The official documentation is available here.

To deploy a full-fledged Kubeflow on Google Cloud Kubernetes cluster, follow steps below.

Kubeflow is deployed as follows

• Deploy mangement cluster using the manifests in management.

  • The management cluster runs KCC and optionally ConfigSync
  • The management cluster is used to create all Google Cloud resources for Kubeflow (e.g. the GKE cluster)
  • A single management cluster could be used for multiple projects or multiple KF deployments

• Deploy Kubeflow cluster using the manifests in kubeflow.

  • kubeflow contains kustomization rule for each component.
  • Component manifests is pulled from upstream kubeflow/manifests repository to individual folder's upstream/ directory.
  • Makefile uses kustomize and kubectl to generate and apply resources.

For more information about packages refer to the kpt packages guide

1. Use the management blueprint to spin up a management cluster
2. Use the kubeflow blueprint to create a Kubeflow deployment.

To get a sense of how each Kubeflow components are used together for ML workflow, try a basic example kubeflow-e2e-mnist.ipynb using Notebook in Kubeflow. It will make use of Notebook, Volume, Pipelines, AutoML, KServe components.

• Master Periodic
• Master Presubmit
• Master Postsubmit