Kubeflow

November 1, 2025 · View on GitHub

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What is Kubeflow

Kubeflow is the foundation of tools for AI Platforms on Kubernetes.

AI platform teams can build on top of Kubeflow by using each project independently or deploying the entire AI reference platform to meet their specific needs. The Kubeflow AI reference platform is composable, modular, portable, and scalable, backed by an ecosystem of Kubernetes-native projects that cover every stage of the AI lifecycle.

Whether you’re an AI practitioner, a platform administrator, or a team of developers, Kubeflow offers modular, scalable, and extensible tools to support your AI use cases.

Please refer to the official documentation for more information.

What are Kubeflow Projects

Kubeflow is composed of multiple open source projects that address different aspects of the AI lifecycle. These projects are designed to be usable both independently and as part of the Kubeflow AI reference platform. This provides flexibility for users who may not need the full end-to-end AI platform capabilities but want to leverage specific functionalities, such as model training or model serving.

Kubeflow ProjectSource Code
KServekserve/kserve
Kubeflow Katibkubeflow/katib
Kubeflow Model Registrykubeflow/model-registry
Kubeflow Notebookskubeflow/notebooks
Kubeflow Pipelineskubeflow/pipelines
Kubeflow SDKkubeflow/sdk
Kubeflow Spark Operatorkubeflow/spark-operator
Kubeflow Trainerkubeflow/trainer

What is the Kubeflow AI Reference Platform

The Kubeflow AI reference platform refers to the full suite of Kubeflow projects bundled together with additional integration and management tools. Kubeflow AI reference platform deploys the comprehensive toolkit for the entire AI lifecycle. The Kubeflow AI reference platform can be installed via Packaged Distributions or Kubeflow Manifests.

Kubeflow AI Reference Platform ToolSource Code
Central Dashboardkubeflow/dashboard
Profile Controllerkubeflow/dashboard
Kubeflow Manifestskubeflow/manifests

Kubeflow Community

Kubeflow is a community-led project maintained by the Kubeflow Working Groups under the guidance of the Kubeflow Steering Committee.

We encourage you to learn about the Kubeflow Community and how to contribute to the project!