Installing Kubeflow

Deployment options for Kubeflow

Kubeflow is an end-to-end Machine Learning (ML) platform for Kubernetes, it provides components for each stage in the ML lifecycle, from exploration through to training and deployment. Operators can choose what is best for their users, there is no requirement to deploy every component. To read more about the components and architecture of Kubeflow, please see the Kubeflow Architecture page.

There are two pathways to get up and running with Kubeflow, you may either:

  1. Use a packaged distribution
  2. Use the manifests (advanced)

Install a packaged Kubeflow distribution

See the table below for a list of options and links to documentation:

Name Maintainer Platform Version Docs Website
Kubeflow on AWS Amazon Web Services (AWS) Amazon Elastic Kubernetes Service (EKS) 1.3 Docs
Kubeflow on Azure Microsoft Azure Azure Kubernetes Service (AKS) 1.2 Docs
Kubeflow on Google Cloud Google Cloud Google Kubernetes Engine (GKE) 1.5.0 Docs
Kubeflow on IBM Cloud IBM Cloud IBM Cloud Kubernetes Service (IKS) 1.5 Docs External Website
Kubeflow on Nutanix Nutanix Nutanix Karbon 1.4 Docs
Kubeflow on OpenShift Red Hat OpenShift 1.3 Docs External Website
Argoflow Argoflow Community Conformant Kubernetes 1.3 N/A External Website
Arrikto MiniKF Arrikto AWS Marketplace, GCP Marketplace 1.4 Docs External Website
Arrikto Enterprise Kubeflow Arrikto EKS, AKS, GKE 1.4 Docs External Website
Charmed Kubeflow Canonical Conformant Kubernetes 1.4 Docs External Website

Install the Kubeflow Manifests manually

The Manifests Working Group is responsible for aggregating the authoritative manifests of each official Kubeflow component. While these manifests are intended to be the base of packaged distributions, advanced users may choose to install them directly by following these instructions.

Next steps


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