Quality Gates in Production: How We Turn OpenTelemetry...
summary
Describes an automated pipeline that prevents unsafe rollouts by gating production deployments on real production-like checks: OpenTelemetry traces logs metrics correlate deploy events with error rates and latency, CI/CD steps emit spans, and Prometheus alerts block if P1/P2 fire. Uses ArgoCD + GitHub Actions + Playwright + Checkly plus TestContainers; MLFlow tracks models and gates on patch coverage with thresholds 90% (degraded) and 85% (critical). Result: end-to-end tests stabilize, alert quality improves, and deployments rise to about 5–10 productions per day.
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chapters (13)
- 0:00Introduction
- 3:56Manual deployment challenges
- 5:22Automated quality gates
- 6:48Kubernetes cluster check
- 7:30External monitoring gate
- 8:12Development alerts verification
- 9:59CI/CD tracing with OpenTelemetry
- 12:10End-to-end pipeline testing
- 13:34AI services deployment
- 16:29Lessons learned
- 18:17Cost optimization with GitHub runners
- 19:23Engineering workflow impact
- 20:24Recommendations and future plans
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