tkatila / kubeflow

Machine Learning Toolkit for Kubernetes

The Kubeflow makes AI/ML on Kubernetes simple, portable and scalable.

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Documentation

Please refer to the official docs at kubeflow.org.

Kubeflow Components

The Kubeflow ecosystem is composed of multiple open-source projects for each stage in the ML lifecycle.

Learn more about each project in the Kubeflow documentation.

Please use the following GitHub repositories to open issues and pull requests for the different Kubeflow components:

Component	Source Code
KServe	kserve/kserve
Kubeflow Katib	kubeflow/katib
Kubeflow Model Registry	kubeflow/model-registry
Kubeflow MPI Operator	kubeflow/mpi-operator
Kubeflow Notebooks	kubeflow/notebooks
Kubeflow Pipelines	kubeflow/pipelines
Kubeflow Spark Operator	kubeflow/spark-operator
Kubeflow Training Operator	kubeflow/training-operator

If you want to open issue or pull request for the Kubeflow Platform components:

• Use the kubeflow/manifests GitHub repository for the Kubeflow Manifests.
• Use the kubeflow/dashboard GitHub repository for the Kubeflow Profile Controller, Central Dashboard, CRUD Web Apps, PVC Viewer, PodDefault, and Access Management components.

If you have questions about Kubeflow community or Kubeflow ecosystem, please use the kubeflow/community GitHub repository.

Kubeflow Community

Every Kubeflow component is maintained by Kubeflow working group (WG) leads.

Learn more about Kubeflow community and WG in this guide.