This project hosts codes and documents to enable machine learning workloads better running on VMware vSphere and VMware Cloud. For now, this project focuses on Kubeflow. We will further extend the scope to other machine learning software soon.
- Carvel packaging to enable Kubeflow deployment on vSphere with Tanzu and more
- Components for better working with vSphere, for example, GPU enablement, storage support, et al.
- Documents on user guide and best practices
- Better vSphere integration on authentication, resource management, et al.
- Ray on vSphere and integration with Kubeflow
- Support for LLMs
- ...
For detailed instructions on how to deploy, configure and use Kubeflow on vSphere and VMware Cloud, refer to docs here.
Feel free to provide us feedback by filling an issue. Feature requests are always welcome. If you wish to contribute, please take a quick look at the next section.
This project team welcomes contributions from the community. If you wish to contribute code and you have not signed our contributor license agreement (CLA), our bot will update the issue when you open a Pull Request. For any questions about the CLA process, please refer to our FAQ.
- Clone this repository and create a new branch
- Make changes and test
- Submit Pull Request with comprehensive description of changes
The project is licensed under the terms of the Apache 2.0 license.
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