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# Donating KubeRay to CNCF

**[CNCF](https://daily.dev/sources/cncf)** · 4 min read · 0 upvotes · 0 comments

## Summary

KubeRay is joining the Cloud Native Computing Foundation as a sandbox project, bringing the entire PARK stack (PyTorch, AI models, Ray, and Kubernetes) under Linux Foundation governance. KubeRay is a Kubernetes operator that runs distributed AI and Ray workloads, providing three CRDs: RayCluster for cluster lifecycle management, RayJob for ephemeral batch and training workloads, and RayService for zero-downtime online inference. It integrates with OpenTelemetry, Prometheus, Fluent Bit, and schedulers like Kueue, Volcano, and KAI for GPU/TPU quota management. Spotify uses KubeRay to scale its internal ML platform, Hendrix, on GKE.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.cncf.io/blog/2026/11/09/donating-kuberay-to-cncf>

## Questions this post answers

### What is KubeRay and what Kubernetes custom resources does it provide?

KubeRay is an open source Kubernetes operator for running distributed Ray workloads. It provides three custom resource definitions: RayCluster, which manages the full lifecycle of a Ray cluster including autoscaling and fault tolerance; RayJob, which spins up an ephemeral cluster for batch or training jobs and tears it down after; and RayService, which manages Ray Serve deployments for zero-downtime online inference.

_Teams building ML platforms on Kubernetes can track KubeRay's roadmap and CNCF status on daily.dev._

### Is KubeRay now part of the Cloud Native Computing Foundation?

Yes, KubeRay is joining the CNCF as a sandbox project, bringing the full PARK stack (PyTorch, AI models, Ray, and Kubernetes) under Linux Foundation governance. Previously PyTorch and Ray were governed by the PyTorch Foundation and Kubernetes by CNCF, leaving KubeRay as the missing piece for unified, vendor-neutral governance across the stack.

_Anyone evaluating open source AI infrastructure governance can follow project status changes like this on daily.dev._

### What schedulers does KubeRay integrate with for GPU and TPU resource management?

KubeRay integrates natively with Kueue, Volcano, and KAI to bring Kubernetes-native job queueing to RayJob and RayCluster workloads. This enables gang scheduling for all-or-nothing pod placement, multi-tenant resource quotas, priority preemption, and topology-aware scheduling across scarce GPU and TPU resources.

_Teams choosing a batch scheduler for GPU-heavy Ray workloads can compare options like these on daily.dev._

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- [Tame Ray workloads on OpenShift AI with KubeRay and Kueue](https://daily.dev/posts/tame-ray-workloads-on-openshift-ai-with-kuberay-and-kueue-ebyhfxbjb) · Red Hat Developer · 1 upvotes · 0 comments
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---

Tags: [#kubernetes](https://daily.dev/tags/kubernetes), [#mlops](https://daily.dev/tags/mlops), [#cncf](https://daily.dev/tags/cncf)

[View this post on daily.dev](https://daily.dev/posts/donating-kuberay-to-cncf-gbdcudwyo)

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