Human-centric ML Infrastructure: A Netflix Original // Savin Goyal // MLOps Meetup #44

MLOps community meetup #44! Last Wednesday, we talked to Savin Goyal, Tech lead for the ML Infra team at Netflix. // Abstract: In this conversation, Savin talked about some of the challenges encountered and choices made by the Netflix ML Infrastructure team while developing tooling for data scientists. // Bio: Savin is an engineer on the ML Infrastructure team at Netflix. He focuses on building generalizable infrastructure to accelerate the impact of data science at Netflix. // Other links to check on Savin: https://www.usenix.org/conference/opml20/presentation/cepoi https://www.youtube.com/watch?v=lakPlz8GJcA&ab_channel=RConsortium https://www.youtube.com/watch?v=-oMZAS9qfrE&ab_channel=AnalyticsIndiaMagazine https://www.youtube.com/watch?v=yyWirT279tY&ab_channel=FunctionalTV https://www.youtube.com/watch?v=QkRJ24Q0E-k&ab_channel=Matroid ----------- Connect With Us ✌️-------------    Join our Slack community:  https://go.mlops.community/slack Follow us on Twitter:  @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Savin on LinkedIn: https://www.linkedin.com/in/savingoyal/ Timestamps: [00:00] Background of Savin Goyal [02:41] Breakdown of Metaflow [05:44] In the stack, where does Metaflow stand? [13:23] Where does Metaflow start in Runway Project? [15:27] What tools or storage does Netflix use for DataOps, ie: the front-end management of data sets and how does that integrate with Metaflow? [18:56] Recommender Systems: Can you explain the other areas that you're using Machine Learning? [22:27] What do you feel is the hardest part of building an operating  Machine Learning workflow? [28:45] 3 Pillars: Reproducibility, Scalability, Usability. [36:05] You give so much power to people. How do you keep them from going overboard? [37:47] Can you explain this Pillar of Usability? [41:09] Road-based access control has been coming up a lot recently. Does Metaflow do something specific for that? [44:49] What are some learnings that come across that you didn't have since you open-sourced when you were working at Netflix? [48:10] What kind of trends you have been seeing? Where do you feel like the market is going? [50:33] Have you seen some companies really interested in Metaflow? How have you been seeing them combine other tools that are out there?