How We Gained Observability Into Our CI/CD Pipeline
summary
A Jenkins pipeline summary step serializes branch, machine, step durations, status and flakiness into a JSON and persists it to OpenSearch/Elasticsearch so historical runs live off Jenkins; traces emit via OpenTelemetry (OTLP → OTLP -> Jaeger) to visualize span timelines; metrics flow from Jenkins endpoints through Telegraf -> Prometheus into Grafana; Kibana/OpenSearch dashboards answer failure-by-step, flaky-test and machine-level questions and deliver start-of-day Slack reports and alerts. Result: shorter lead time for changes and far fewer false debugging detours.
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chapters (17)
- 0:00The observability challenge
- 2:22Introduction and context
- 4:52Defining success with DORA
- 7:10Project requirements
- 9:03Collecting pipeline data
- 12:09Visualizing CI/CD metrics
- 13:59Reporting and alerting
- 15:36Test performance analysis
- 17:49Organizational flexibility
- 19:49Distributed tracing in CI/CD
- 21:26Tracing implementation
- 23:37Granular instrumentation
- 28:50Infrastructure metrics
- 30:48Advanced infrastructure views
- 35:06Summary of best practices
- 38:42Standardization efforts
- 40:37Q&A and conclusion
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