CNCF Announces Kubeflow Graduation

The Cloud Native Computing Foundation® (CNCF®), which builds sustainable ecosystems for cloud native software, announced the graduation of Kubeflow, a cloud native ecosystem forged by an open community dedicated to standardizing Data & AI workloads on Kubernetes.

The graduation signals Kubeflow’s technical maturity and confirms its role as an operational backbone for enterprises running AI workloads in production, including data processing, model training, fine-tuning and inference. Kubeflow provides native capabilities for data processing, interactive workloads, model training, fine-tuning, and interactive development. Kubeflow’s upcoming roadmap focuses on expanding Large Language Model (LLM) orchestration, enhancing post-training capabilities with fine-tuning, large-scale data engineering and agentic workloads for Data & AI lifecycle.

As organizations shift from AI experimentation to production, they need consistent infrastructure to advance their AI adoption in a standard way. Kubeflow helps bridge data science, AI engineers and AI platform engineering, enabling teams to scale AI solutions predictably and seamlessly. Kubeflow’s Python packages have reached nearly 260 million PyPI downloads, including major enterprises such as Bloomberg, NVIDIA, Red Hat, LinkedIn, and Spotify, which have used Kubeflow Subprojects to standardize AI workloads.

“Kubeflow has become a fantastic platform for organizations looking to unify work across AI, data science and platform engineering teams,” said Chris Aniszczyk, CTO, CNCF. “Graduation marks a critical milestone, cementing Kubeflow as a mature option for enterprise AI workloads on Kubernetes. The project’s remarkable growth reflects the tireless work of its maintainers and community, and we are thrilled to celebrate this milestone with them.”

Created at Google in 2017, Kubeflow has evolved from a collection of components into a unified, AI-native platform designed around the needs of data processing, model development, training and serving. Since joining CNCF as an incubating project in 2023, it has grown to more than 6,600 contributors across more than 1,000 organizations and has accumulated over 33,000 GitHub stars across its repositories. The project also works with CNCF technologies such as Prometheus for monitoring, KServe, Feast and Kueue for job queuing and Istio for secure service communication. As one of the first AI-native projects to reach graduated status, Kubeflow marks an inflection point for CNCF’s AI portfolio as the cloud native ecosystem has matured past infrastructure alone and now delivers production-grade, vendor-neutral foundations for the full data & AI lifecycle.

“Nine years ago, Jeremy Lewi, Vishnu Kannan and I put together a crazy demo involving hot dogs and Kubernetes, and Kubeflow was born,” said David Aronchick, co-founder, Kubeflow. “I could not be more ecstatic to see how far it’s come — and how many people have turned it into something teams and businesses genuinely rely on. Thank you to the CNCF and everyone in the community who carried it this far. To the next seven years and beyond!”

To reach graduation status, Kubeflow completed a third-party security audit, established a formal steering committee to ensure transparent governance and adopted the CNCF Code of Conduct. The project also maintains a Core Infrastructure Initiative (CII) Best Practices Badge, demonstrating a commitment to secure software development.

The CNCF Technical Oversight Committee (TOC) provides technical leadership to the cloud native community, defining its vision and stewarding projects through maturity levels up to graduation.