Managed Kubernetes services

Most KubeRay documentation only requires a local Kubernetes cluster such as Kind. Some KubeRay examples require GPU nodes, which can be provided by a managed Kubernetes service. We collect a few helpful links for users who are getting started with a managed Kubernetes service to launch a Kubernetes cluster equipped with GPUs.

Setting up a GKE cluster (Google Cloud)

• Start Google Cloud GKE Cluster with GPUs for KubeRay

Setting up an EKS cluster (AWS)

• Start Amazon EKS Cluster with GPUs for KubeRay

Setting up an AKS (Microsoft Azure)

You can find the landing page for AKS here. If you have an account set up, you can immediately start experimenting with Kubernetes clusters in the provider’s console. Alternatively, check out the documentation and quickstart guides. To successfully deploy Ray on Kubernetes, you will need to configure pools of Kubernetes nodes; find guidance here.