Welcome to Flyte!#
The highly scalable and flexible workflow orchestrator that unifies data, ML and analytics.
Flyte is an open-source, Kubernetes-native workflow orchestrator implemented in Go. It enables highly concurrent, scalable and reproducible workflows for data processing, machine learning and analytics.
Created at Lyft in collaboration with Spotify, Freenome, and many others, Flyte provides first-class support for Python, Java, and Scala. Data Scientists and ML Engineers in the industry use Flyte to create:
Data pipelines for processing petabyte-scale data.
Analytics workflows for business and finance use cases.
Machine learning pipelines for logistics, image processing, and cancer diagnostics.
The following guides will take you through Flyte, whether you want to write workflows, deploy the Flyte platform to your K8s cluster, or extend and contribute its architecture and design. You can also access the docs pages by tag.
Get your first workflow running, learn about the Flyte development lifecycle and core use cases.
A comprehensive view of Flyte’s functionality for data and ML practitioners.
End-to-end examples of Flyte for data/feature engineering, machine learning, bioinformatics, and more.
Leverage a rich ecosystem of third-party tools and libraries to make your Flyte workflows even more effective.
Guides for platform engineers to deploy and maintain a Flyte cluster on your own infrastructure.
Dive deep into all of Flyte’s concepts, from tasks and workflows to the underlying Flyte scheduler.
Below are the API reference to the different components of Flyte:
Have questions or need support? The best way to reach us is through Slack:
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Share any suggestions or feedback you have on how to make Flyte better.
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