Charmed Kubeflow Documentation

Charmed Kubeflow is an open-source, end-to-end, production ready MLOps platform on top of cloud native technologies.

Charmed Kubeflow translates Machine Learning steps into complete workflows, enabling training, tuning, and shipping of ML models. It enables automation of workflows, increases quality of models, and simplifies deployment of ML workloads into production in a reliable way.

Charmed Kubeflow meets the need of building Machine Learning applications in a structured and consistent manner while contributing to higher productivity and better collaboration in Data Science teams.

For Data Scientists and Machine Learning Engineers Charmed Kubeflow provides an advanced toolkit to organise and scale their work.

In this documentation

Get started - a hands-on introduction to Charmed Kubeflow for new users
How-to guides
Step-by-step guides covering key operations and common tasks
Concepts - discussion and clarification of key topics
Technical information - specifications, APIs, architecture

Project and community

Charmed Kubeflow is an official distribution of the Kubeflow project. It’s an open-source project that welcomes community contributions, suggestions, fixes and constructive feedback.

Thinking about using Charmed Kubeflow for your next project? Get in touch!


Level Path Navlink
1 / Charmed Kubeflow
1 tutorial Tutorial
2 get-started-with-charmed-kubeflow Get started with Charmed Kubeflow
1 how-to-guides How-to guides
2 manage-charmed-kubeflow Manage Charmed Kubeflow
3 install Install
3 deploy-kubeflow-with-aws-cloud-formation Install on AWS with CloudFormation
3 install-on-microk8s-behind-a-web-proxy Install on Microk8s behind a web proxy
3 install-on-microk8s-on-aws Install on MicroK8s on AWS
3 install-on-nvidia-dgx Install on NVIDIA DGX
3 manage-profiles Manage profiles
3 customise Customize
3 use-nvidia-gpus Use NVIDIA GPUs
3 upgrade Upgrade
4 upgrade-14-16 Upgrade from 1.4 to 1.6
4 upgrade-16-17 Upgrade from 1.6 to 1.7
3 troubleshooting Troubleshoot
3 uninstall Uninstall
2 integrate-with-other-charms Integrate Charmed Kubeflow with other charms
3 integrate-with-mlflow Integrate with MLFlow
3 integrate-observability-stack Integrate with Canonical Observability Stack (COS)
3 allow-access-minio Allow access to MinIO
2 integrate-with-external-tools Integrate Charmed Kubeflow with external tools
3 mindspore Integrate with Mindspore
3 ldap Set up LDAP Authentication
2 use-kubeflow Use Kubeflow
3 accelerated-ml-experiments-on-microk8s-with-inaccel-fpga-operator-and-kubeflow-katib Accelerated ML experiments on MicroK8s with InAccel FPGA Operator and Kubeflow Katib
3 aks-spot Use AKS spot instances for pipelines
3 build-an-mlops-pipeline-with-mlflow-seldon-core-and-kubeflow Build an MLOps pipeline with MLFlow, Seldon Core and Kubeflow
3 ml-workflow-kubeflow-with-katib-and-mlflow ML Workflow: Kubeflow with Katib and MLFlow
1 reference Reference
2 authentication Authentication
2 aws-kubeflow-cloudformation-form AWS Kubeflow CloudFormation Form
2 kubeflow-bundle ‘kubeflow’ bundle
2 mlops-pipeline MLOps pipeline
3 list-of-mlops-tools List of MLOps tools
2 profile Profile
2 supported-versions Supported versions
2 release-notes Release notes
3 release-notes-1-7 Charmed Kubeflow 1.7
1 explanation Explanation
2 authorisation Authorisation
contributing-docs Contributing to docs


Mapping table
Location Path
/docs/mlops-pipelines-with-mlflow-seldon-core-and-kubeflow /docs/build-an-mlops-pipeline-with-mlflow-seldon-core-and-kubeflow
/docs/quickstart /docs/get-started-with-charmed-kubeflow
/docs/kubeflow-basics /docs/get-started-with-charmed-kubeflow
/docs/aws /docs/install-on-microk8s-on-aws
/docs/authentication-with-oidc-and-keycloak /docs/how-to-guides
/docs/visual-workflow-design-with-charmed-kubeflow-and-elyra /docs/how-to-guides
/docs/run-spark-on-kubernetes /docs/how-to-guides
/docs/using-vscode-on-charmed-kubeflow /docs/how-to-guides
/docs/setting-up-remote-access /docs/how-to-guides
/docs/operators-and-bundles /docs/components
/docs/deploy-kubeflow-on-microk8s-behind-a-web-proxy /docs/prepare-to-install-on-microk8s-behind-a-web-proxy
/docs/nvidia-gpu-integration-outside-microk8s /docs/use-nvidia-gpus
/docs/components /docs/kubeflow-bundle
/docs/dashboard /docs/install
/docs/prepare-to-install-on-microk8s-behind-a-web-proxy /docs/install-on-microk8s-behind-a-web-proxy