What is Flyte used for?

Flyte is a durable AI runtime that orchestrates training, serving, and agent workloads with automatic failure recovery. It is a good fit for batch inference, fine-tuning and pretraining.

Is Flyte open source?

Yes. Flyte is open source under the Apache-2.0 licence. Its source code is on GitHub at flyteorg/flyte and is written mainly in Go.

Yes. Flyte is open source, so the software itself is free to use. A managed cloud version is also available.

Can I self-host Flyte?

Yes. Flyte can be self-hosted on your own server or infrastructure.

What is Flyte an alternative to?

Flyte is an open-source alternative to Amazon SageMaker, Domino Data Lab, NVIDIA AI Enterprise and Valohai. Other open-source alternatives to Amazon SageMaker include Kubeflow, MLflow and Pachyderm.

Is Flyte actively maintained?

Yes. The most recent commit to Flyte was on 13 October 2026, and the latest release is v2.0.51, published on 8 October 2026. The project has 7.7k stars on GitHub.

Flyte: open-source alternative to Amazon SageMaker

About Flyte

Flyte is a distributed orchestration platform for AI workloads, including training, serving, and agents. It runs on Kubernetes and supports writing workflows in pure Python with async/await, as well as other languages like Rust, Go, and TypeScript. The platform is designed to recover from infrastructure and code failures automatically.

Workflows are defined as plain async functions without DSL or YAML. A TaskEnvironment declares images, resources, secrets, and retry policies. The runtime records I/O for every step so that a crash resumes instead of restarting. The same code can run locally, on a devbox, or on a cluster.

Key features

Type-checked I/O between tasks using language-native types, files, DataFrames, and dataclasses
Native agents that wrap tools as tasks with traced LLM calls
Automatic recovery from API rate limits, network errors, OOM kills, node interruptions, GPU disappears, and code exceptions
Supports batch inference, fine-tuning, pretraining, and RL agent loops
Real-time model endpoints and dashboards served with the same Python API

Good fit for

Batch inference
Fine-tuning
Pretraining

Built with: Go tools; Kubernetes tools; Python tools
Tags: orchestration; kubernetes; machine-learning; ai; workflow; python

Flyte: questions and answers

What is Flyte used for?: Flyte is a durable AI runtime that orchestrates training, serving, and agent workloads with automatic failure recovery. It is a good fit for batch inference, fine-tuning and pretraining.
Is Flyte open source?: Yes. Flyte is open source under the Apache-2.0 licence. Its source code is on GitHub at flyteorg/flyte and is written mainly in Go.
Is Flyte free?: Yes. Flyte is open source, so the software itself is free to use. A managed cloud version is also available.
Can I self-host Flyte?: Yes. Flyte can be self-hosted on your own server or infrastructure.
What is Flyte an alternative to?: Flyte is an open-source alternative to Amazon SageMaker, Domino Data Lab, NVIDIA AI Enterprise and Valohai. Other open-source alternatives to Amazon SageMaker include Kubeflow, MLflow and Pachyderm.
Is Flyte actively maintained?: Yes. The most recent commit to Flyte was on 13 October 2026, and the latest release is v2.0.51, published on 8 October 2026. The project has 7.7k stars on GitHub.