flyte: a Kubernetes-native orchestration platform for scaling ML pipelines and AI agents in pure Python

What it solves

Flyte is designed to reliably orchestrate ML pipelines, models, and agents at scale. It allows developers to build and deploy these complex workflows in pure Python, simplifying the transition from local development to production-grade distributed systems.

How it works

Flyte uses a Python-based environment system to define tasks and workflows. Users can specify the exact environment (including Python version and pip packages) via TaskEnvironment or FastAPIAppEnvironment, which Flyte then handles. It supports asynchronous execution of tasks using asyncio and provides both a Python API and a CLI for running and serving models as services (e.g., via FastAPI).

Who it’s for

It is intended for ML engineers and data scientists who need to scale their Python-based ML workflows, from simple task orchestration to serving models as APIs.

Highlights

• Pure Python Experience: Orchestrate pipelines and agents using Python decorators and native async support.
• Kubernetes-native: The backend infrastructure is built to be a distributed, multi-node service on Kubernetes.
• Model Serving: Built-in capabilities to serve models as APIs using FastAPI integration.
• Local Development: Includes a TUI for a rich local development experience and a hosted browser-based demo.