What's changed: Created Professional Cloud DevOps Engineer Chapter 4 (Domain 4 "Observability": Ops Agent/OpenTelemetry/Managed Service for Prometheus/Cloud Audit Logs/VPC Flow Logs, log optimization, synthetic monitors, log-based metrics, Logs Explorer, BigQuery/Pub/Sub/Cloud Storage export, PII/PHI redaction; Metrics Explorer/PromQL dashboards/alerting policies/PagerDuty, distributed tracing Cloud Trace/OpenTelemetry, trace-log correlation, troubleshooting).
4.2Metrics, dashboards, alerts, and distributed tracing
Understand metric analysis via the Metrics Explorer, dashboards (PromQL, sharing, playbooks), alerting policies (SLI/SLO, cost) with third-party integration (e.g., PagerDuty), distributed tracing (OpenTelemetry, Cloud Trace, trace-log correlation), and troubleshooting infrastructure/CI-CD/app/performance/latency issues.
Collected telemetry only pays off when turned into visibility, awareness, and root-cause tracing. Visualize metrics, alert smartly, and follow latency causes via distributed tracing.
4.2.1Metrics, dashboards, and alerts
Explore metrics with the Metrics Explorer and collect them into dashboards (query with PromQL, share, attach playbooks). Set alerting policies on symptoms (SLI/SLO breaches, cost overruns) to avoid noise. Route notifications via webhooks to third-party tools like PagerDuty. Map "chart overview = dashboards" and "notify on SLO breach = alerting policies."
4.2.2Distributed tracing and troubleshooting
Trace microservice latency with distributed tracing (instrument with Cloud Trace/OpenTelemetry). Visualize a request as a waterfall of spans to find the slow call. Correlate the trace ID with structured logs to jump from a slow request to its detailed logs. Troubleshoot across layers—infrastructure/CI-CD/app/observability/performance-latency—by cross-referencing logs, metrics, and traces. Map "microservice latency cause = distributed tracing."
Common: requirement → means. E.g., "explore metrics" = Metrics Explorer; "dashboards with PromQL" = dashboards; "notify on SLO breach" = alerting policies; "on-call integration" = PagerDuty (webhooks); "find microservice latency" = distributed tracing (Cloud Trace); "jump to slow-request logs" = trace-ID-to-log correlation.
Watch the mix-ups: (1) Alert on symptoms (SLO/user impact), not causes, to avoid noise. (2) Metrics (aggregates) vs traces (one request’s path) vs logs (events) differ—correlate them. (3) Tracing usually samples, not every request.
4.2.3Section summary
- Explore via Metrics Explorer; dashboards (PromQL/playbooks); alert on SLO/cost symptoms + PagerDuty
- Distributed tracing = Cloud Trace/OpenTelemetry; span waterfalls; correlate trace ID with logs
- Troubleshoot by cross-referencing logs/metrics/traces across infra/CI-CD/app/performance
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Quick check
(just a quick review)Q1. To collect multiple metric charts on one screen and share with the team, which is best?
Q2. To notify on conditions like SLO breaches or cost overruns, which is best?
Q3. To identify which call is slow across microservices, which is best?
Q4. To jump quickly from a slow request’s trace to its detailed logs, what is most effective?
Q5. To send on-call escalation notifications to an external tool, which is a common integration?
Q6. To reduce notification noise, on what basis should alerts be designed?
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