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Ray functionality is available with Domino-provided images. The Domino Ray Environment is built specifically for workspaces that control a Ray cluster. It includes Ray on top of the typical DSE functionality. You can get the latest released Ray images from compute Environment catalog.

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Create an environment

To set up a Ray cluster, the user needs to first create two environments, one for the Ray cluster (base or worker environment) and one for the workspace/job execution (compute environment). To create a new base Ray cluster environment, follow the general environment creation steps with the following environment_attributes:
  • Base Image Select Custom Image and enter an image URI that points to a deployable Ray image. Domino recommends that you use the latest release tag for your version of Ray from the options published at compute Environment catalog. For example, for Domino 6.0 the following cluster images are available:
    • quay.io/domino/ray-cluster-environment:ray2.36.0-py3.10-domino6.0
    • quay.io/domino/ray-cluster-gpu-environment:ray2.36.0-py3.10-gpu-domino6.0
  • Supported Clusters Select Domino managed Ray (Required). This ensures that the environment will be available for use when creating Ray clusters from workspaces and jobs.
  • Visibility You can set this attribute the same way you would for any other compute environment based on your desired visibility.
  • Dockerfile Instructions Leave blank to use the images as provided by Ray project. You can modify this section to include additional packages that might be necessary for your workloads and must be available on the Ray cluster nodes. See Manage dependencies to learn more.
  • Pluggable Notebooks / Workspace Sessions Leave this section blank because the Ray base environments are not intended to include any workspace configuration.

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Prepare your Ray execution compute environment

In addition to the base Ray cluster environment, you must connect your workspace to your cluster. Domino recommends that you use the Ray base image to create a compatible workspace. See compute Environment catalog. For example, for Domino 6.0, the available compute image is: quay.io/domino/domino-ray-environment:ubuntu22-py3.10-r4.4-ray2.36.0-domino6.0

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Customize this Workspace compute environment

Use the image mentioned previously and add Pluggable Workspace Tools. 
jupyter:
  title: "Jupyter (Python, R, Julia)"
  iconUrl: "/assets/images/workspace-logos/Jupyter.svg"
  start: [ "/opt/domino/workspaces/jupyter/start" ]
  supportedFileExtensions: [ ".ipynb" ]
  httpProxy:
    port: 8888
    rewrite: false
    internalPath: "/{{ownerUsername}}/{{projectName}}/{{sessionPathComponent}}/{{runId}}/{{#if pathToOpen}}tree/{{pathToOpen}}{{/if}}"
    requireSubdomain: false
jupyterlab:
  title: "JupyterLab"
  iconUrl: "/assets/images/workspace-logos/jupyterlab.svg"
  start: [  "/opt/domino/workspaces/jupyterlab/start" ]
  httpProxy:
    internalPath: "/{{ownerUsername}}/{{projectName}}/{{sessionPathComponent}}/{{runId}}/{{#if pathToOpen}}tree/{{pathToOpen}}{{/if}}"
    port: 8888
    rewrite: false
    requireSubdomain: false
vscode:
  title: "vscode"
  iconUrl: "/assets/images/workspace-logos/vscode.svg"
  start: [ "/opt/domino/workspaces/vscode/start" ]
  httpProxy:
    port: 8888
    requireSubdomain: false
rstudio:
  title: "RStudio"
  iconUrl: "/assets/images/workspace-logos/Rstudio.svg"
  start: [ "/opt/domino/workspaces/rstudio/start" ]
  httpProxy:
    port: 8888
    requireSubdomain: false