Quick reference

• The official ray docker image.

• Maintained by: openEuler CloudNative SIG.

• Where to get help: openEuler CloudNative SIG, openEuler.

ray | openEuler

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI libraries for simplifying ML compute:

Learn more about Ray on Welcome to Ray!.

Supported tags and respective Dockerfile links

The tag of each ray docker image is consist of the version of ray and the version of basic image. The details are as follows

Tags	Currently	Architectures
2.55.1-oe2403sp3	ray 2.55.1 on openEuler 24.03-lts-sp3	amd64, arm64

Usage

• Start a Ray head node

  docker run -d --name ray-head -p 8265:8265 -p 6379:6379 openeuler/ray:{Tag}
  

• Start a Ray worker connecting to the head node

  docker run -d --name ray-worker openeuler/ray:{Tag} ray start --address=<head-node-ip>:6379
  

• Run a Python script on the Ray cluster

  docker exec -it ray-head python -c "import ray; ray.init(address='auto'); print(ray.cluster_resources())"
  

• Access the Ray Dashboard at http://localhost:8265

Question and answering

If you have any questions or want to use some special features, please submit an issue or a pull request on openeuler-docker-images.