https://github.com/gaocegege/kubeflow-controller
Kubernetes controller for tensorflow CRD
https://github.com/gaocegege/kubeflow-controller
Last synced: 2 months ago
JSON representation
Kubernetes controller for tensorflow CRD
- Host: GitHub
- URL: https://github.com/gaocegege/kubeflow-controller
- Owner: gaocegege
- Created: 2018-01-02T11:03:01.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-01-10T07:06:52.000Z (over 7 years ago)
- Last Synced: 2025-02-08T15:48:16.651Z (4 months ago)
- Language: Go
- Homepage:
- Size: 6.94 MB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
[tensorflow/k8s]: https://github.com/tensorflow/k8s
[caicloud/kubeflow-clientset]: https://github.com/caicloud/kubeflow-clientset
# KubeFlow Controller
Kubeflow controller is the open source re-implementation of part of the internal tool, ml-executor, in CaiCloud. This project is temporary and we hope we could use [tensorflow/k8s][] powered by the Kubeflow community eventually to replace this controller.
## Background
Recently Google open sources a new project [Kubeflow](https://github.com/google/kubeflow), which is dedicated to making using ML stacks on Kubernetes easy, fast and extensible.
We have a similar project in CaiCloud and it serves for several years. In that project we took different approaches but similar design decisions to Kubeflow. Then we re-implement our internal tool and open source it to accelerate the development of the community powered controller [tensorflow/k8s][].
## Overview
We separate Kubeflow into two parts:
- Kubeflow controller, which contains the controller for Kuberflow CRD.
- [Kubeflow clientset][caicloud/kubeflow-clientset], which contains the clientset and CRD specification for Kubeflow.
There are some differences between [tensorflow/k8s][] and this controller:
- caicloud/kubeflow-controller follows the design pattern of controller, which does not keep a state machine in the code and just moves from the current state to the desired state. tensorflow/k8s follows the design pattern of operator.
- caicloud/kubeflow-controller uses pods to run the workers and PS, while tensorflow/k8s uses jobs.
Besides these, there are also some differences between [tensorflow/k8s CRD][tensorflow/k8s] and [caicloud/kubeflow-clientset CRD][caicloud/kubeflow-clientset]:
- We do not support TensorBoard in the CRD, since the TensorBoard and Serving support will be in other CRDs.
These three points are the biggest differences, others could be ignored or unified.
## Get Started
The controller is easy to use, see [docs/get_started.md](docs/get_started.md) for more details.
## CONTRIBUTING
Feel free to hack on the controller! [docs/development.md](docs/development.md) will help you to get involved into the development.
## Acknowledgments
- Thanks [Kubeflow community](https://github.com/google/kubeflow) for the awesome open source project.
- Thanks [tensorflow/k8s][] authors for the operator.