What is Kubeflow?
Kubeflow makes artificial intelligence and machine learning simple, portable, and scalable.
We are an ecosystem of Kubernetes
based components for each stage in
the AI/ML Lifecycle
with support for best-in-class open source tools and frameworks.
Deploy Kubeflow anywhere you run Kubernetes.
Kubeflow Components
Pipelines
Kubeflow Pipelines (KFP) is a platform for building then deploying portable and scalable machine learning workflows using Kubernetes.
Notebooks
Kubeflow Notebooks lets you run web-based development environments on your Kubernetes cluster by running them inside Pods.
Dashboard
Kubeflow Central Dashboard is our hub which connects the authenticated web interfaces of Kubeflow and other ecosystem components.
AutoML
Katib is a Kubernetes-native project for automated machine learning (AutoML) with support for hyperparameter tuning, early stopping and neural architecture search.
Model Training
Kubeflow Training Operator is a unified interface for model training and fine-tuning on Kubernetes. It runs scalable and distributed training jobs for popular frameworks including PyTorch, TensorFlow, MPI, MXNet, PaddlePaddle, and XGBoost.
Model Serving
KServe (previously KFServing) solves production model serving on Kubernetes. It delivers high-abstraction and performant interfaces for frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX.
Join our Community
We are an open and welcoming community of software developers, data scientists, and organizations! Check out the weekly community call, get involved in discussions on the mailing list or chat with others on the Slack Workspace!
