The CNCF has officially announced 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:
