Installation Options for Kubeflow Pipelines

Overview of the ways to deploy Kubeflow Pipelines

Kubeflow Pipelines offers a few installation options. This page describes the options and the features available with each option:

Kubeflow Pipelines Standalone

Use this option to deploy Kubeflow Pipelines to an on-premises or cloud Kubernetes cluster, without the other components of Kubeflow. To deploy Kubeflow Pipelines Standalone, you use kustomize manifests only. This process makes it simpler to customize your deployment and to integrate Kubeflow Pipelines into an existing Kubernetes cluster.

Installation guide
Kubeflow Pipelines Standalone deployment guide
Interfaces
  • Kubeflow Pipelines UI
  • Kubeflow Pipelines SDK
  • Kubeflow Pipelines API
Notes on specific features
After deployment, your Kubernetes cluster contains Kubeflow Pipelines only. It does not include the other Kubeflow components. For example, to use a Jupyter Notebook, you must use a local notebook or a hosted notebook in a cloud service such as the AI Platform Notebooks.

Full Kubeflow deployment

Use this option to deploy Kubeflow Pipelines to your local machine, on-premises, or to a cloud, as part of a full Kubeflow installation.

Installation guide
Kubeflow installation guide
Interfaces :
  • Kubeflow UI
  • Kubeflow Pipelines UI within or outside the Kubeflow UI
  • Kubeflow Pipelines SDK
  • Kubeflow Pipelines API
  • Other Kubeflow APIs
Notes on specific features
After deployment, your Kubernetes cluster includes all the Kubeflow components. For example, you can use the Jupyter notebook services deployed with Kubeflow to create one or more notebook servers in your Kubeflow cluster.

GCP Hosted ML Pipelines

Use this option to deploy Kubeflow Pipelines to Google Kubernetes Engine (GKE) from GCP Marketplace. You can deploy Kubeflow Pipelines to an existing or new GKE cluster and manage your cluster within GCP.

Installation guide
Deploy Kubeflow Pipelines from Google Cloud Marketplace
Interfaces
  • GCP Console for managing the Kubeflow Pipelines cluster and other GCP services.
  • Kubeflow Pipelines UI via the Open Pipelines Dashboard link in the GCP Console
  • Kubeflow Pipelines SDK in Cloud Notebooks
Notes on specific features
After deployment, your Kubernetes cluster contains Kubeflow Pipelines only. It does not include the other Kubeflow components. For example, to use a Jupyter Notebook, you can use AI Platform Notebooks.