AIM326-R – Implement ML workflows with Kubernetes and Amazon SageMaker – re:Invent 2019 – Key Takeaways

The Key

• How K8s and SageMaker work together, with SageMaker Operator for K8s

The Takeaways

• Lots of things to worry when running ML workloads on K8s, security, scalability, multiple libraries, orchestration, etc.
• The K8s operator maps SageMaker API as K8s resource
• Lyft case study
  • Data and ML becoming one, so need a single tool for both
  • Flyte is such an open source tool created by Lyft
  • Flyte supports SageMaker (though it’s confusing that I saw this recently)
  • Demo
    • NOTE: I found this guy elaborate code details fairly well, you should watch it if you want some deep dive
    • It’s cool to see user submits a task in Flyte, and drill down on each steps, and finally can out-link to SageMaker jobs and view all the way to the deepest detail

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