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Skill · Version 1.0.0

Monitoring und handlungsfähige Alarme

Verbindet Diensttelemetrie mit Nutzerfolgen für Diagnose und handlungsfähige Alarme mit klarer Verantwortung.

monitoring-logging-alerting

Entdecke, wie der Skill hilft

Wann ist der Skill hilfreich?

Nutze ihn bei unverbundenen Logs oder häufigen Alarmen ohne erkennbare Maßnahme.

Wobei hilft er dir?

  • Verknüpft Latenz, Verkehr, Fehler und Sättigung mit Dienstverhalten.
  • Verbindet strukturierte Logs über Korrelationskennungen ohne Geheimnisse.
  • Alarmiert bei Nutzerfolgen mit Verantwortlichen, Anleitungen und sinnvollen Schwellen.

Das könntest du fragen

Ersetze laute CPU-Alarme durch einen handlungsfähigen Warteschlangenstillstands-Alarm. Pausiere einen Worker im kontrollierten Test und beobachte steigendes Auftragsalter. Alarmiere Verantwortliche mit Queue-Kennung, Nutzerwirkung und Wiederherstellungsanleitung.

Ausführliche Dokumentation

Hier findest du die ursprüngliche Anleitung, Beispiele und Prüfschritte des Skills in ihrer Originalsprache.

Details…Weniger anzeigen

Monitoring, Logging & Alerting

Observability exists to answer two questions quickly during normal operations and incidents: Are users experiencing a problem right now? and Where in the system is the bottleneck or failure?

The Four Golden Signals & USE/RED Metrics

Measure both user-facing service health (RED) and underlying resource health (USE):

Signal What to Measure Why Averages Lie
Latency Request & job duration histograms (p50, p95, p99), separated for successful (2xx) vs. failed (5xx) requests A fast 500 error (2ms) drags down average latency and hides 30s timeouts on 200 responses!
Traffic / Rate Requests/sec, jobs enqueued/sec, active connections Establishes baseline load and distinguishes traffic spikes from zero-traffic outages.
Errors HTTP 5xx rate, unhandled exceptions, failed background jobs, dead-letter queue growth, synthetic check failures Direct indicator of broken user flows.
Saturation DB connection pool utilization, queue depth / consumer lag, CPU throttling, memory working set vs. limit, disk Space/IOPS Predicts impending failure before hard errors begin (often degrades steeply above 80–85% utilization).

Structured, Correlated & Redacted Logging

  1. Single-line JSON structured logs in production:
    • Include standard fields on every log entry: timestamp (ISO-8601 UTC), level, service, version (git_sha), env, request_id / trace_id, job_id, duration_ms, and error.code / error.stack.
  2. Propagate correlation IDs across boundaries:
    • Accept or generate an incoming x-request-id / W3C traceparent header at the edge, attach it to all logs, pass it to outbound HTTP calls and enqueued background jobs, and echo it in error responses so users and engineers can locate the exact trace.
  3. Never log secrets or high-cardinality PII:
    • Redact Authorization headers, cookies, session tokens, API keys, passwords, and raw payment/personal data at the logger serializer layer.

Actionable Alerting Discipline

Every page/notification must require human action and point to a clear next step:

  • Page on user-visible symptoms (SLO burn rate, high error rate, queue stall, disk near full) rather than noisy transient CPU spikes that self-heal.
  • Mandatory alert metadata: Every alert rule must define:
    1. Impact: What user or system capability is degraded?
    2. Owner / Routing: Which role or channel is responsible?
    3. Runbook / First Triage Steps: Exact dashboard link, log query, and safe mitigation options (e.g., rollback, scale worker, drain node).
  • Never silence a recurring alert permanently without fixing the underlying cause or recalibrating the threshold with measured evidence.

Enthaltene Dateien 1

  • SKILL.md