Pipeline demo
CI/CD failure investigation
Separate the failing check that matters from the ten that failed downstream of it.
The challenge
A red pipeline reports many failures, most of them consequences of one cause, and the cause is not the first one listed.
The scenario
The main branch goes red with eleven failing checks across three pipelines. The team needs to know which one to actually fix.
What goes in
- Failing checks
- Current check results across pipelines.
- Change history
- Recent commits and their scope.
What you can ask
Illustrative prompts. Results depend on your own data and are not deterministic.
- “Which failing check is the actual cause?”
- “Has this failure happened before?”
- “Which change introduced this?”
How Clearception approaches it
How the work is structured. Each step shows what its output is grounded in.
Group the failures
AI-inferredCluster failures that share a cause or a dependency.
Correlate with change
ObservedMatch failure onset to the changes that preceded it.
Check history
ObservedLook for prior occurrences of the same signature.
Report the likely cause
AI-inferredName the candidate cause and the evidence for it.
What you get
The shape of what comes back — not a promised result.
Cause candidate
AI-inferredThe failure most likely upstream, with the change that introduced it.
Downstream list
AI-inferredFailures explained as consequences rather than separate problems.
Why it matters
- One thing to fix
- Attention goes to the cause rather than the loudest symptom.
- Repeat failures recognised
- A known flake is identified as one.
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Want to try this with your own work?
Open Pipeline and bring your own data. No signup is needed to read these demos.