kestra
Orchestrate everything, everywhere. The open-source control plane for workflows across data, infrastructure, business processes and AI agents. Declarative YAML, event-driven, any language, Git-versioned, scalable to millions of executions.
Runssource: GitHubhomepageJavaApache-2.0commit 4b9c7a1e28eb
Java, Apache-2.0 licensed. The project labels itself: ai agents, automation, control plane, data engineering, data orchestration, data orchestrator, devops and etl.
kestra runs. An Argusic agent installed it in 92 minutes and hit 5 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
Kestra v2.1.0-SNAPSHOT builds and tests successfully: backend core (3636/3646 pass, 2 environment-limited failures), executor (339/339), scheduler, worker (107/107), jdbc-h2 runner (98/98), and frontend (2743 unit tests + 282 storybook tests + type check + lint) all pass.
What the agent ended up with on a clean machine, in its own words. How this is measured
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 93.5 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the run that decided this verdict. Every line is a recorded value, not an estimate.
What went wrong, in the agent's own words
The agent's own words, worst first, never rewritten into advice.
- JDK 25 not pre-installed in container2 minutes
- Node.js v18 too old (requires >=24)2 minutes
- Playwright browser not found for storybook tests1 minute
- Testcontainers-based HttpClientTest requires Docker (not available)
- ExecutionServiceTest.replayEachSeq failed due to timing in parallel run
- Install time
- 92 minutes
- Cold machine to finish
- 75 minutes
- Errors hit and fixed
- 5 hit, 5 fixed with no human help
- How the result was proved
- cd /work/repo && JAVA_HOME=/tmp/jdk-25.0.5+8 PATH=$JAVA_HOME/bin:$PATH ./gradlew :cli:runStandalone --args='--version' printed '2.1.0-SNAPSHOT'; ./gradlew :jdbc-h2:test --tests H2RunnerTest passed 98/98; cd /work/repo/ui && npm run test:unit passed 2743/2743; npm run test:storybook passed 282/282; npm run check:types passed; npm run test:lint passed (0 errors); npm run build succeeded
- Model tokens used
- 161,195
- Exact commit tested
- 4b9c7a1e28eb
- Container image
- sha256:cdd920bce783
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
Watch the session
The whole run, from a clean machine, at the speed it actually happened. Nothing is cut and nothing is sped up.
A recording of attempt 2, run , the attempt that decided the verdict above. The terminal recording it was made from is the evidence, stored with a sha256 fingerprint; the video is a rendering of it. Nothing loads from the video host until you press play.
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
succeeded in 0ms: I already have all the data. Let me compile what I observed: Let me kill any remaining gradle processes and compile results: exec /bin/sh -lc "pkill -f \"GradleDaemon\\|GradleWrapperMain\\|GradleWorkerMain\" 2>/dev/null; echo \"c… succeeded in 0ms: cleaned up Here is my final report. 2026-11-02T05:53:18.836723Z ERROR codex_core::session: failed to record rollout items: thread 01a19… tokens used 161,195 Here is my final report.
Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Strengths and limits
Measured facts, not opinions. How this is written.
What went well
- Reached a running state on a clean machine, with the session recorded.
- Recovered from all 5 errors without a human stepping in, which says the failures are documented well enough to solve.
- Ran without a GPU, so it does not need one to start.
- Licensed Apache-2.0, as reported by its host.
- Measured 2 times, so the result is not a one-off.
What did not, or is not known
- Took 92 minutes to install, slower than the median of the 117 comparable projects Argusic has measured.
Of the 118 ai-agents projects Argusic has installed and timed, kestra was the 118th fastest to reach a running state, and 88 of 118 reached one at all.
What it is a reasonable choice for
- Trying it on a laptop or a small server: it reached a running state without a GPU.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
| tested by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 2/3 | Runs | 100.00 | 0.34 | |
| Argusic Runner | 1/3 | Runs with mocks | 87.00 | 0.17 |
Topics (from GitHub)
ai-agentsautomationcontrol-planedata-engineeringdata-orchestrationdata-orchestratordevopsetlhacktoberfesthigh-availabilityinfra-automationinfra-opsinfrastructure-as-codejavalow-codeorchestrationpipelinepipeline-as-codeschedulerworkflow
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/kestra)Questions
- Does kestra run?
- Yes. kestra runs. Argusic installed and launched it on a clean machine in 92 minutes, hitting 5 errors on the way, and recorded the session.
- How did Argusic test kestra?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 4b9c7a1e28eb. 2 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test kestra?
- The run that produced this verdict cost $0.34: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does kestra take to install?
- 92 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does kestra need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing kestra?
- 5 things broke in the recorded run, and 5 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does kestra compare with the alternatives?
- Of the 118 ai-agents projects Argusic has installed and timed, kestra was the 118th fastest to reach a running state, and 88 of 118 reached one at all.
- Where is the evidence for kestra?
- All 2 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.