Correlate Observability Signals
技能 已验证 活跃Unify metrics, logs, and traces for cohesive debugging. Implement exemplars for log-to-trace linking, build unified dashboards using RED/USE methods, and enable rapid root cause analysis across observability signals. Use when investigating complex incidents spanning multiple systems, reducing mean time to resolution, implementing distributed tracing, or moving from siloed tools to a unified observability platform.
To enable cohesive debugging and rapid root cause analysis by unifying metrics, logs, and traces into a single observability view.
功能
- Implement trace context propagation in logs and metrics
- Configure Prometheus exemplars for log-to-trace linking
- Build unified dashboards using RED and USE methods
- Link logs to traces in Loki for cohesive debugging
- Provide step-by-step guidance for incident investigation workflows
使用场景
- Investigating complex incidents spanning multiple systems
- Reducing mean time to resolution (MTTR)
- Building unified observability dashboards
- Implementing distributed tracing across services
非目标
- Configuring the underlying observability backends (Prometheus, Loki, Tempo)
- Writing application code beyond instrumentation for trace propagation
- Replacing existing monitoring and alerting tools
工作流
- Implement Trace Context Propagation
- Configure Exemplars in Prometheus
- Build Unified Dashboard with RED Method
- Implement USE Method for Resources
- Link Logs to Traces in Loki
- Create Unified Incident View
实践
- Observability
- Distributed Tracing
- Debugging
- Incident Response
先决条件
- Prometheus (metrics)
- Log aggregation system (Loki, Elasticsearch, CloudWatch)
- Distributed tracing backend (Tempo, Jaeger, Zipkin)
- Optional: Grafana for unified visualization
- Optional: OpenTelemetry instrumentation
安装
/plugin install agent-almanac@pjt222-agent-almanac质量评分
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