and test ML experiments with Helm • Manage training jobs and pipelines with Argo • Serve trained models for inference with TF Serving • Rapid prototyping with self-service Jupyter notebook from JupyterHub • JupyterHub to create and manage interactive Jupyter notebooks • Model serving – serve exported models with TF Serving or Seldon • Additional components for storage, workflow, etc. Artificial Intelligence Classic DevOps solutions: • Containers • CI/CD • Autoscaling • A/B testing and canary release of Models • Comparing Production accuracy vs expected accuracy when possible • Rolling-updates • … Resources

? ? ? Kubernetes Kops Kubernetes Operations Kubernetes Kops Kubernetes Operations “Kops models a cluster then realizes it in a cloud” - Kris Nova Kubernetes Kops Kubernetes Operations Statically dealing with YAML Kops 1.4 And we had a lot of it.. Kops 1.4 $: git checkout tags/v1.4.4 $: cd upup/models/cloudup $: find . | xargs wc -l | grep total total 1076 The next release Kops 1.5 wanted new

like? Replica Config LoadBalancer Rolling Update Quota Docker Image Volume RBAC Kubernetes models applications How about Kubernetes itself? How about the fleet Kubernetes running on? Onboard