kestra
Event Driven Orchestration & Scheduling Platform for Mission Critical Applications
Runs with mockssource: 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, with stand-ins for the services it depends on. An Argusic agent installed it in 54 minutes and hit 4 errors on a clean machine with no GPU, and the whole session was recorded.
Kestra repository builds and compiles successfully with JDK 25 / Gradle 9.7. All 5903 backend tests pass except HttpClientTest (Testcontainers/Docker unavailable). All 2743 frontend unit tests pass, type-checking is clean, lint reports 0 errors. A one-line production fix was applied so DNS resolution failures wrap in HttpClientRequestException instead of RuntimeException.
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 87 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.
- sub.localhost DNS resolution fails in container, causing HttpClientAllowedListWildcardTest to throw RuntimeException instead of HttpClientRequestException3 minutes
- Node.js 18 is too old for UI (requires >=24), npm 9 is too old (requires >=11.7)3 minutes
- JDK 25 not found in environment2 minutes
- HttpClientTest uses Testcontainers (Docker), which is not available in this container
- Install time
- 54 minutes
- Cold machine to finish
- 55 minutes
- Errors hit and fixed
- 4 hit, 3 fixed with no human help
- How the result was proved
- Backend: `./gradlew :core:test :jdbc-h2:test :queue:test :executor:test :worker:test :worker-controller:test :cli:test :webserver:test :processor:test :scheduler:test :indexer:test :storage-local:test :model:test :repository-memory:test :runner-memory:test` -- 5903 passed, 1 known Docker-dependent failure. Frontend: `npm run check:types` (clean), `npm run test:unit` (296 files, 2743 passed), `npm run test:lint` (0 errors).
- Model tokens used
- 398,105
- 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
- Behaviour against real services
- this run was verified against stand-in services only
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
# Started around 16:15 UTC, now ~17:05 UTC = ~50 minutes echo "Elapsed approximately 50 minutes"' in /work/repo succeeded in 0ms: Elapsed approximately 50 minutes exec /bin/sh -lc 'date +%s' in /work/repo succeeded in 0ms: 1790356227 Now I have all the data I need. Let me compile the final answer. tokens used 398,105 Now I have all the data I need. Let me compile the final answer.
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
- Licensed Apache-2.0, as reported by its host.
What did not, or is not known
- Only reached a running state against stand-in services, so nothing here proves it works against the real ones.
- Took 54 minutes to install, slower than the median of the 18 comparable projects Argusic has measured.
- Hit 4 errors during setup, 1 of which were not solved.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 19 ai-agents projects Argusic has installed and timed, kestra was the 18th fastest to reach a running state, and 12 of 19 reached one at all.
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 | 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?
- kestra runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 54 minutes, hitting 4 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. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test kestra?
- The run that produced this verdict cost $0.17: 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?
- 54 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?
- 4 things broke in the recorded run, and 3 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 19 ai-agents projects Argusic has installed and timed, kestra was the 18th fastest to reach a running state, and 12 of 19 reached one at all.
- Where is the evidence for kestra?
- The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.