Kubeflow is an open-source platform designed to make deployments of machine learning (ML) workflows on Kubernetes simple, portable, and scalable. It provides a suite of tools and components for end-to-end ML pipeline management, including training, deployment, and monitoring in distributed and cloud environments. Kubeflow is well-suited for data scientists, ML engineers, and organizations building and managing production-grade ML and GenAI solutions at scale.
Visit Kubeflow's official website for product details and getting started.
Comprehensive guides and API references for getting started and using Kubeflow.
Join the Kubeflow community for discussions, support, and collaboration.
Access the source code, report issues, and contribute to Kubeflow on GitHub.