Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.siderolabs.com/llms.txt

Use this file to discover all available pages before exploring further.

Ray is a project for running machine learning jobs in a cluster of machines. KubeRay is an operator for installing Ray on top of Kubernetes. For up-to-date installation guide check with the upstream Ray documentation.

​
Install Ray operator with Helm

Create a Kubernetes cluster with talosctl or via Omni. Deploy the operator via Helm. 
helm repo add kuberay https://ray-project.github.io/kuberay-helm/
helm repo update

helm install kuberay-operator kuberay/kuberay-operator --version 1.4.2
Once the operator pod is running you can create a Ray cluster. 
helm install raycluster kuberay/ray-cluster --version 1.4.2
Get the status of the cluster: 
kubectl get rayclusters
The output should look like this. 
NAME                 DESIRED WORKERS   AVAILABLE WORKERS   CPUS   MEMORY   GPUS   STATUS   AGE
raycluster-kuberay   1                 1                   2      3G       0      ready    13m
From here you can follow the Ray documentation to run a RayJob.