Lightning Talks
On-Demand Ray Clusters in ML Workflows via KubeRay & Sematic
September 18, 3:00 PM - 3:15 PMIt can often be useful to leverage short-lived Ray clusters as a part of a broader ML workflow (ex: to perform distributed training as part of a pipeline with multiple data and modeling steps). Using these single-purpose, ephemeral Ray clusters can unlock opportunities for improved reproducibility, efficiency, and observability. KubeRay provides a natural way to manage these ephemeral Ray clusters on Kubernetes. Sematic (https://sematic.dev) shares learnings from leveraging KubeRay & Ray in this way.
About Josh
Josh Bauer has written code for everything from particle accelerator data analysis for data from the LHC to ML infra for self-driving cars at Cruise. Most recently, he's been a founding engineer at https://sematic.dev trying to bring world-class ML workflow tooling to teams of all shapes and sizes.
Josh Bauer
Founding Engineer, Sematic (sematic.dev)
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