head to head · open source

Kestra vs Tracely-ai

Kestra has 28,146 GitHub stars, 2,997 forks, 713 open issues and last shipped yesterday. Tracely-ai has 1,406 stars, 172 forks, 21 open issues and last shipped 2 days ago. Kestra leads on adoption by 1,902% (28,146 vs 1,406 stars). Kestra is written in Java under Apache-2.0; Tracely-ai is written in Python under MIT. Kestra has attracted 11% as many forks as stars, Tracely-ai 12%. Kestra was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (ai-agents), so they are genuine substitutes rather than adjacent tools.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

Kestra ★ 28K Tracely-ai ★ 1.4K category Infrastructure & Operations

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Side by side

Kestra Tracely-ai
GitHub stars ★ 28K ★ 1.4K
License Apache-2.0 MIT
Written in Java Python
Last push 2026-09-17 2026-09-16
Forks ⑂ 3.0K ⑂ 172
Self-hosting Yes Yes
Data ownership Your server Your server

pick Kestra if

  • You weight community size — 28K stars and counting
  • You want the Apache-2.0 license terms
  • Your stack matches Java
  • You value the larger contributor base for long-term maintenance

full Kestra profile →

pick Tracely-ai if

  • You want the Tracely-ai feature set and don't need the biggest community
  • You prefer the MIT license terms
  • Your stack matches Python
  • You evaluated both and Tracely-ai fits your workflow better

full Tracely-ai profile →

About Kestra

Kestra is an open source, event driven orchestration platform for data, AI, and infrastructure workflows. It operates in the Java based ecosystem and is licensed under Apache 2.0. The project provides a unified interface for both scheduled and real time automation, supporting declarative workflow definitions in YAML while also offering visual and AI assisted authoring.

read the full Kestra overview →

About Tracely-ai

Tracely is a Python, MIT licensed project for AI agent operations and continuous integration. It lives in the AI agent, LLM observability, CI/CD, and evaluation ecosystem. The project treats production traces as the source of regression tests: when an agent run fails, Tracely can detect the failure, cluster related failures, freeze the bad run into a hermetic replayable case, and block a pull request that would reintroduce the same problem.

read the full Tracely-ai overview →

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More Orchestration & Scheduling projects

Compare either of these against the rest of the Orchestration & Scheduling field.

Kestra vs compose Kestra vs conductor Kestra vs xxl-job Kestra vs gitleaks Kestra vs haystack Kestra vs rancher Kestra vs Prefect Kestra vs Archon Kestra vs Temporal Kestra vs rowboat Kestra vs Trigger Kestra vs dolphinscheduler

Frequently asked questions

Is Kestra or Tracely-ai more popular?

Kestra has 28,146 GitHub stars and Tracely-ai has 1,406. Kestra has the larger community by that measure.

Are Kestra and Tracely-ai free?

Both are open source. Kestra is licensed under Apache-2.0 and Tracely-ai under MIT. Neither carries a licence fee.

What is the difference between Kestra and Tracely-ai?

Kestra is written in Java and Tracely-ai in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, Kestra or Tracely-ai?

Choose Kestra if you want the larger community (28,146 stars) or its Apache-2.0 licence terms. Choose Tracely-ai if its feature set, stack or MIT licence fits better. Both are self-hostable.