The Kubeflow Authors
Kubeflow is a CNCF-hosted, open-source cloud-native AI platform composed of modular Kubernetes-native projects for data and AI workloads. Its mission is to bridge the Data, AI and Cloud Native ecosystems and provide a standard, portable, scalable and composable path across the AI lifecycle.
At a Glance
- Data scientists
- AI and ML engineers
- Platform and infrastructure engineering teams
- Organizations operating Kubernetes in public, private or hybrid clouds
- +2 more
AI Tools by The Kubeflow Authors
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Kubeflow
Kubernetes Native AI ML Platform
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Latest News
Kubeflow has graduated from CNCF
CNCF announced Kubeflow's graduation as a mature standard for cloud-native AI operations
Introducing Kubeflow MCP, an agent interface for cloud-native AI at scale
KubeCon + CloudNativeCon India 2026: Kubeflow community experience
Products & Services
The integrated Kubeflow distribution for running the project’s ecosystem on Kubernetes; the 1.11 release was dated December 15, 2025.
A platform for building and deploying portable, scalable machine-learning workflows on Kubernetes.
A Kubernetes-native distributed AI training platform for LLM fine-tuning and model training across frameworks including PyTorch, MLX, Hugging Face, DeepSpeed, Megatron, JAX and XGBoost.
Interactive development environments for AI, ML and data workloads on Kubernetes.
Market Position
Kubeflow positions itself as an open, vendor-neutral and Kubernetes-native alternative to proprietary or cloud-specific MLOps/AI platforms. Its differentiation is the breadth of its composable lifecycle stack, portability across environments, integration with the CNCF ecosystem and community governance; adjacent competitors include managed cloud ML platforms and other open-source MLOps systems.
Leadership
Founders
David Aronchick
Google engineer and co-founder of Kubeflow; he described the founding demo and project origin in the CNCF graduation announcement.
Jeremy Lewi
Google senior software developer/engineer and Kubeflow co-founder and lead engineer at the project's launch.
Vishnu Kannan
Google engineer who co-created the original Kubeflow demonstration with David Aronchick and Jeremy Lewi.
Executive Team
Andrey Velichkevich
Kubeflow Steering Committee member
Current KSC member (term beginning February 2026); affiliated with Apple.
Chase Christensen
Kubeflow Steering Committee member
Current KSC member (term beginning February 2026); affiliated with Wiz.
Founding Story
Kubeflow was created at Google in 2017. According to co-founder David Aronchick, he, Jeremy Lewi and Vishnu Kannan assembled an early Kubernetes-and-machine-learning demo involving hot dogs; the project began as a way to make machine learning workflows scalable and portable on Kubernetes.
Business Model
Revenue Model
Kubeflow is open-source software governed as a CNCF project and distributed under open-source licenses. The project itself provides software and community infrastructure rather than a disclosed subscription or usage-based commercial pricing model.
Target Markets
- Data scientists
- AI and ML engineers
- Platform and infrastructure engineering teams
- Organizations operating Kubernetes in public, private or hybrid clouds
- Enterprises with regulated, sovereign or disconnected infrastructure requirements
- Research, HPC and large-scale model-training teams
- End-to-end AI/ML lifecycle management
- Data processing and engineering
- Interactive data science and model development
- Distributed model training and LLM fine-tuning
- Automated machine learning and hyperparameter optimization
- ML pipeline orchestration and reproducible workflows
- Bloomberg
- NVIDIA
- Red Hat