This is a deep dive into the most recent MLOps Engineering Labs from the point of view of Team 1.
// Diagram Link: https://github.com/mlops-labs-team1/engineering.labs#workflow
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Connect with Michel on LinkedIn: https://www.linkedin.com/in/michel-vasconcelos-8273008/
Connect with Varuna on LinkedIn: https://www.linkedin.com/in/vpjayasiri/
Timestamps
[00:00] Introduction to Engineering Labs Participants
[00:34] What are the Engineering Labs?
[01:05] Credits to Ivan Nardini who organized this episode!
[04:24] John Savage Profile
[05:13] Did you want to learn MLFlow before this?
[05:50] Alexey Naiden Profile
[07:26] Varuna Jayasiri Profile
[08:28] Michel Vasconcelos Profile
[10:07] Do something with Pytorch and MLFlow and then figure out the rest: What did the process look like for you all? What have you created?
[13:39] What did the implementation look like? How you went about structuring and coding it?
[17:03] Did you encounter problems along the way?
[20:26] Can you give us a rough overview of what you designed and then where was the first problem you saw?
[23:08] Was there a lot to catch up with or did you feel it was fine. Can you explain how it was?
[24:12] Talk to us about this tool that you have that John was calling out. What was it called?
[24:41] Is this homegrown? You built this?
[24:51] Did you guys implement this when you went to the engineering labs? [26:03] Can you take us through the pipeline and then the serving and what the overall view of the diagram is?
[37:26] For a pet project it works well, but when you wanna start adding a little bit more on top of it wasn't doing the trick?
[38:13] So you see it coming in it's much less of an integral part, another lego building block that is part of the whole thing?
[40:54] Did you all have trouble with Pytorch or MLFlow?
[42:44] Along with that, what was the prompt you were encountering when you were trying to use Torchserve?
[44:27] What are you thinking would have been better in that case?
[49:05] Feedback on how Engineering Labs went
[50:20] Michel: "Engineering Labs should go on. I would like to be a part of it in the next lab."
[51:52] Varuna: "This gives me a tangible thing to look at at any point in time and learn from it."
[53:00] John: "I feel I have an anchor into the world of MLOps from having done this lab."
[55:52] Alexey: "We're at a checkpoint where there are ways we could take"
[56:01] Terraform piece Michel wrote for reproducibility.