Analyze a Jenkins Job

Run analysis against a Jenkins build, follow it from queue to report, and start another pass when you need updated output or different AI settings. This gets you from a job name and build number to a usable result quickly, without losing the original run when you retry.

Note: The web UI uses the dashboard to monitor and reopen analyses. New Jenkins analyses are submitted through jji or the REST API, then tracked from the dashboard and live status view.

Prerequisites

• A reachable JJI server.
• A Jenkins job name and build number.
• Jenkins access and an AI provider/model already configured on the server, or passed on the request.
• For the browser, a username in the web app if prompted.
• For jji, either pass --server and --user, or use a default CLI server profile.
• If your server uses an allow list, use a permitted username.

Quick Example

jji --server http://localhost:8000 --user alice analyze \
  --job-name "my-job" \
  --build-number 42 \
  --provider claude \
  --model opus

jji --server http://localhost:8000 --user alice status <job-id>

jji --server http://localhost:8000 --user alice re-analyze <job-id>

The first command queues the analysis and prints a new job_id plus a poll link. Use that job_id in the next commands to watch the run or queue another analysis of the same Jenkins build.

Tip: If you already set a default CLI server profile, you can usually omit --server and --user. See Configuration and Environment Reference for details.

Step-by-Step

1. Queue the analysis.

jji --server http://localhost:8000 --user alice analyze \
  --job-name "my-job" \
  --build-number 42 \
  --provider claude \
  --model opus

JJI returns immediately with queued, a new job_id, and a result_url. Keep the job_id; you will use it to watch the run and open the finished report.

1. Watch the run from the status view or dashboard.

jji --server http://localhost:8000 --user alice status <job-id>

Open the dashboard in your browser to watch the same run live. Active rows open the status view, and both the dashboard and status view refresh automatically.

Note: Timed Out is a web UI label for AI-analysis timeouts. The API and CLI still report the underlying run as failed.

1. Open the finished result.

jji --server http://localhost:8000 --user alice results show <job-id>

In the browser, click the completed row in the dashboard. If you open the returned result_url before the run finishes, JJI redirects you to the live status view automatically.

See Investigate Failure History for details if you need to compare recurring failures across builds. See Create GitHub Issues and Jira Bugs for details if the result should become a ticket.

1. Run it again when you need another pass.

jji --server http://localhost:8000 --user alice re-analyze <job-id>

Use this when you want the fastest retry with the same saved settings. JJI creates a new analysis record and a new job_id, but it keeps the same Jenkins job and build number.

Use the Re-Analyze button on a failed status page or a completed report when you need to change AI settings before retrying. That path can override provider/model, AI timeout, prompt, repo context, Jira settings, and peer-review settings.

Warning: Re-Analyze does not trigger a new Jenkins build. If you need fresh Jenkins output, rerun the job in Jenkins first and then submit the new build number with jji analyze or POST /analyze.

Advanced Usage

Submit Through the REST API

curl -sS -X POST "http://localhost:8000/analyze" \
  -H "Content-Type: application/json" \
  -H "Cookie: jji_username=alice" \
  -d '{"job_name":"my-job","build_number":42,"ai_provider":"claude","ai_model":"opus"}'

Poll the returned job with GET /results/<job-id> until it reaches completed or failed. While a run is still active, GET /results/<job-id> returns HTTP 202; once it finishes, it returns HTTP 200.

Re-Analyze Through the REST API With Overrides

curl -sS -X POST "http://localhost:8000/re-analyze/<job-id>" \
  -H "Content-Type: application/json" \
  -H "Cookie: jji_username=alice" \
  -d '{"ai_provider":"claude","ai_model":"opus","ai_cli_timeout":20}'

Use this when the quick CLI rerun is too limited. The rerun keeps the original Jenkins job and build number, but lets you override the shared analysis fields that the endpoint accepts.

Pick the Right Rerun Path

Useful jji analyze Flags

The live status view can show more than one phase on longer runs, including waiting for Jenkins, analyzing test failures, analyzing child jobs, Jira enrichment, peer-review rounds, and the final save step. The progress log is persisted, so refreshing the page does not erase what has already happened.

See CLI Command Reference for details on every command and flag. See REST API Reference for details on every request field and status code. See Configuration and Environment Reference for details on reusable CLI server profiles and server defaults.

Troubleshooting

• You cannot see Re-Analyze: wait for the run to fail or complete. Active runs stay on the live status flow.
• 400 when you submit a run usually means the request is missing required fields such as job_name, build_number, ai_provider, or ai_model, or the build number is not numeric.
• 403 from the API or Access denied in the browser usually means your user is not allowed to use this server or view that job.
• Job not found usually means the job_id is wrong or the analysis was deleted.
• Timed Out in the web UI means the AI analysis timed out. Retry with a longer AI timeout or a different model.
• After a server restart, jobs that were still waiting resume automatically. Jobs that were already pending or running should be requeued.

Related Pages

• Analyze Your First Jenkins Job
• Customize AI Analysis
• Review and Classify Failures
• Investigate Failure History
• Create GitHub Issues and Jira Bugs