https://github.com/kubedl-io/kubedl

Run your deep learning workloads on Kubernetes more easily and efficiently.
https://github.com/kubedl-io/kubedl

container deep-learning inference kubernetes machine-learning model scheduling

Last synced: 2 months ago
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Run your deep learning workloads on Kubernetes more easily and efficiently.

• Host: GitHub
• URL: https://github.com/kubedl-io/kubedl
• Owner: kubedl-io
• License: apache-2.0
• Created: 2019-12-10T02:18:51.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2024-03-04T10:50:10.000Z (11 months ago)
• Last Synced: 2024-08-04T04:05:41.618Z (6 months ago)
• Topics: container, deep-learning, inference, kubernetes, machine-learning, model, scheduling
• Language: Go
• Homepage: https://kubedl.io/
• Size: 36 MB
• Stars: 497
• Watchers: 22
• Forks: 78
• Open Issues: 60
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Security: SECURITY.md
  • Governance: GOVERNANCE.md

Awesome Lists containing this project

• awesome-cloud-native - kubedl - Run your deep learning workloads on Kubernetes more easily and efficiently. (AI)

README

        
[![License](https://img.shields.io/badge/license-Apache%202-4EB1BA.svg)](https://www.apache.org/licenses/LICENSE-2.0.html)

[![KubeDL Action Status](https://github.com/kubedl-io/kubedl/workflows/CI/badge.svg)](https://github.com/kubedl-io}/kubedl}/actions)

[![FOSSA Status](https://app.fossa.com/api/projects/git%2Bgithub.com%2Fkubedl-io%2Fkubedl.svg?type=shield)](https://app.fossa.com/projects/git%2Bgithub.com%2Fkubedl-io%2Fkubedl?ref=badge_shield)

[![CII Best Practices](https://bestpractices.coreinfrastructure.org/projects/5072/badge)](https://bestpractices.coreinfrastructure.org/projects/5072)



 

 


KubeDL enables deep learning workloads to run on Kubernetes more easily and efficiently. 

KubeDL is a [CNCF sandbox](https://www.cncf.io/sandbox-projects/) project. 



    

 


## Features

- Support training and inferences workloads (Tensorflow, Pytorch. [Mars](https://github.com/mars-project/mars) etc.)in a single unified controller.  Features include advanced scheduling, acceleration using cache, metadata persistentcy, file sync, enable service discovery for training in host network  etc.

- Automatically tunes the best configurations for ML model deployment. - [Morphling Github](https://github.com/alibaba/morphling)

- Package and deploy ML Model in container and track the model lineage natively with Kubernentes CRD.

Check the website: https://kubedl.io



 

 


## Getting Involved

| Platform                                                                                  | Purpose                                                                             | Estimated Response Time |

|-------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------|-------------------------|

| [DingTalk](https://github.com/kubedl-io/kubedl/blob/master/docs/img/kubedl-dingtalk.png ) | For discussions about development and questions about usage.	                       | < 1 day                 |

| [Github Issues](https://github.com/kubedl-io/kubedl/issues)                               | For reporting bugs and filing feature requests.                                     | < 2 days                |

| E-Mail([email protected])                                             | For discussing specific topics or ask for help from community members/maintainers.  | < 3 days                |

## Publications

Morphling: Fast, Near-Optimal Auto-Configuration for Cloud-Native Model Serving. ACM Socc 2021[link](https://dl.acm.org/doi/10.1145/3472883.3486987)

## License

[![FOSSA Status](https://app.fossa.com/api/projects/git%2Bgithub.com%2Fkubedl-io%2Fkubedl.svg?type=large)](https://app.fossa.com/projects/git%2Bgithub.com%2Fkubedl-io%2Fkubedl?ref=badge_large)