ray-project/kuberay
A Kubernetes operator that manages Ray clusters for distributed ML and deep-learning workloads.
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KubeRay provides three custom resource definitions—RayCluster, RayJob, and RayService—to automate the deployment, scaling, and fault-tolerant management of Ray applications on Kubernetes. It handles cluster lifecycle management, autoscaling, and zero-downtime upgrades. The toolkit includes a kubectl plugin for simplified workflows and an APIServer for simplified configuration.
Frequently asked
- What is ray-project/kuberay?
- A Kubernetes operator that manages Ray clusters for distributed ML and deep-learning workloads.
- Is kuberay open source?
- Yes — ray-project/kuberay is open source, released under the Apache-2.0 license.
- What language is kuberay written in?
- ray-project/kuberay is primarily written in Go.
- How popular is kuberay?
- ray-project/kuberay has 2.6k stars on GitHub.
- Where can I find kuberay?
- ray-project/kuberay is on GitHub at https://github.com/ray-project/kuberay.