are abiding by the GRI standard, that is a great way of showing that you are complying with this legislation when it effectively comes into force."

And because our standard, as we are producing, is aligning

Chris Adams: referring an existing

Alexander Dawson: Yeah, exactly. Because what we have produced is aligning itself with GRI and we've got GRI measurement impacts with every single guideline, the great thing is that if people can make those measurable improvements, they will have effectively our weighted evidence that they can use in their reporting to show that they are complying with this upcoming legislation, which hopefully will be a sign to show that they are conforming with sustainability regulation as it is coming into force, which is another hopeful, beneficial move to show other governments that potentially they should be moving in this direction as well.

Chris Adams: Okay, and, Anne, I might just ask for... GRI, we haven't defined what GRI means, but we've said it lots and lots of times. GRI, it's the Global Reporting Index. Is that the,

is? Yeah, Initiative, Global Reporting Index, which is a, maybe you could just briefly touch on some of that before we move to another questions about, and we need to be quite short about this one on the W3C because there are recommendations, there's standards, and there's different things, and we might be useful to talk about that. But in the meantime, yeah, maybe you could just briefly, for the uninitiated, explain the role of the GRI and what some of this actually is, because it comes up a lot again and again and again, just as Alex says.

Anne Faubry: Well, actually, if you allow me, I'd rather have Alex answer this because don't use the GRI much.

I didn't know actually of the GRI before joining the W3C, so I don't think we use it that much in France.

Chris Adams: Alright, quickly then, we'll stay on the GRI, because there's another, I didn't mean this to be such a kind of TLA, sorry, three letter acronym soup of an episode, but we are going to talk a little bit about, okay, you've got these guidelines, what happens next? So Alex, if I ask you briefly what the GRI is

then we'll just touch on what happens from here to turning this into like standards or what that process looks like.

Alexander Dawson: Yeah, absolutely. The best way that I can describe it for listeners in a really simple, easy way, the really simple crash course is that effectively you have best practices, you have standards, and then you have regulation. Essentially what we are producing with the Web Sustainability Guidelines is what's known as a best practice.

So it's something which helps you conform with any standards or any regulation because it's effectively out there but it's effectively not endorsed by a regulatory body, but it's something which is bound by evidence and we try to link it in with what standards already exist. You also have standards.

Now these are things like the GRI and you also have the International Standards Organization, otherwise known as ISO. And the GRI have produced a standard and GRI, the Global Reporting Initiative, it's been around for about 20 odd years and it's used by businesses and corporations and later bodies everywhere.

And it's free for anybody to use and it essentially lays down a whole set of different guidelines for things like mineral use and for water usage and for all the things that you would measure under ESG. So that's essentially set down in stone because they're a standards body like the World Wide Web Consortium.

And then above that you obviously have regulation because they're regulated by governments, and they are the people who effectively lay down the laws. So, essentially, that's the crash course method. You've got the governments, the standard bodies, and then you've got people like us who are producing materials to try and comply with those different things.

Chris Adams: Okay. All right. Thanks for spelling that out, I suppose. All right. So we spoke a little bit about the fact that, okay, you have these different kind of tracks and there is a way that you might go from here. Maybe we could just briefly touch on the fact that you've, there's now a second draft of these guidelines that are, that are out for people. Um, what's next on the roadmap? Or maybe I should ask, like, is there a roadmap? What happens over the next six to 12 months now that these are out here, for example? Anne, if I put that question to you, maybe you could talk a little bit about that, and then we'll touch on some of the other questions.

Anne Faubry: So people are actually asking lots of questions, uh, suggesting improvements, debating some of the facts, um, and sometimes contributing with new points of view, uh, and submitting issues on GitHub. And Alexander and Tim are doing an amazing job trying to integrate all of this feedback into the second and then now the currently the third draft of these guidelines.

Chris Adams: Okay, so we got that. So basically, if you read through these, and we'll be linking to these, you're able to run through... Basically, the idea is, go to GitHub, ask some of the questions there, possibly make a pull request or something like that, but that's the main way for collecting people's feedback right now.

So that's the case. Yeah?

Alexander Dawson: A pull request, add an issue to the issues system, and obviously it will be reviewed and integrated into the next draft and yeah, everyone's welcome also to join the community group and come to our meetings because we hold them every month and we discuss current progress.

Chris Adams: Okay, so if you can't use GitHub and you're or maybe you don't want to use GitHub, there are other channels you can either use and I think that there's maybe even something as old as old as low tech as a mailing list. So there's like a mailing list and video and there's also calls people can join to go. So there's a more than one channel by which you might share some of your feedback into the formation of some of these guidelines. Okay, alright, that's really helpful for people to understand. We're just coming to the end of the time, so I just wanted to give a bit of time for you two to talk about, now that we've just been speaking all about these guidelines and them being out there, and how they can be consumed and used, and how they are made, are there any other open projects or communities that, that outside of this, you think are really exciting and interesting?

So Anne, what kind of projects are inspiring you right now that might have helped you shape your thinking for this work here, but also that you spend your time thinking about or wanting to contribute to outside of this as well?

Anne Faubry: There's a great tool I keep using, but it's not even new, actually. It was done by Artefact, which is, I think, a company from England. And they created the Tarot Cards of Tech, a list of questions you can use. I use it in my projects, I use it with my students, I use it with my colleagues to ponder your choices, think long term, think strategy, and think externalities you might have, good or bad. I love the questions. There's actually two of my favorites, which are, "what would you do differently if nature was your client?" So you can think really differently about your service, thinking "maybe I could reduce this footprint or add this feature to raise awareness on this issue with the users." And another one I love is "what happens if 100 million people are using your product?" And then you can also think what externalities you might have on jobs, on social habits, on housing, and on many different topics to rethink more systematically and, and to think about more/other sustainable issues besides environmental ones.

Chris Adams: Okay, cool. Thank you for that, Anne. And Alex, I'll give a bit of space for you before we wrap up on this one. So, what projects are catching your eye or that you're really interested in right now that might have helped inform some of the work that you've been doing recently?

Alexander Dawson: I think the main one that really informed me most lately is CO2.js.

Chris Adams: Fershad will be happy, yeah.

Alexander Dawson: Yeah, I'm working on measurement because that really inspired me on when I was doing some of my own research to investigate more on how carbon affects various different aspects of the web ecosystem.

Chris Adams: I assure you that wasn't planned ahead, alright? Um, for reference folks, CO2.js is one of the projects that, uh, the Green Web Foundation works on and maintains that's used in a number of tools, uh, for this. I'm a little bit embarrassed, so I'm gonna move on quite quickly, uh, to the final question. Basically, we, if people have found this interesting or finding out about the fact that there are, there is guidance from the W3C trying to do this kind of work, and they want to find out about what to do and what's happening with this, could you just tell people where they should look or where they go?

If there is a particular website you would, you could possibly pronounce and spell out for people so they, if they're listening, they know what to Google.

Alexander Dawson: Yeah, if they just Google the Sustainable Web Design Community group, they will find our homepage and there's a great link to the wiki there which has all the information about all of our past meetings, frequently asked questions and links to all the social channels and how they can get involved. So that's a great place where people can start getting involved in the project.

Chris Adams: Cool, thank you, Alex. I've just checked while you're describing that. I've also, if you type in the word Sustyweb, it's a pretty good Google hack. So, there is nothing related to Sustyweb so far, other than this stuff. Okay, Anne, I'm going to hand over to you and then we'll get the final word with Alex. If people are curious about some of your work and if you have any kind of professional presence and you're comfortable sharing that, is there a particular place you would send people to or if they've found what you were talking about as interesting, where should they look?

Anne Faubry: Our main English resource, uh, is the guidelines that we produced. It's called Eco-design. I will share the exact link so people will know where to look. And otherwise I'd be happy to talk with anyone on, on LinkedIn. That's the best place to find me.

Chris Adams: Okay, so Anne Faubry on LinkedIn or, or Eco-design. Okay, and, Alex, yourself? If people want to find you online, what's the best way to find you in a professional context?

Alexander Dawson: With me it's relatively easy, they just go to alexanderdawson.com

Chris Adams: All right, that was easy. Okay, this has been fun. I've learned a lot. And this has been a nice conversation. Thank you so much for taking the time to actually run through this with me and tell me all about how this works and hopefully this should be interesting for other people who are curious about how standards are formed and how the W3C might be having some kind of impact in how people think about sustainable web. All right, thank you folks! Hey everyone, thanks for listening! Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser. Thanks again and see you in the next episode.

View Details

TWiGS host Chris Adams is joined by special guest Tony van Swet from Electricity Maps, to talk about the mapping of the carbon intensity of electricity grid. Tony shares some of the work that Electricity Maps has been doing to make it easier to understand how clean or dirty electricity is around the world, as well as how they’re making this data more accessible and usable to consumers. Join in on this candid conversation discussing the uses of such data and how to access it, as well as Tony talking about carbon intensity, open data, and open source.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Tony van Swet: LinkedIn | Website

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

News:* How to trace back the origin of electricity (Smoothie Blog Post) | Electricity Maps [06:16] * The value of space-time load-shifting flexibility for 24/7 carbon-free electricity procurement | Zenodo (TU Berlin’s Study with Google, using PYPSA) [12:11] * Electricity Maps | Client Story: Monta (EV Smart Charging use case) [15:41] * GitHub - electricitymaps/electricitymaps-contrib: A real-time visualisation of the CO2 emissions of electricity consumption [21:01] * Electricity Maps | Reports - Hourly Residual Mix Methodology [27:13]

Resources:* Electricity Maps | Data Portal [18:29] * Electricity Maps Methodology

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

TRANSCRIPT BELOW:

Tony van Swet: Looking at Google's use case at their data centers, they have the huge potential to shift their computation based on time or location, so this enables them to manipulate their energy consumption through using our API to increase their consumption when the sun shines and the wind blows.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host, Chris Adams. Hello, and welcome to another episode of This Week in Green Software, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. When we talk about green software, it's often common to talk about energy efficiency, and one of the reasons we care about it at all, is that right now we burn a lot of fossil fuels to generate electricity used in data centers, networks, and end-user devices. But how much of that comes from fossil fuels? And is that changing? This data exists all around the world, and sometimes the data is open, but it's often very messy. In 2017, the Electricity Map project was launched to make it easier to understand how clean or dirty electricity was all around the world. And as the name suggests, it took the form of a map showing the carbon intensity of electricity in as many places around the world as possible. Over the subsequent years, an open source project has grown with hundreds of developers around the world, contributing open web scrapers for data in their parts of the world to make the data more accessible. And earlier this year, the company behind the project released a new open data portal for historical data about how clean electricity was for anyone to use how they wish. So, what does this have to do with green software? Having access to this kind of data makes it much easier to understand the carbon footprint of your software. And this week, we're joined by Tony van Swet from Electricity Maps to talk about carbon intensity, open data, and open source. Hey there, Tony.

Tony van Swet: Hi, great to be here.

Chris Adams: Okay, Tony, before I get ahead of myself, I think we should give you a bit of space to introduce yourself properly. So can you tell us a little bit about what you do at Electricity Maps? And for folks new to the field, what Electricity Maps does these days, please?

Tony van Swet: Yeah, of course. I'm a senior software engineer in the advocacy team at Electricity Maps, and I'll give you a bit of background on what we do at Electricity Maps. So our mission is to organize the world's electricity data to drive the transition to a truly decarbonized electricity system. And as part of the advocacy team, my focus is enabling climate action with transparent insights.

We do this with the help of the open source community, building products such as our map visualization and the data portal that we're here to talk about today.

Chris Adams: Cool. Thanks for that, Tony. Okay. So if you're new to this podcast, um, my name is Chris Adams, as I mentioned before. Um, I work as the executive director at the Green Web Foundation, a Dutch nonprofit focused on an entirely fossil-free internet. And I also work as the chair of the policy working group inside the Green Software Foundation. And before we dive in, here's just a quick reminder, everything we talk about, we'll link to in the show notes below. So if there's a paper that caught your interest, or there's a story you've heard about, we'll do everything we can to make sure there's a helpful set of links that you can follow up for your own research a little bit later. But back to Tony. Tony, I've got to have to ask you, I know you're working in Denmark, but... I suspect you might not be coming from Denmark in the first place. What does a Kiwi end up doing on the opposite side of the world in Denmark, working for a company like Electricity Maps? I'm sure there's a story behind that.

Tony van Swet: Yeah, absolutely. It's definitely a bit of a career shift for me. So I started out about 10 years ago as a truck driver in New Zealand. I was full of self doubt, a bit depressed, struggling to find my place in the world. And to lift myself up out of this, I made it my mission to create technology to combat climate change, and I identified that software was the most powerful way to effect change at scale.

And this led me to enroll in a computer science degree. From there, I worked at a few cool startups in New Zealand, eventually looking to integrate electricity maps data when I saw their job postings and applied, and within a few months, I had the job and was waving goodbye to my friends and family to fly across the world to Denmark.

It's definitely been full of challenges, but it's been amazing to find a company that really shares my values and aligns so perfectly with my mission.

Chris Adams: Wow. So you, when you say you're a truck driver, you're talking about the massive, like 18 wheelers crossing from city to city, right? Something like that.

Tony van Swet: Yeah, I actually worked with the HIAB trucks, which have a crane on the back. So I was delivering building supplies around Auckland. It definitely gave me a lot of time to think about the world and take in the kind of sights and sounds of the city.

Chris Adams: Wow. Okay. So I think you may be the first former truck driver we've ever had onto this podcast. So yeah. Wow. Thank you for, thank you for coming along. That's also a fun story. I, it's, it's quite nice to hear something like that because, uh, I myself, there's a lot of us who are self taught technologists and to hear a nice story about switching careers you're going, "that's cool, actually." All right, before we digress, let's go back to what we were supposed to be here talking about, which is open data and carbon Intensity. So one thing you mentioned is that we're here to talk about open data and there's some recent work at your end that's made that visible. But before we do that, could we briefly just cover what carbon intensity means at your end, because this is something that isn't obvious to most people.

And I remember there being a kind of nice introduction on your website using metaphors like blenders and so on to explain that there's more to electricity to it being just gray versus green, for example. So maybe you could just. provide a bit of a background or how you explain this to people, then we can dive into some of the details about open data.

Tony van Swet: Yeah, the blender analogy is really great. We even did a smoothie maps version of our app for April fools, renaming all of the power sources to different fruits and vegetables to illustrate that. So yeah, carbon intensity to us seems like it's relatively straightforward, but if you're not familiar with this idea, it's quite hard to understand.

And in this case, we refer to carbon intensity as the CO2 equivalent for a given zone where energy is being consumed. We calculate this by determining the carbon intensity for each generation type and then weigh it according to its proportion of the grid mix. We also then calculate the neighboring zones and account for all the imports and exports of the connected zones to figure out a final number for the carbon intensity where you plug into the wall and consume it.

Chris Adams: So basically, if I understand that correctly, you're, what you're saying is you look at all the various parts of the world, and when you say zone, you're referring to maybe a country or a part of a country, depending on how a grid is designed. And then when you're talking about the kinds of generation, you're talking about, say a coal fired power plant or a gas fired power plant or a solar farm or something like this. So these have different levels of CO2 that get emitted for each unit of electricity and you're mixing those together, something like that. Is that correct?

Tony van Swet: Yeah, definitely. When we take a look at a coal plant, it's going to emit a lot more carbon than the equivalent solar or wind farm.

Chris Adams: Okay, cool. So that talks about the consumption, the how, where the electricity comes from. So maybe we can talk a little bit about, okay, how we experienced that and how, like, when I plug something into the wall, for example, what happens next?

Tony van Swet: Yeah, so when we, um, plug into the wall, the energy we consume is, um, considered a mix of all the generation types of the grid you're connected to, um, and it's almost impossible to determine whether an electron comes from a wind farm or a coal plant, even though this will have a significant change in the carbon intensity of the energy you consume.

So this is where it's really useful to consider the grid as a giant blender, mixing together all those generation types. And then we can evaluate the true carbon intensity of the energy that you consume.

Chris Adams: Okay. If we're going to continue this blender analogy, if you put lots and lots of, say, strawberries in a blender, it's going to look one color. And if you had lots of Kiwi fruit in a blender, it's going to look another color. So that's a little bit like what you expose to people and how that might change over the

day.

Right. Okay, cool. I believe what we'll do is we'll share a link to the blog post, because

I found it one of the clearest ways to actually help people get their head around this kind of concept, because it is a bit of a leap when you're first starting to get into this field. So with that, we've got a kind of grounding there. Maybe it's worth talking about this from the point of view of a software engineer. So. Let's say you do know this and you have access to this information. Why is this helpful if you're a software engineer? Like where does this fit into what you might do, for example, or affect your job?

Tony van Swet: I think it's super useful as a software engineer to, to have this information and I see a few main categories where you can apply this data, particularly around raising awareness of when to consume energy. We want people to use power when the sun shines and the wind blows. So I think that there are ways to present this information so people can make decisions in their everyday lives.

But particularly for me, I find it interesting of automating solutions where we can get carbon-aware products that will shift their consumption or the load of the power consumed based on how sustainable the power is available to them.

Chris Adams: Okay. So in this case, this scenario here, you're basically saying, if you have an abundance of power, which is very green, you might kind of tune or change your usage to use more of that, and when the power is particularly dirty, for example, you would try to use less of it so that you're shifting your power through time or possibly through space so that the average carbon intensity might be lower than it otherwise would be.

That's what I think you're saying, right?

Tony van Swet: Yeah, exactly. So the two main ways to optimize your consumption here is over time or via location. Um, so we know that different grids are much cleaner and, um, some people have the luxury to be able to shift their consumption via location as well.

Chris Adams: Okay, cool. So. We've got the kind of general concept for this. Are there any kind of favorite examples that you might point people to of people using this to actually demonstrate their behavior, either at a personal level or an organizational level? Because yeah, having a concrete example would be really helpful for people who are listening to this for the first time.

Tony van Swet: Yeah, I think, um, my favorite example is, um, looking at Google's use case at their data centers. They have the huge potential to shift their computation based on time or location. So this enables them to manipulate their energy consumption through using our API to increase their consumption when the sun shines and the wind blows.

Chris Adams: Okay, so if I understand it correctly, they're like a client of yours or a customer of yours, they pay for this, and then they use it then to essentially either scale things up or down, depending on the amount of power they might be using, depending on where the data centers are. That's, that's what it sounds like, what you're suggesting there, correct?

Tony van Swet: Yeah, definitely. So there is the location aspect and we see a huge variation of the carbon intensity throughout the day. So they also do time-based or scheduled computation based on the carbon intensity available to them.

Chris Adams: Cool. Okay. I'm glad you mentioned this because this is something we've had people come on the show before to talk about some of this, but since we have spoken about this, there's actually, uh, some interesting data. Uh, there was a study published with TU Berlin where we're, I'm based in Berlin so we've, I found out about this study and, uh, there's. I found this actually quite a nice example of this to talk about, because a lot of the time, when you see companies talking about this, it's quite hard to actually find meaningful numbers to say, does this actually translate to a saving in carbon? Or does it translate to a saving in even money, for example? And this is the first time I've seen with really detailed information, which has been modeled through this. Um, we'll share a link to this paper, but there's a few kind of headlines that I saw from this. And as I understand it, one thing that Google is doing, for example, they've basically set a commitment to say, "we want to have the average carbon intensity of our power to be this much." So we want to have a certain percentage coming from what they call is like carbon-free or fossil-free sources of generation. And, uh, the study that I saw basically showed that by moving the load around, it reduces the amount of renewable energy, renewable kind of generation that needs to be deployed in the first place for this.

So there's an embodied carbon saving in the, in not needing to have a bunch of wind turbines or solar all around the globe. And this study that I see, it was modeling five data centers. So five out of say 14 data centers that are around there. And there were. The savings are pretty good, or actually like measurable.

I think with the combination of moving things through time and moving things through space, so moving a compute load to where it was going to be greener, the figures that I saw, some of the headlines were that they're able to reduce the cost of doing this by something in the region of a third of the amount of investment that would need to be possible. And, uh, they also, this is one of the first examples I've seen, which even explains like what the costs on a yearly basis might be for this. And, uh, I think the. There was a couple of scenarios inside this. So there's maybe with zero load shifting or moving, say, about 40 percent of the compute loads that to to different parts of the data centers, where maybe one part of the world might be particularly windy or sunny. When I look at the figures here, I see something in the region of, if you, the savings that are here and we need to, and I will share a link to this, to the actual study for this, so that people can look into this a bit more detail, but with the five data centers modeled in, I think, Germany, in Denmark, in Portugal, in Ireland, and in Finland they were basically able to model savings of around at least 200 million US dollars each year by, in terms of the amount of power that you would need to be, the amount of like generation you would need to match this, to actually hit those targets. Now this is, I think this is actually useful to understand because this actually speaks to the fact that there's economic drivers as well as actually just environmental drivers for this. And this kind of speaks to the wider kind of trend, but. I think it's useful to, for this to be, people to be aware that there's actually something in the public domain to interrogate and look at some of these numbers and see how some of these are modeled and what some of the assumptions are. So we spoke about that. Are there any other use cases that you might point to that may be a little bit more closer to home, for example, or something that you might, that people might experience on a more kind of daily basis or close to themselves, for example?

Tony van Swet: Yeah, absolutely. Yeah. We have a few customers in the EV smart charging space, and we have also done some research with the Frederiksburg commune here in Denmark about the benefits of smart charging. And we... We were quite impressed to see a 10 to 15 percent reduction in carbon emissions if we have grid-aware smart charging products.

So this is plugging your car in the evening and letting it decide when the best time is to charge the car overnight. And even with a small shift in that load, we see a significant reduction in the carbon emissions of the energy consumed. So we were really positive with the results of that. And particularly find it a very nice use case that you put the decision-making power in the hands of the consumers here.

So people can choose whether they want to use these products or not.

Chris Adams: Okay, cool. All right. If you're in the UK, I believe there's a number of companies that do things like this. Octopus is one of the better known examples of this. And I think under some of the tariffs, there are scenarios where you can actually be paid to charge up a car rather than pay to charge a car or to use a car.

So the cost can go negative. Because there's maybe an abundance of power in the grid or like we have here. So that's actually, okay. That's quite useful. So we've covered a couple of use cases now. Maybe it's worth talking a little bit about, little bit about what kind of software supports the use of this data. So I know that at the Green Software Foundation, there's a carbon aware SDK, which is designed to allow people to embed this in some of their software. And where I work at my nonprofit, the Green Web Foundation, we have a library, a Golang library, which is used in a project called Carmado, which is a kind of federated Kubernetes operator. Could you talk a little bit about some of your experiences of what you've seen people use for some of this stuff? For example, maybe you could talk a little bit about some of the pieces of software that you've seen in the wild using some of these tools or using some of this data, for example.

Tony van Swet: Yeah, definitely. Firstly, yeah, we're hugely appreciative of the Green Software Foundation and their work to make it easier for developers to use data like this. We do our best to enable developers and hobbyists with our free data through our API. Previously, it was known as CO2 Signal and we've now incorporated that into the Electricity Maps API.

And we see lots of amazing tools being built. We see people building dashboards so they can make decisions around which data centers they use. And we do see a big community from Home Assistant also integrating our data. So people can connect their smart homes to become carbon aware and give information on the carbon intensity of their homes.

Chris Adams: All right. So we've got some, some stuff like that. And I think we've done a decent job of now establishing what carbon intensity is and how some people might be using it so far. And, uh, we spoke about this idea. There's a, like a free tier, which basically implies that people pay for a data service. But one of the things that we're here to talk about today is open data and this open data portal.

And as I understand it, this is your baby, so to speak, right? So maybe you could talk a little bit about, okay. What is this that we, that that's actually gone live because I've got a history with open data, but I suspect it'd be useful for people who are coming to this to understand what this data portal is and why it's useful and what it lets people do, for example.

Tony van Swet: Yeah, I was super excited to take the lead on the Data Portal project and really happy to come on the show today to talk about it. Providing free and open data really motivates me. And the Data Portal is a product on our website where anyone can download free carbon intensity data for over 50 countries in hourly, daily, monthly, and yearly for both 2021 and 2022.

Chris Adams: Okay. So let me just check if I understand that. So, uh, if people want to start using or experimenting with this data, there's a free tier which you, which folks like yourselves provide. Uh, there's another provider called Watttime that does a, of a free, a free tier. And there's commercial kind of real time feeds from both yourself.

And, uh, this part here is this high resolution historical data that has typically been quite hard for people to give access to. And this is openly licensed in the sense that people are free to use this how, however they wish, is that the case or is there any, or maybe we could talk a little bit about the licensing part so people understand how they could use some of this.

Tony van Swet: Yes, so we have provided the data free for anyone to use. We particularly look at Carbon Accountants and researchers to use the data. People are welcome to use it under our license, as long as they, if they're building a new product with our data, then they'll be required to open source that new product, but if you're using this data for Carbon Accountant, then you're fine to use it and charge for that accordingly.

Chris Adams: Okay, cool. All right. Uh, what we'll do is we'll share a link to the message, to, to the licensing. So people have an understanding for this. So I think when I looked at it was the open database license. So you're able to use it for free in any, in any form, as long as, uh, you're prepared to share under similar terms yourself.

That's basically the kind of general approach that I understand for that. And you, you spoke a little bit about there's an intended audience of people who might be carbon accountants or researchers or energy geeks. Can you talk a little bit about how this data gets published in the first place, where it comes from? Because as I understand it, the data can be quite messy to actually put into a kind of API for someone to consume.

Tony van Swet: Yeah, yeah. It's, it's a huge challenge to collect all the data. So we have an open source repository full of parsers that collect this data from TSOs and data providers around the world. We have an incredible open source community that helps us to maintain those parsers. We then process this raw data with the kind of smoothie idea that we talked about earlier, run data quality checks on top of the data, and then present it in a way that's easy to navigate and consume.

Chris Adams: Okay. So you've used a bit of jargon that I'll need to unpack on there. So you said that you're getting data from a few places and you mentioned a TSO. I'm assuming a TSO is a transmission service operator, like someone who operates part of the grid and they publish information. So that's where some of the data might be coming from.

Is that correct?

Tony van Swet: Yeah. Yeah. Spot on.

Chris Adams: Okay. And one of the challenges is that not every, so maybe I, as I understand it, when I've looked at this data, the data comes out in like grams per kilowatt-hour, what I would typically be paying for, but different places might have different ways of reporting it or different units. Is that the kind of stuff that you, that ends up having to be munged so that there's a kind of clean interface for people to consume?

Tony van Swet: Yeah. So the data providers, the TSOs tend to give the data in the format of a energy breakdown. So the various production types, whether it's wind, solar, coal, gas, and we then process this data and apply emission factors. So we add a direct and life cycle emission factors to each of the generation types, and then compute that to give a final carbon intensity number for each zone.

Chris Adams: Okay. All right. So if I understand that correctly, you're basically saying we know what this kind of coal power station is likely to be doing for each unit of coal. And because we might have some information about it being an old machine, old one or a younger power station. So you'll have some figures like that, and you essentially run through every single form of generation so that you've got a kind of up-to-date, accurate number for that based on what, what people are doing rather than have to look that up because yeah, it's quite hard to find.

So. You've, you've created this data portal. People are able to download it for a set of countries or different parts of the world, and you said that there's data for 2021 and 2022, and this kind of begs the question, what happens next? Is this, is the idea, is the intention to keep having this available on an, on a, on a annual basis so that next year there'll be data for 2023, for example?

Tony van Swet: Yeah, absolutely. I listened to your podcast a few weeks ago and I heard you mention that we were looking to raise the bar of energy data available out there. And I really like that term. It's exactly what we want to do. We plan to release new data early 2023. We want to enable carbon accountants to do granular carbon accounting based on our data.

And we really hope that providing this data for free gives the industry a push to be more open and transparent around what energy data is available.

Chris Adams: Okay, cool. All right. So for the energy nerds here, I, it might be worth just briefly talking about the fact that this currently provides average carbon intensity data. Is that correct? So that's basically the kind of location-based figure. So there, this isn't trying to take into account water or anything to do with market-based figures at present.

That's something that might be on the horizon in future. Could you maybe talk a little bit about what things are on the wishlist or what people are asking about What would they like to use in future from here? Because you alluded to some things about, uh, the life cycle intensity of, of, of energy, for example, and there's a whole other set of footprint impacts that people often ask about when they talk about carbon intensity, or even just the environmental impact of the use of electricity in any kind of service.

Tony van Swet: Yeah, absolutely. So carbon accountants are most interested in the direct emissions that we provide in this data because they're doing their accounting based on the Scope 2 emissions of a company. Um, we do also provide the life cycle analysis emissions for each zone as well. And this is taking a cradle to grave approach of the emissions.

We use the numbers from the IPCC and the,

Chris Adams: So IPCC in this case is the Intergovernmental Panel on Climate Change.

So that's one thing. And then the UNEC, so I'm guessing it's United Nations.

Tony van Swet: United Nations Economic Commission for Europe.

Chris Adams: Okay, great. Okay. So, so that's basically the kind of bona fide place where you're taking some of these numbers from. And when you talk about the life cycle emissions there, that means that let's say you're talking about solar or wind, for example. That includes the fact that someone has to make the panels in the first place, and there's going to be some pollution that may be caused there, carbon pollution from making the kind of silicon panels or the turbines.

Is that correct? And then the dispose disposal.

Tony van Swet: Yeah, exactly. Yeah. And even in the case of nuclear, the lifecycle analysis takes into account the storage and disposal of nuclear waste over hundreds of years and applies the costs of that to a carbon equivalent.

Chris Adams: Okay, cool. All right. So we've spoken about carbon and we will talk about carbon a bit more, but. It's very, one thing that has come up when people talk about the environmental impact of digital services, there's this term called carbon tunnel vision, where people only look at the one figure, or the one kind of dimension. Is this actually something that, is this on your wishlist, for example, because we know there's a, say, there's a water impact. People talk a lot about machine learning and AI and tools like that, having a water impact, and there's also an impact from the actual generation, for example. Could you maybe talk about a little bit like that?

Is that something that you'd like to be heading towards, or is that on the roadmap, for example, in the, in the long run?

Tony van Swet: I think we'd love to take a step back and, and have a broader look at the impacts. We're relatively limited with our capacity, so, so we do focus on what we know and what we're experts in. But I would love to see us work with partners to be able to provide our data alongside other sources to take a bigger picture approach to this.

Chris Adams: Okay, cool, Tony. So back to carbon then. You spoke a little bit about working with other providers and I realized just as I was doing some research for this recording, this podcast, there was a new paper that came out from Electricity Maps specifically about, this is a, this is a really nerdy, I'm afraid, residual carbon emissions when you look at the environmental impact of electricity and If I understand it, I'm just going to try and run my understanding by you if I can, and then if you can give me an idea about if it's in the right direction, that'd be really helpful.

So, as it stands, electricity maps gives you figures for location-based data. So you look at the carbon intensity of the generation all around the world through, and like dams or wind or solar, uh, you'll look at that part, green energy, they often talk about, say, using green energy in some parts of the world where they've purchased essentially certificates to count electricity as green.

And this is a kind of like a market-based approach that people use. And this is the basis that various companies use to say, "we're using a hundred percent green energy," for example. Now, if I understand it, this paper that goes into this and basically says, if you're going to look at the carbon intensity of electricity, you need to account where these certificates that people use, where they're actually being used in various parts, because that's going to have an impact if, because if someone is claiming green energy in Ireland, for example, and they're claiming that on the basis of certificates that were traded from Norway, that's going to have an impact on how green the power might look in Norway compared to Ireland, for example. This is what I think some of the research is that was in this paper. Is that directionally correct? Is that moving in the general direction of correctness for this stuff?

Tony van Swet: Yeah, absolutely. Yes. I think a lot of companies are buying renewable energy certificates and it has to be a zero-sum game. So the residual mixed paper that our policy team has just released goes into a huge amount of detail into how you calculate the carbon intensity after you have sold those renewable energy certificates for each zone.

Chris Adams: And as I understand it, this is something that's on the roadmap that will be looked at is A, a thing that is unsolved right now, but people are looking to figure out how to incorporate into how they work. I know that in the Green Software Foundation, there's a group called Realtime Cloud, who are working to come up with hourly figures to make it possible to provide this kind of reporting. This seems to be one thing that comes up because when I was looking through this paper just last night, actually, there was a few things which are really eye opening for me. So Ireland and Germany are two large markets in Europe, for example. And as I understand it, something like eight times the certificates were consumed as were issued in Ireland, for example.

So this basically means as I understand it, that eight times as much green energy is being claimed as is generated in Ireland. So therefore you've got a bunch of generation in somewhere else in the world that needs to be accounted for when you look at the carbon intensity of say, a place like Iceland or Norway, for example, but the same things seem to be in Germany as well. Germany has something like seven times the certificates consumed as were issued in Germany. So that suggests to me that seven times as much green energy has been claimed as is being generated. So if Germany had to have an entirely green grid, you would need something like a sevenfold increase in order for them to be saying, "yes, we're running entirely on green energy." That seems, this is pretty eyeopening. I'm really glad this is actually out there because I haven't seen this data provided in this resolution, particularly in hourly level before.

Tony van Swet: Yeah, I think it's really fascinating and definitely highlights why we need the transparency around this market based approach. And it's very early days, so we are hoping to inform the methodology of how we approach this in the future.

Chris Adams: Great. Okay. So what we'll do, we'll share a link to that. The things I've just shared are in the first 10 pages of this paper. It's about 80 to 90 pages long, and it's a really impressive tour de force. So Cyril, I'm really impressed with this work. Really mad props for you to actually get this together. Cyril is the policy lead, Electricity Maps, and he's also on some of these working groups, which is why it really caught my eye. So Tony, we've just spoken a little bit about Open data, different ways of measuring the carbon intensity of electricity here for informing your decisions as a software developer. Is there anything that you would like to draw people's attention to? Any projects or things that you are particularly interested or that you're excited about right now?

Tony van Swet: Yeah, absolutely. Yeah. First off, I'd welcome people to jump on and take a look at the data portal and I would appreciate any feedback around that. And. If anyone would like to contribute to our open-source work, we're also always looking for contributors there. To find out more, jump on our website at electricitymaps.com.

Chris Adams: And if I understand it correctly, you folks are still, it's still mostly Python scrapers and a kind of React app that you had before. Is that still the case for people?

Tony van Swet: Yeah, definitely. Yeah. Python and JavaScript.

Chris Adams: Okay. So common languages that people know their way around. Okay. Brilliant. I think that's pretty much it. I've, I've really enjoyed this, actually. Thank you so much for giving us your time and diving into some of the finer points of carbon intensity of electricity and, uh, some of the nerdery there. And, uh, Tony, thank you so much.

I've really, I've really enjoyed this. Cheers, mate.

Tony van Swet: Yeah. Thank you, Chris. It was really great to be here. I also wanted to say I went digging through our open source repo and found your name on there. So I want to give you a personal thank you for contributing in the past.

Chris Adams: Thank you very much. Um, there, I think there'll be more PRs coming in future when I find the time. Okay. Cheers, Tony.

Tony van Swet: Amazing. Thank you.

Chris Adams: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts.

And please, do leave a rating and review if you like what we're doing, it helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser.

Thanks again, and see you in the next episode!

View Details

This Week in Green Software has Dr. Daniel Schien from the University of Bristol, UK, joining host Chris Adams to talk about old research, recent news, and future prospects all revolving around digital sustainability. This conversation touches on some of the work Daniel has done in the past (and plans to do in the future) as well as their thoughts and reckons on this and how it can be used to steer our efforts towards a sustainable future. Together, they cover topics such as streaming being the new flying, and some ways in which new research has changed their perspectives on some problems in green tech.

Learn more about our people:* Chris Adams: LinkedIn | GitHub | Website * Daniel Schien: LinkedIn

Find out more about the GSF:* The Green Software Foundation Website * Sign up to the Green Software Foundation Newsletter

Resources:* The True Climate Impact of Streaming - About Netflix [04:06] * The carbon impact of streaming: an update on BBC TV's energy footprint [05:07] * Does not compute: Avoiding pitfalls assessing the Internet's energy and carbon impacts - ScienceDirect [21:10] * Evaluating Sustainable Interaction Design of Digital Services | Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems [40:50] * A low carbon kubernetes scheduler — University of Bristol [41:47]

If you enjoyed this episode then please either:* Follow, rate, and review on Apple Podcasts * Follow and rate on Spotify * Watch our videos on The Green Software Foundation YouTube Channel! * Connect with us on Twitter, Github and LinkedIn!

**TRANSCRIPT BELOW:

Daniel Schien:** If we are saying streaming is bad and instead consumers jump into their car and go to the cinema, that would be the worst thing that people could do. And same if we are saying streaming is bad and consumers swap to terrestrial broadcast, makes hardly a difference in the short term to the energy consumption that is associated to the delivery of the service.

Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host, Chris Adams. Welcome to another episode of The Week in Green Software, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. In this episode, we're joined by Dr. Daniel Schien, a member of the Green Software Foundation. Daniel teaches and researches sustainable software at the University of Bristol, England.

Hey, Dan.

Daniel Schien: Hi Chris.

Chris Adams: Dan, if any of our listeners lurk on the Green Software Foundation forums, or the kind of IETF E-Impact mailing list, they might be familiar with you. But for folks who are new, would you mind taking a second to introduce yourself to the pod for our listeners, please?

Daniel Schien: Sure. Thanks for having me. My name is Daniel Schien, and I, as you said, teach and research at the University of Bristol in the United Kingdom. I'm a computer scientist and work here in the Faculty of Engineering, researching questions of sustainability of ICT. And here in Bristol, I'm part of a small but dedicated group of researchers looking at the environmental impact of ICT.

Chris Adams: Okay. And I did a bit of research before this call and I realized the first paper I saw from you was back in 2011, researching the dynamic carbon footprint of digital services back in 2011. So it sounds like you've been doing this a while and you've worked with a number of organizations in the industry as well.

Is that correct?

Daniel Schien: Yes, that's true. Indeed, I joined the University of Bristol at the end of 2010, working on a project for the Guardian newspaper, actually. And at that time, they were interested in understanding the transformation of their business from a paper-based delivery to a digital delivery, reading the news online. And at that point there were no methods, no existing similar analyses of environmental impact from the distribution starting at data centers over networks to user devices. And in this void, we helped to come up with an assessment that can compare the quite well understood print side of delivering news with the digital version.

Chris Adams: Wow. Okay. And you've worked with a few other organizations as well. And I think we're going to touch on that a little bit later on. So wow. Thank you. The little story about the Guardian. I had no idea that the Grawn was doing that stuff so long ago already, actually. Okay. Um, cheers for that, Dan. If you're new to this podcast folks, as mentioned before, my name is Chris Adams.

I work as the chair of the policy working group at the Green Software Foundation. And I'm also the executive director of the Green Web Foundation, a Dutch nonprofit working towards an entirely fossil-free internet by 2030. I'm also going to share that whenever we mention a story or a project or a paper in this podcast, we'll do everything we can to find a link so you can actually research some of this yourselves and learn somewhat more if anything caught your interest.

And if there's something that you heard us talk about that you didn't see in the show notes, please do send us an email or get in touch and we'll do everything we can to capture that information and make sure it's available for everyone else. Okay, Dan, are you sitting comfortably?

Daniel Schien: Yes, I am. Thank you very much.

Chris Adams: All right, I think we should begin then.

So a few years back, one of the tropes that just would not die when people started talking about sustainability in the digital realm was this idea of streaming being the new flying. And, um, I saw your name linked to some work that was published in 2021, uh, working with Netflix that actually, in my view, helped shed some light into this and, uh, hopefully might put away some of the kind of poorly written part articles that you often see in the newspapers.

Could you talk, talk a little bit about some of this work that you did? Cause this was one of the first places I really came across your more mainstream work and it, I found it really interesting, actually.

Daniel Schien: Sure. So I mentioned earlier that my, my work here in Bristol on the sustainability of digital media started working with the Guardian and they wanted to understand the transition from print to digital. A couple of years later in 2015, we then worked with the BBC who also wanted to understand a similar transition. For them, it was the transition from terrestrial broadcast of BBC television to IP-based delivery. There is a broader context within which this transition happens. Terrestrial television, terrestrial broadcast uses up spectrum, and that spectrum is a scarce resource. And so there's a, there's an interest in potentially freeing the spectrum up for other purposes. So that's one of the drivers and the other is of course the affordance that IP-based delivery provides. You're moving from a broadcast mode to a unicast mode and, and enabling a lot of new ways of consuming. First of all, you can, you have video on demand as we know, and the other is more interactive forms of media. However, there was a concern about the environmental implications of it. And this concern was, was born just out of a lack of knowledge. At that time, the colleagues at the BBC, they, of course, had very good understanding of the energy consumption of the servers they were operating themselves, but what they did not have a firm grasp on was the energy consumption in networks that transport the data from data centers to the users and then the energy consumption of the devices in the homes. And this product system is, in its structure, relatively similar to the one that delivers the Guardian News Media. So we could leverage some of the methods that we developed in the work before to, to then come up with an estimate, an assessment model that then helped develop an estimate of the energy consumption for delivering BBC television, uh, over IP, but at the same time we delivered this, uh, we used this model to assess the impact from cable and from satellite as well, including terrestrial. And then we were able to also complement this with scenarios of how this might change in the future as the technology becomes more efficient, as the energy transforms, becomes more green, and as user behaviors change. So, so this was, this was a really, I think, yeah, a very successful collaboration. And there's a couple of things that we can dig into later on that are interesting here when it comes to the interpretation of those assessments. But one of the, one of the great things that came out of this was that at that time, that was one of the first studies that worked with an organization that provided the content and so had primary data of the impact in the infrastructure to some degree. And that was an important advantage compared to other work that is based purely on secondary data, on publicly available data, that it provides maybe a more robust.

Chris Adams: Yeah, you get to speak the people, surely. You're asked, you're asked like, "Hey, have I got this data right? Am I understanding it correctly?" And presumably, assuming they're being transparent and honest with you, you've got much greater access about what assumptions are going into that, rather than what you see elsewhere.