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

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s