Docs > Platform Observability > Getting Started with Pipeline Monitoring
Getting Started with Pipeline Monitoring
Overview
This guide introduces AppStatus Pipeline Monitoring and covers:
- Record every CI/CD and data pipeline run
- Duration, outcome and the stage that failed
- Deploy markers on APM and error timelines
- Cancelled runs reported separately from failures
- Duration trend so a slowly lengthening build is visible
What is Pipeline Monitoring in AppStatus?
Pipeline monitoring records each CI/CD or data pipeline run and marks your deploys onto the performance and error timelines, so a change in latency can be lined up against the release that caused it.
That marker is the point of the feature. A latency change that starts exactly at a deploy marker is a release problem until proven otherwise, and having the marker turns a long debate into a short one.
Key capabilities:
- Run history with duration, outcome and failing stage
- Deploy markers rendered on APM and Error Tracking timelines
- Commit or version attribution per run
- Cancelled runs distinguished from failed ones
- Duration trend per pipeline over time
What you will see
What the run history looks like
Scroll the table sideways to see every column.
Repeated failures at the same stage are worth fixing before adding retries.
Troubleshooting
Runs appear but no deploy markers show on APM
The run needs a commit or version to attribute against, and the service name must match the one APM reports. Without both, the run is recorded but cannot be placed on a service timeline.
Every run shows as failed
Check the webhook is called on completion with the real outcome, not only at start. A run that never reports a finish is treated as unfinished, which reads as a failure.
Duration is growing but nothing is broken
That is exactly what the trend view is for. A build that lengthens a few seconds per week costs your team every day; it is worth treating as work rather than waiting for it to break.
Operational Guidance
- A latency change that starts exactly at a deploy marker is a release problem until proven otherwise.
- Track pipeline duration trend — a slowly lengthening build is a cost you pay every day.
- Repeated failures at the same stage are worth fixing before adding retries.
Step-by-Step Setup
Two webhook calls from your CI job — one at start, one at finish — and your deploys start appearing as markers on the performance timelines. The commit is the field that makes it all work.
Before you start
- A CI/CD or data pipeline you can add a step to
- 1
Create an ingest key scoped to pipelines
Open Ingest Keys and create a key scoped to pipelines for the environment you are setting up. The key value is shown once — copy it into your secret manager now, not into source control.
WhereIngest Keys → Create keyTipOne scope per key. A key reused across signals turns a single leak into full ingest access.
- 2
Call the webhook on start
Add a step at the beginning of your pipeline that reports the run has started, with the pipeline name and the commit or version being built.
WherePipeline Monitoring → Setup → copy webhook - 3
Call it again on finish
Report the outcome when the run ends — success, failure or cancelled — and the failing stage if there was one. A run that never reports a finish is treated as unfinished, which reads as a failure.
WhereYour CI configurationTipUse an always-run step so cancelled and failed runs still report. This is the most common setup mistake.
- 4
Confirm the run appears
Trigger the pipeline once and confirm the run shows with its duration, stages and outcome.
WherePipeline Monitoring → Runs - 5
Check the deploy marker
Open APM for the service you just deployed and confirm a marker appears on the timeline. If it does not, the commit or the service name is not matching what APM reports.
WhereAPM → Services → timeline
Configuration Options
Every option you can set, what each choice means, and what to pick. Use this as a reference while you fill in the form.
Run reporting
| Field | Options | What it does | Recommended |
|---|---|---|---|
| Pipeline name | Any string | Groups runs together. | One name per pipeline definition, stable across branches. |
| Commit / version | SHA or build number | Links the run to a deploy marker. | Always send it, or the marker cannot be attributed. |
| Stage | Step name | Which step failed. | Report stages so failures point at a step, not the whole run. |
| Outcome | success / failed / cancelled | How the run ended. | Report cancelled separately so it does not read as a failure. |
Feature Reference
Every feature, where to find it in the app, and what it does. Use this when you know what you want to do but not where it lives.
| Feature | Where in app | Description |
|---|---|---|
| Run history | Pipeline Monitoring → Runs | Duration, outcome and failing stage per run. |
| Deploy markers | APM and Error Tracking timelines | Releases marked where performance changed. |
| Duration trend | Pipeline detail | A slowly lengthening build made visible. |
| Release attribution | Error Tracking → issue | New issues tied to the deploy that introduced them. |
Next Steps
Continue building your monitoring stack:
