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The Kubeflow makes AI/ML on Kubernetes simple, portable and scalable.
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---
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## About Kubeflow
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## Documentation
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[Kubeflow](https://www.kubeflow.org/) makes artificial intelligence and machine learning simple, portable, and scalable.
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Please refer to the official docs at [kubeflow.org](http://kubeflow.org).
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We are an _ecosystem_ of [Kubernetes](https://kubernetes.io/) based components for each stage in the [AI/ML Lifecycle](https://www.kubeflow.org/docs/started/architecture/#kubeflow-components-in-the-ml-lifecycle) with support for best-in-class open source [tools and frameworks](https://www.kubeflow.org/docs/started/architecture/#kubeflow-ecosystem).
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Please refer to the official [documentation](https://www.kubeflow.org/docs/) for more information.
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## Kubeflow Components
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The Kubeflow ecosystem is composed of multiple open-source projects for each stage in
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[the ML lifecycle](https://www.kubeflow.org/docs/started/architecture/#kubeflow-components-in-the-ml-lifecycle).
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The [Kubeflow Ecosystem](https://www.kubeflow.org/docs/started/architecture/#kubeflow-ecosystem) is composed of several projects known as _Kubeflow Components_.
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Learn more about each project in [the Kubeflow documentation](https://www.kubeflow.org/docs/components/).
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The following table lists the components and their respective source code repositories:
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Please use the following GitHub repositories to open issues and pull requests for
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[the different Kubeflow components](https://www.kubeflow.org/docs/started/introduction/#what-are-standalone-kubeflow-components):
|[Kubeflow Model Registry](https://www.kubeflow.org/docs/components/model-registry/)|[`kubeflow/model-registry`](https://github.com/kubeflow/model-registry)|
|[Kubeflow Training Operator](https://www.kubeflow.org/docs/components/training/)|[`kubeflow/training-operator`](https://github.com/kubeflow/training-operator)|
The [Kubeflow Platform](https://www.kubeflow.org/docs/started/introduction/#what-is-kubeflow-platform) refers to the full suite of Kubeflow Components bundled together with additional integration and management tools.
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- Use the [`kubeflow/manifests`](https://github.com/kubeflow/manifests) GitHub repository for
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the Kubeflow Manifests.
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- Use the [`kubeflow/dashboard`](https://github.com/kubeflow/dashboard) GitHub repository for
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the Kubeflow Profile Controller, Central Dashboard, CRUD Web Apps, PVC Viewer, PodDefault, and
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Access Management components.
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The following table lists the platform components and their respective source code repositories:
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If you have questions about Kubeflow community or Kubeflow ecosystem, please use the
Every Kubeflow component is maintained by Kubeflow working group (WG) leads.
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Kubeflow is a community-lead project maintained by the [Kubeflow Working Groups](https://www.kubeflow.org/docs/about/community/#kubeflow-working-groups) under the guidance of the [Kubeflow Steering Committee](https://github.com/kubeflow/community/blob/master/KUBEFLOW-STEERING-COMMITTEE.md).
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Learn more about Kubeflow community and WG [in this guide](https://www.kubeflow.org/docs/about/community/).
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We encourage you to learn about the [Kubeflow Community](https://www.kubeflow.org/docs/about/community/) and how to [contribute](https://www.kubeflow.org/docs/about/contributing/) to the project!
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# Kubeflow Roadmap
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## Kubeflow 1.9 Release, Planned for release: Jul 2024
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## Kubeflow 1.9 Release, Delivered: July 2024
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The Kubeflow Community plans to deliver its v1.9 release in Jul 2024 per this [timeline](https://github.com/kubeflow/community/blob/master/releases/release-1.9/README.md#timeline). The high level deliverables are tracked in the [v1.9 Release](https://github.com/orgs/kubeflow/projects/61) Github project board. The v1.9 release process will be managed by the v1.9 [release team](https://github.com/kubeflow/community/blob/master/releases/release-1.9/release-team.md) using the best practices in the [Release Handbook](https://github.com/kubeflow/community/blob/master/releases/handbook.md).
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