Looking for a fully supported platform for MLOps?
Canonical Charmed Kubeflow is a state of the art, fully supported MLOps platform that helps data scientists collaborate on AI innovation on any cloud from concept to production, offered by Canonical - the open source experts.
Charmed Kubeflow is free to use: the solution can be deployed in any environment without constraints, paywall or restricted features. Data labs and MLOps teams only need to train their data scientists and engineers once to work consistently and efficiently on any cloud – or on-premise.
Charmed Kubeflow offers a centralised, browser-based MLOps platform that runs on any conformant Kubernetes – offering enhanced productivity, improved governance and reducing the risks associated with shadow IT.
Learn more about deploying and using Charmed Kubeflow at https://charmed-kubeflow.io.
Key features
- Centralised, browser-based data science workspaces: familiar experience
- Multi user: one environment for your whole data science team
- NVIDIA GPU support: accelerate deep learning model training
- Apache Spark integration: empower big data driven model training
- Ideation to production: automate model training & deployment
- AutoML: hyperparameter tuning, architecture search
- Composable: edge deployment configurations available
Scale AI experiments to thousands of jobs
Founded on Kubernetes, scaling machine learning with Charmed Kubeflow is painless. Multi-cloud Charmed Kubeflow delivers the elasticity of the public clouds with the governance of on-premise deployment. Train your team once to work anywhere.
Why engineers and data scientists choose Charmed Kubeflow
- Maintenance: Charmed Kubeflow offers up to two years of maintenance on select releases
- Optional 24/7 support available, contact us here for more information
- Optional dedicated fully managed service available, contact us here for more information or learn more about Canonical’s Managed Apps service.
- Portability: Charmed Kubeflow can be deployed on any conformant Kubernetes, on any cloud or on-premise
Get started guide
Charmed Kubeflow delivers a powerful, sophisticated end-to-end MLOps platform which you can deploy in half an hour or less, using MicroK8s or another conformant Kubernetes distribution. Get started with this guide.
Now with AutoML – introducing Katib
Charmed Kubeflow includes Katib to simplify model hyperparameter tuning and neural architecture search experiments. Find the best ML model faster with Charmed Kubeflow and Katib.
Documentation
Please see the official docs site for complete documentation of the Charmed Kubeflow distribution.
All–you–need support services
Enterprise support, deployment and fully managed Charmed Kubeflow are available. Rely on 24/7 full-stack enterprise support with the SLAs you need. Offload deployment and management to Canonical’s engineers.
Contact us to find out more about our support, expert services and managed services offers for Charmed Kubeflow.
An ecosystem for MLOps
Charmed Kubeflow includes support for integration with a growing ecosystem of complementary open source tools including MLFlow, Seldon Core and Apache Spark, enabling you to get even more productive with Kubeflow.
Navigation
Navigation
| Level | Path | Navlink |
|---|---|---|
| 1 | charmed-kubeflow | Introduction |