# Kubeflow is Officially CNCF Graduated!

**URL:** <https://community.amperecomputing.com/t/kubeflow-is-officially-cncf-graduated/3478>\
**Category:** General Discussion\
**Tags:** cncf, kubeflow\
**Created:** [September 10, 2026, 7:55pm UTC](https://community.amperecomputing.com/t/kubeflow-is-officially-cncf-graduated/3478 "2026-09-10T19:55:53Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![Aaron](https://yyz1.discourse-cdn.com/flex027/user_avatar/community.amperecomputing.com/aaron/32/37_2.png) [@Aaron](https://community.amperecomputing.com/u/Aaron)\
**Post date:** [September 10, 2026, 7:55pm UTC](https://community.amperecomputing.com/t/kubeflow-is-officially-cncf-graduated/3478/1 "2026-09-10T19:55:53Z")

</div>

The CNCF has [officially announced](https://www.cncf.io/announcements/2026/08/17/cncf-announces-kubeflows-graduation-solidifying-the-standard-for-cloud-native-ai-operations/) the **graduation of Kubeflow** , recognizing it as a mature, production-ready standard for cloud-native AI and machine learning operations on Kubernetes.

This milestone confirms Kubeflow’s technical maturity and its role as an operational backbone for automating the full Data & AI lifecycle—from data processing and interactive notebook development to distributed training, fine-tuning, and production model serving across public, private, and hybrid cloud environments.

**Key Project Highlights:**

- **Enterprise Adoption & Scale:** Kubeflow Python packages have reached nearly **260 million PyPI downloads** , supported by over **33,000 GitHub stars** and **6,600+ contributors** across 1,000+ organizations.
- **Trusted Industry Standard:** Relied on in production by major enterprises including Bloomberg, NVIDIA, Red Hat, AWS, Canonical, Capital One, and DHL.
- **Production Maturity:** Met strict graduation requirements by completing an independent third-party security audit, establishing formal steering committee governance, and maintaining a CII Best Practices Badge.

We have had many people from this community help out getting the Arm64 side of it to parity. We also had the pleasure of doing a live event with Steering Committee Member Chase Christensen and contributor @DoJoJo2000 (Jeffery Tu). Check that out here:

[![](https://canada1.discourse-cdn.com/flex027/uploads/amperedevelopers/original/2X/9/90842dd642b6ecaff08e1876a77ca3d56fc62dcf.jpeg "Dev Impact: Efficient AI: Scaling Kubeflow on Arm64") ](https://www.youtube.com/watch?v=P4MXH4uk_co&t=2s)