Kubernetes-native workflow automation platform for complex, mission-critical data and ML processes at scale. It has been battle-tested at Lyft, Spotify, Freenome, and others and is truly open-source.

Flyte Backend Plugins contributed by the Flyte community.

Control Plane for Flyte. Flyteadmin is a gRPC + REST Service written in golang and uses a RDBMs to store meta information and management information for Flyte Tasks and Workflows.

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

tensorboard for pytorch (and chainer, mxnet, numpy, ...)

Source files for the website

Code of the official webpage of onnx

FlytePropeller is a Kubernetes native operator, that executes Flyte Workflows and Tasks. It has its own kubectl-flyte CLI to interact and is extensible using the flyteplugins/pluginmachinery interface

Specification of the IR for Flyte workflows and tasks. Also Interfaces for all backend services. https://docs.flyte.org/projects/flyteidl/en/stable/

Extensible Python SDK for developing Flyte tasks and workflows. Simple to get started and learn and highly extensible.

Flyte User-Guides and Tutorials - https://flytecookbook.readthedocs.io

Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.

Hydra is a framework for elegantly configuring complex applications

Connect, secure, control, and observe services.

An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

Open source platform for the machine learning lifecycle