flyte

Free

Dynamic, resilient AI orchestration. Coordinate data, models, and compute as you build AI workflows.

Model APIsFreeFree tier

Type

Open Source

Company

Flyte

Visit Website GitHub (7.0k stars)

About flyte

Flyte is an open-source AI orchestration platform that enables developers to build, test, and scale dynamic, fault-tolerant workflows in pure Python. It supports durable execution with automatic retries and failure recovery, dynamic workflow decisions at runtime, and infrastructure-aware autoscaling. Workflows can be developed locally and deployed to Kubernetes for production. Key features include strongly typed interfaces, map tasks for parallel processing, built-in caching and versioning, and integrations with tools like Apache Spark, BigQuery, PyTorch, Ray, and Snowflake. Trusted by companies like Spotify, Wayve, and Warner Bros. Discovery, Flyte streamlines AI/ML pipelines, agentic workflows, and data processing.

Key Features

Author in pure Python without needing a DSL

Durable workflows with automatic retries and failure recovery

Dynamic workflow execution with runtime decisions and conditions

Infrastructure-aware autoscaling for complex workflows

Run and debug workflows locally, then deploy to Kubernetes

Strongly typed interfaces with built-in data validation

Map tasks for parallel processing (e.g., hyperparameter tuning)

Built-in caching and versioning for fast, repeatable runs

Integrations with Spark, BigQuery, PyTorch Elastic, Ray, Snowflake, Weights & Biases

Self-healing workflows that recover autonomously from failures

Pros & Cons

Pros

Pure Python authoring with no DSL to learn
Durable execution ensures workflows survive failures
Dynamic workflows adapt at runtime, enabling complex logic
Scalable from local development to production on Kubernetes
Strong typing catches errors early and validates data
Rich ecosystem of integrations and active community
Open-source with enterprise option (Union.ai) for advanced needs

Cons

Requires Kubernetes for full production scalability
May have a steep learning curve for users unfamiliar with distributed systems
Advanced features (e.g., real-time inference, live debugger) require enterprise edition

Best For

Building and orchestrating AI/ML pipelinesDeveloping agentic workflows with stateful executionData processing and transformation at scaleModel training, hyperparameter tuning, and distributed computingDeploying and serving real-time inference with sub-second latencyAutomating ETL and data validation pipelines

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FAQ

What is Flyte?

Flyte is an open-source AI orchestration platform that allows you to build, test, and scale dynamic, fault-tolerant workflows using pure Python, without needing a DSL.

How does Flyte handle failures?

Flyte is durable by default: workflows automatically retry on failure, pick up where they left off, and can self-heal, making failures inconsequential.

Can I run Flyte locally?

Yes, you can test and debug tasks in your local environment using the same Python SDK that runs in production on Kubernetes.

What languages does Flyte support?

Flyte supports writing workflows in Python, Java, Scala, and JavaScript, and you can also use any language via raw containers.

How do I get started with Flyte?

You can start by exploring the official docs, trying the Flyte Devbox for local execution, or checking out the community and case studies on the website.