Charmed Kubeflow (CKF) is an open-source, end-to-end, production-ready MLOps platform on top of cloud-native technologies.
It translates Machine Learning (ML) steps into complete workflows, including 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.
CKF meets the need of building ML applications in a structured and consistent manner while contributing to higher productivity and better collaboration within teams.
It is intended for data scientists and ML engineers, providing an advanced toolkit to organise and scale their work.
In this documentation
Tutorial Get started - a hands-on introduction to CKF for newcomers |
How-to guides Step-by-step guides covering key operations and common tasks with CKF |
Explanation Discussion and clarification of key topics |
Reference Technical information, including specifications, APIs, settings and configuration |
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.
- Contribute and report bugs.
- Contribute to this documentation.
- Join the Discourse forum.
- Talk to us on Matrix.
- Try out some projects.
Navigation
Navigation
Level | Path | Navlink |
---|---|---|
1 | / | Home |
1 | tutorial | Tutorial |
2 | get-started | Get started |
2 | build-your-first-ml-model | Build your first ML model |
1 | how-to | How to |
2 | install | Install |
3 | general-installation | General installation |
3 | install-in-an-airgapped-environment | Install in an air-gapped environment |
3 | install-on-aks | Install on AKS |
3 | install-on-eks | Install on EKS |
3 | install-on-gke | Install on GKE |
3 | install-behind-a-web-proxy | Install behind a web proxy |
3 | install-on-nvidia-dgx | Install on NVIDIA DGX |
3 | install-using-terraform | Install using Terraform |
2 | manage | Manage |
3 | upgrade | Upgrade |
4 | upgrade-18-19 | Upgrade from 1.8 to 1.9 |
4 | upgrade-17-18 | Upgrade from 1.7 to 1.8 |
3 | uninstall | Uninstall |
3 | troubleshoot | Troubleshoot |
3 | back-up | Back up control plane |
3 | restore | Restore control plane |
3 | integrate-with-cos | Integrate with COS |
3 | integrate-with-minio | Integrate with MinIO |
3 | integrate-with-mlflow | Integrate with MLflow |
3 | manage-profiles | Manage profiles |
3 | configure-high-availability-for-istio-gateway | Configure High Availability for Istio Gateway |
3 | configure-kubeflow-notebook-creation-page | Configure Kubeflow Notebook creation page |
3 | enable-https | Enable HTTPS |
3 | enable-istio-cni-plugin | Enable Istio CNI plugin |
2 | use | Use |
3 | customise-link-configuration-on-the-kubeflow-dashboard | Customise link configuration |
3 | leverage-poddefaults | Leverage PodDefaults |
3 | deploy-nvidia-nims | Deploy NVIDIA NIMs |
3 | launch-nvidia-ngc-notebooks | Launch NVIDIA NGC notebooks |
3 | serve-a-model-using-triton-inference-server | Serve a model using Triton Inference Server |
2 | integrate-with | Integrate with |
3 | integrate-with-azure-blob-storage | Azure Blob Storage |
3 | integrate-with-azure-spot-virtual-machines | Azure spot virtual machines |
3 | integrate-with-identity-providers | Identity providers |
3 | integrate-with-inaccel-fpga-operator | InAccel FPGA Operator |
1 | reference | Reference |
2 | release-notes | Release notes |
3 | release-notes-1-9 | Charmed Kubeflow 1.9 |
3 | release-notes-1-8 | Charmed Kubeflow 1.8 |
2 | supported-versions | Supported versions |
2 | monitoring | Monitoring |
3 | prometheus-metrics | Prometheus metrics |
3 | prometheus-alerts | Prometheus alerts |
3 | grafana-dashboards | Grafana dashboards |
3 | loki-logs | Loki logs |
2 | kubeflow-bundle | Kubeflow bundle |
1 | explanation | Explanation |
2 | security | Security |
3 | authentication | Authentication |
3 | authorisation | Authorisation |
3 | cryptography | Cryptography |
2 | charmed-vs-upstream | Charmed vs. upstream |
2 | mlops-tools | MLOps tools |
contributing-docs | Contributing to docs | |
get-started-with-managed-kubeflow-on-azure | Get started with Managed Kubeflow on Azure |