Kubeflow

The Machine Learning Toolkit for Kubernetes

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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

Kubeflow Pipelines Logo
Pipelines

Kubeflow Pipelines (KFP) is a platform for building then deploying portable and scalable machine learning workflows using Kubernetes.

Jupyter + VSCode + RLang Logo
Notebooks

Kubeflow Notebooks lets you run web-based development environments on your Kubernetes cluster by running them inside Pods.

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Dashboard

Kubeflow Central Dashboard is our hub which connects the authenticated web interfaces of Kubeflow and other ecosystem components.


Katib Logo
AutoML

Katib is a Kubernetes-native project for automated machine learning (AutoML) with support for hyperparameter tuning, early stopping and neural architecture search.

TensorFlow + PyTorch Logo
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.

KServe Logo
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!

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We are a Cloud Native Computing Foundation project.