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 Machine Learning (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 ML 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
|
Tutorial Learn how to deploy, debug and explore Kubeflow in this exciting sequence of tutorials |
How-to guides Navigate essential Kubeflow procedures like EKS installation |
|
Explanation Deep-dive into the details of Kubeflow on topics like authorisation |
Reference Find technical information on things like authentication with Dex and supported versions |
Project and community
Charmed Kubeflow is a member of the Ubuntu family. It’s an open-source project that welcomes community contributions, suggestions, fixes and constructive feedback.
- Read our Code of Conduct
- Try out some Charmed Kubeflow projects
- Join the Discourse forum
- Contribute and report bugs
- Contribute to the documentation
- Talk to us on Mattermost Chat
Thinking about using Charmed Kubeflow for your next project? Get in touch!
Navigation
Navigation
| Level | Path | Navlink |
|---|---|---|
| 1 | / | Charmed Kubeflow |
| 1 | tutorial | Tutorials |
| 2 | get-started-with-charmed-kubeflow | Get started |
| 2 | explore-kubeflow | Explore components |
| 2 | debugging-charmed-kubeflow | Explore basic operations |
| 1 | how-to-guides | How-to guides |
| 2 | manage-charmed-kubeflow | Manage Charmed Kubeflow |
| 3 | install | Install |
| 3 | install-in-airgapped-environment | Install in airgapped environment |
| 3 | deploy-kubeflow-with-aws-cloud-formation | Deploy to AWS with CloudFormation |
| 3 | install-on-microk8s-behind-a-web-proxy | Deploy to Microk8s behind a web proxy |
| 3 | install-on-microk8s-on-aws | Deploy to MicroK8s on AWS |
| 3 | install-on-nvidia-dgx | Deploy to NVIDIA DGX |
| 3 | deploy-charmed-kubeflow-to-eks | Deploy to EKS |
| 3 | manage-profiles | Manage profiles |
| 3 | customise | Customize |
| 3 | use-nvidia-gpus | Use NVIDIA GPUs |
| 3 | upgrade | Upgrade |
| 4 | databases-migration-guide | MariaDB - MySQL Databases Migration |
| 4 | upgrade-14-16 | Upgrade from 1.4 to 1.6 |
| 4 | upgrade-16-17 | Upgrade from 1.6 to 1.7 |
| 4 | upgrade-17-171 | Upgrade from 1.7 to 1.7 Patch 1 |
| 4 | upgrade-17-18 | Upgrade from 1.7 to 1.8 |
| 3 | troubleshooting | Troubleshoot |
| 3 | uninstall | Uninstall |
| 3 | create-eks-cluster-for-mlops | Create EKS cluster for MLOps |
| 3 | how-tosetup-ssh-vm-access-with-port-forwarding | SSH VM Access |
| 2 | integrate-with-other-charms | Integrate Charmed Kubeflow with other charms |
| 3 | integrate-with-mlflow | Integrate with MLFlow |
| 3 | allow-access-minio | Allow access to MinIO |
| 3 | integrate-with-cos | Integrate with COS |
| 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 |
| 3 | ml-workflow-kubeflow-with-katib-and-mlflow | ML Workflow: Kubeflow with Katib and MLFlow |
| 3 | dynamically-configure-the-notebook-images-list | Dynamically configure the Notebook images list |
| 3 | add-and-reorder-links-on-the-kubeflow-dashboard | Add and reorder links on the Kubeflow Dashboard |
| 1 | reference | Reference |
| 2 | authentication | Authentication |
| 2 | aws-kubeflow-cloudformation-form | AWS Kubeflow CloudFormation Form |
| 2 | kubeflow-bundle | Kubeflow bundle Components |
| 2 | kubeflow-dashboard | Kubeflow Dashboard |
| 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 |
| 3 | release-notes-1-8 | Charmed Kubeflow 1.8 |
| 1 | explanation | Explanation |
| 2 | authorisation | Authorisation |
| 2 | charmed-vs–upstream-kubeflow | Charmed Vs. Upstream Kubeflow |
| contributing-docs | Contributing to docs |
Redirects
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 |