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.