Flyte

Flyte

Flyte is a production-grade workflow orchestration platform built by Lyft, Union.ai, and the open-source community. It models ML pipelines as strongly-typed Directed Acyclic Graphs (DAGs), with each task running as a containerized Kubernetes pod — giving full reproducibility, scalability, and multi-cloud portability.

Key Features

• Type-safe workflows — Python type hints on task inputs/outputs enforced at compile time and runtime
• Kubernetes-native — every task runs in its own pod; leverage GPU, TPU, Spark, Ray, or MPI backends
• Versioned artifacts — all executions, inputs, outputs, and code are stored and retrievable for reproducibility
• Dynamic workflows — fan-out, map tasks, and conditional branching in pure Python (no YAML required)
• Plugins — Spark, Ray, Dask, SageMaker, BigQuery, Snowflake, and 50+ integrations via flytekit-plugins
• UI — rich console with execution graphs, logs, and artifact lineage
• Multi-cloud — runs on AWS, GCP, Azure, and on-premises Kubernetes

Quick Start

pip install flytekit
flytectl demo start

from flytekit import task, workflow

@task
def say_hello(name: str) -> str:
    return f"Hello, {name}!"

@workflow
def my_workflow(name: str = "world") -> str:
    return say_hello(name=name)

Install via ai-supply

npx ai-supply add flyte-ml-workflow-orchestration

Curated mirror of the open-source Flyte (Apache-2.0). Get it from the source.