CNCF Announces Kubeflow’s Graduation, Solidifying a Standard for Cloud Native AI Operations

Milestone marks widespread enterprise adoption for automating end-to-end AI and machine learning lifecycles on Kubernetes

Key Highlights

CNCF has graduated Kubeflow, recognizing the open source project as a mature, production-ready platform for cloud native AI and machine learning operations on Kubernetes.

Kubeflow standardizes the full AI and ML lifecycle—from data processing and interactive development to distributed training, fine-tuning, inference and model serving—across public, private and hybrid cloud environments.

The graduation comes as enterprises increasingly require scalable, portable and vendor-neutral infrastructure to move AI workloads from experimentation to production.

Kubeflow benefits data scientists, AI engineers, ML engineers, platform teams and regulated enterprises by providing a unified Kubernetes-native foundation for building, deploying and operating AI applications at scale.

SAN FRANCISCO — August 17, 2026 — The Cloud Native Computing Foundation® (CNCF®), which builds sustainable ecosystems for cloud native software, today 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.

Supporting quotes:

“Congratulations to the Kubeflow community on this well-deserved graduation! This milestone reflects the community’s relentless focus on making machine learning workflows portable, scalable, and production-ready on Kubernetes. Kubeflow has proven its value across industries, earning the trust of organizations and practitioners worldwide. This is a fantastic achievement and a testament to the hard work, dedication, and maturity of the project and its maintainers, contributors, and adopters. Looking forward to seeing Kubeflow continue to thrive as a CNCF Graduated project!” — Faseela Khan, TOC sponsor, CNCF

“For almost a decade, the Kubeflow community has been driving the adoption of Kubernetes for AI workloads. It has been incredible to watch Kubeflow evolve from a way to run TensorFlow on Kubernetes into a platform that supports the entire data & AI lifecycle. As organizations build AI infrastructure, they consistently need the same core capabilities for building and operating AI applications at scale. The community recognized early that these building blocks should be Kubernetes-native, portable, composable, and easy to use.

CNCF graduation validates that vision and demonstrates the strength and sustainability of the community behind it. What excites me most is that Kubeflow has become a bridge between the cloud native (“Kube”) and machine learning (“Flow”) communities, giving AI practitioners the infrastructure they need to take ideas from experimentation to production and accelerate innovation for everyone!” — Andrey Velichkevich, Kubeflow Steering Committee member

“Having spent almost my entire professional career working alongside the Kubeflow community, this moment feels personal. I have huge admiration for everyone who pushed hard to make it happen. Kubeflow isn’t just a community of some of the best professionals in scalable AI infrastructure, it’s also friends and colleagues I can rely on, people who’ve built an environment I genuinely enjoy coming back to. This is only the beginning. I can’t wait to see where this project goes next, especially in times as wild as these.” — Stefano Fioravanzo, Kubeflow ML Experience Working Group lead and independent AI consultant

“This milestone validates Kubeflow’s unique effort to provide a unified interface for the entire model development life-cycle in an open source, Kubernetes-native, vendor-agnostic way. It took a tremendous amount of effort to cross this threshold. It would not have been possible without the dedication of a genuinely amazing maintainer and contributor community that I consider it a tremendous privilege to be part of. Thank you to everyone who made this milestone possible!” — Alexander Perlman, distinguished engineer, Capital One

“Kubeflow’s graduation reflects years of collaboration across maintainers, contributors, end users, and organizations to build an open, Kubernetes-native platform for the entire Data & AI lifecycle. As organizations move from experimentation to production, they need scalable data processing, reproducible ML workflows, and reliable AI infrastructure working together. As maintainers of the Kubeflow Spark Operator and MCP Spark History Server, we’re proud to contribute to the Kubeflow ecosystem and look forward to helping the community continue advancing open, production-ready infrastructure for Data & AI.” — Vara Bonthu, Principal OSS Specialist SA, AWS & Manabu McCloskey, Senior Open Source Engineer, AWS

“This milestone proves that Kubeflow is not just an open source success but also works as large scale enterprise platform in practice.” — Julius von Kohout, Kubeflow Steering Committee member and principal MLOps architect, DHL Data & AI

“As AI workloads scale in production, having a mature, Kubernetes-native foundation for the full MLOps lifecycle becomes critical. Kubeflow has proven itself as an essential project, giving platform teams the standard abstractions needed to simplify complex AI operations: from interactive development and data processing to distributed training and production serving. CNCF Graduation is a testament to the maintainers’ open governance, technical maturity, and commitment to solving real-world enterprise challenges. We are thrilled to see the entire community reach this milestone and look forward to our continued upstream collaboration.” — Ron Kahn, senior software engineer, NVIDIA

“Kubeflow has become the gold standard for operationalizing AI and ML, and at Canonical, we’re delighted to see it reach this milestone as an independent, open source initiative. We’ve been delivering enterprise support on Kubeflow since the early days of the project, and it’s exciting to see how the platform has evolved and matured. Now users everywhere have access to sophisticated, reliable MLOps capabilities.” — Rob Gibbon, product manager, Canonical

“I come at this from an unusual angle. I run an independent consultancy across Australia and New Zealand, deploying Kubeflow for organizations that have no stake in who wins the MLOps market — they simply need models in production, on infrastructure they control, in environments that are often disconnected from the internet and subject to serious regulatory scrutiny. Kubeflow is the only platform I can put in front of them that is genuinely open, composable, and portable across the environments they actually operate in.

What makes that work is Kubernetes: scalability governed by budget rather than hope, a security model that goes all the way down — encrypted service-to-service traffic, deny-by-default between tenants — and every team free to pin its own runtime without turning one upgrade into everyone’s change window. That maturity is why graduation matters commercially as much as technically: ‘CNCF Graduated’ clears procurement conversations and risk committees in a way that ‘incubating’ never quite did, and that will translate directly into more open source AI infrastructure reaching production.

Contributing to Kubeflow has been one of the more rewarding parts of my career, and I didn’t get here alone — a number of people in this community answered my questions patiently when I was new to it, and I’m grateful to every one of them. To the maintainers and contributors who have carried this for years, frequently outside their day jobs: thank you. And to practitioners across APAC — the community meetings are open, and your production scars are exactly what upstream needs.” — Vikas K. Saxena, founder, RAICS.AI and Kubeflow contributor

“Kubeflow proved that production AI infrastructure can be built on an open, Kubernetes-native foundation. For organizations that require AI sovereignty and cannot leave their future in the hands of a small number of providers, that openness and portability are essential. Kubeflow gives them the freedom to run AI workloads across environments, retain control of critical infrastructure, and avoid dependence on any single platform or vendor.

What makes Kubeflow especially powerful is the community behind it—a global community of practitioners and experts forging production-grade software from the real challenges of building and operating AI at scale. CNCF graduation recognizes not only the maturity of the project but also the strength of a community that has turned years of hard-won operational experience into open, accessible, and reusable infrastructure for the world.

This milestone validates what the Kubeflow community has believed from the beginning: the future of production AI must be open. We look forward to building it with you.” — Francisco Arceo, Kubeflow Steering Committee member and senior principal software engineer, Red Hat

“Early on in my career, Kubeflow provided me the opportunity to work on machine learning use cases that unlocked the true potential of Kubernetes as part of Arrikto and has since continued to provide me an endless space to learn and grow as an engineer.

This community is filled with incredible people from a wide variety of backgrounds who teach each other and push the standards for how models are built, deployed, and operationalized at scale. I’ve witnessed it firsthand, had the opportunity to share what I’ve learned, and continue to be a part of this community even after Arrikto closed its doors, even having the privilege to serve on the Steering Committee at this time (needless to say, a career highlight). I am far from the only one who contributes to Kubeflow beyond their day job, and that is the real power of Kubeflow: it’s an ecosystem of tools, a platform, a community, and a movement.

With our new community distribution and recent CNCF graduation, our goal remains clear: set the gold standard for ML on Kubernetes, get more models into production, and make AI/ML tools accessible to everyone. Consider this your invitation: community meetings are on Tuesdays—see you there!” —Chase Christensen, Kubeflow Steering Committee member and customer engineer, Wiz

Learn more about Kubeflow and join the community: https://www.kubeflow.org/

Additional Resources

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About Cloud Native Computing Foundation

Cloud native computing empowers organizations to build and run scalable applications with an open source software stack in public, private, and hybrid clouds. The Cloud Native Computing Foundation (CNCF) hosts critical components of the global technology infrastructure, including Kubernetes, Prometheus, and Envoy. CNCF brings together the industry’s top developers, end users, and vendors and runs the largest open source developer conferences in the world. Supported by nearly 800 members, including the world’s largest cloud computing and software companies, as well as over 200 innovative startups, CNCF is part of the nonprofit Linux Foundation. For more information, please visit www.cncf.io.

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