Kubeflow is an open-source Kubernetes native workflow engine created for deploying complex machine learning workflows. It was developed from the Argo Workflow engine. This tool is one among many in the open-source ecosystem simply the use of machine learning models.  

Kubeflow began life within Google, designed to help run TensorFlow jobs but grew to support multi-cloud and multi-architecture frameworks. Today, companies like IBM, Red Hat, Cisco, and other large tech companies contribute to this project. And it supports a wide array of projects like TensorFlow, PyTorch, Chainer, MXNet, Ambassador, XGBoost, Istio, Nuclio, and more. 

Project Background

  • Tool: Kubeflow
  • Author: Google
  • Initial Release: March 2018
  • Type: Workflow Engine
  • License: Apache-2.0 
  • Supports: Various frameworks and libraries
  • Github: kubeflow
  • Runs On: Anywhere
  • Hardware: Supports CPUs, GPUs, and TPUs
  • Twitter: kubeflow


  • Supports various architectural use cases
  • Scales workloads without much effort
  • Works for training and inference
  • Built on top of Kubernetes
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