Note: The master branch may be in an unstable or even broken state during development. Please use releases instead of the master branch in order to get a stable set of binaries.

Overview

Federated learning involves multiple parties to collaborately train a machine learning model, therefore it is usually based on a distributed system. KubeteFATE manages federated learning workloads using cloud native technologies such as containers. KubeFATE enables federated learning jobs to run across public, private and hybrid cloud environments.

FATE (Federated AI Technology Enabler) is an open-source project initiated by Webank's AI Department to provide a secure computing framework to support the federated AI ecosystem. It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). It supports federated learning architectures and secure computation of various machine learning algorithms, including logistic regression, tree-based algorithms, deep learning and transfer learning.

KubeFATE supports the deployment of FATE via Docker Compose and Kubernetes. We recommend installing a quick development and playground FATE cluster with Docker Compose, while a production environment with Kubernetes.

Getting Involved

• For any frequently asked questions, you can check in FAQ.
• Please report bugs by submitting issues.
• Submit contributions using pull requests

Project Structure

KubeFATE
|-- docker-deploy   
|-- k8s-deploy   

docker-deploy: The pricipal of docker-deploy is simple and quickly to set the environment up. Docker Compose can deploy FATE components on a single host. By using Docker Compose, FATE can be set up for environments of multiple parties which are collaborating in a federated manner. Please refer to Docker Compose Deployment for more details.

k8s-deploy: The k8s deployment is design for a real production deployed and managed environment. It designed for flexibility to suit different various environments.

Major features of new KubeFATE k8s-deploy

• Provide a single executable binary for initialing and managing FATE cluster
• Full cycle FATE cluster management, includes deploying a new FATE cluster, querying existed FATE cluster, destroying a given FATE cluster and etc.
• Support customized deployment
• Support one KubeFATE to manage multiple FATE deployments
• Provide cluster management service with RESTful APIs

For more details, please refer to Kubernetes Deployment.

Build KubeFATE

To use docker-deploy for docker compose deployment, you need to make sure [Docker Compose] installed

Refer to: Docker Compose Deployment for more details

To build KubeFATE binary, you need a [Go environment]

git clone https://github.com/FederatedAI/KubeFATE.git
cd KubeFATE
make build-linux-binary

To build KubeFATE service image, you need a [Docker environment]

git clone https://github.com/FederatedAI/KubeFATE.git
cd KubeFATE
make build-docker-image

Note on the usage of ".env"

By default, the installation script pulls the images from Docker Hub during the deployment. A user could also modify .env to specify a local registry (such as Harbor) to pull images from.

License

Apache License 2.0