Build production-grade data and ML workflows, hassle-free
The infinitely scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
Tap into the power of Kubernetes
Flyte is a cloud-native workflow orchestration platform built on top of Kubernetes, providing an abstraction layer for guaranteed scalability and reproducibility of data and machine learning workflows. Its containerized, microservices-based architecture ensures resilience and eliminates single points of failure.
Bridge the gap between scalability and ease of use
Write locally, execute remotely
Don’t let friction between development and production slow down the deployment of new data/ML workflows and cause an increase in production bugs. Flyte enables rapid experimentation with production-grade software. Debug in the cloud by iterating on the workflows locally to achieve tighter feedback loops.
Scale as fast as your imagination
As your data and ML workflows expand and demand more computing power, your workflow orchestration platform must keep up. If it’s not designed to scale, your platform will require constant monitoring and maintenance. Flyte was built with scalability in mind, ready to handle changing workloads and resource needs.
Give the power back to data practitioners and scientists
Data scientists, data and ML practitioners, and analytics pipeline builders need to work independently. They shouldn’t have to rely on ML and platform engineers to turn models or training pipelines into production-ready pipelines. Flyte enables user teams to build workflows using the Python SDK, while they can still easily deploy their workflows to the Flyte backend.
“With Flyte, we want to give the power back to biologists. We want to stand up something that they can play around with different parameters for their models because not every … parameter is fixed. We want to make sure we are giving them the power to run the analyses.”
— Krishna Yeramsetty, Principal Data Scientist at Infinome
Create extremely flexible data and ML workflows
End-to-end data lineage
Track the health of your data and ML workflows at every stage of execution. Analyze data passages to identify the source of errors with ease.
Collaborate with reusable components
Integrate at the platform level
Your orchestration platform should integrate smoothly with the tools and services your teams use. Flyte offers both platform- and SDK-level integrations, making it easy to incorporate into your data/ML workflows as a plug-and-play service.
Allocate resources dynamically
Resource allocation shouldn’t require complex infrastructure changes or decisions at compile time. Flyte lets you fine-tune resources from within your code — at runtime or with real-time resource calculations — without having to tinker with the underlying infrastructure.
For data, ML and analytics
“Gojek is experiencing rapid growth and incorporating machine learning into various products. To sustain this growth and guarantee success, a reliable and scalable pipeline solution is critical. Flyte plays a vital role as a key component of Gojek’s ML Platform by providing exactly that.”
— Pradithya Aria Pura, Principal Software Engineer at Gojek
One platform for your workflow orchestration needs
Manage the lifecycle of your workflows on a centralized platform with ease and at scale without fragmentation of tooling across your data, ML & analytics stacks.
Build your data and ML workflows easily using the intuitive Python SDK or any language of your choice.
Minimal maintenance overhead
Set up once and revisit only if you need to make Flyte more extensible.
Robust and scalable like never before
Deploy your data and ML workflows with confidence. Focus on what matters most — the business logic of your workflows.
Receive timely responses to your questions on Slack, with an average response time of 6–8 hours or less.