• Serve trained models for inference with TF Serving • Rapid prototyping with self-service Jupyter notebook from JupyterHub Simplified ML Workflow/Pipeline What is DevOps? • “A cross-disciplinary community config • Tensorflow, PyTorch, MXNet, Chainer, and more • JupyterHub to create and manage interactive Jupyter notebooks • Model serving – serve exported models with TF Serving or Seldon • Additional components Demo: Create End to End ML Pipelines with Argo Demo: Rapid prototyping with self-service Jupyter notebook from JupyterHub What’s Next? one) Solution is Kubernetes: • Highly Scalable • Easy to explore