Skip to content

Latest commit

 

History

History
38 lines (24 loc) · 2.05 KB

README.md

File metadata and controls

38 lines (24 loc) · 2.05 KB
Raw

Google Cloud distribution of Kubeflow

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

Getting Started

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

Development

Sample material

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.

Test Grid