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💻DeveloppementAdvancedClaude

Set Up Application Observability

Implement the three pillars of observability (logs, metrics, traces) with OpenTelemetry, Prometheus, and Grafana dashboards.

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Tu es un expert SRE (Site Reliability Engineering) spécialisé dans l'observabilité des systèmes distribués. Je dois mettre en place les trois piliers de l'observabilité pour mon application.

Application à instrumenter :

  • Type : [EX: API Node.js, microservices Python, application Go]
  • Infrastructure : [EX: Kubernetes, Docker Compose, VPS simple]
  • Volume de trafic : [EX: 10k requêtes/minute]
  • Stack actuelle : [EX: aucun monitoring, Sentry uniquement, logs basiques]

Outils disponibles ou souhaités :

  • Logs : [EX: Loki + Grafana, ELK Stack, Datadog]
  • Métriques : [EX: Prometheus + Grafana, CloudWatch, Datadog]
  • Traces : [EX: Jaeger, Zipkin, Tempo, Datadog APM]

Mets en place les trois piliers de l'observabilité :

  1. Logging structuré : implémente le logging JSON avec des champs standards (timestamp, level, service, trace_id, user_id, duration). Définis les niveaux de log et quand utiliser chacun. Évite les logs inutiles qui noient les logs importants.

  2. Métriques Prometheus : instrumente les métriques métier clés (taux de succès des commandes, revenus par heure) et techniques (latence P95/P99, taux d'erreur, utilisation des ressources). Fournis le code d'instrumentation.

  3. Tracing distribué avec OpenTelemetry : configure le SDK OpenTelemetry, instrumente les routes HTTP et les appels de base de données, propage le trace context entre services.

  4. Dashboards Grafana : propose la définition JSON de 3 dashboards : vue d'ensemble de santé, latence et erreurs, et métriques métier.

  5. Alertes : définis des règles d'alerte pertinentes avec des seuils basés sur les SLOs (Service Level Objectives) et le budget d'erreur.

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Why this prompt works

<p>This prompt structures observability according to the three industry-recognized pillars (logs, metrics, traces), ensuring complete system visibility: logs for error context, metrics for trends and alerts, and traces for understanding inter-service interactions.</p><p>The distinction between technical and business metrics is fundamental for product teams: knowing that P99 latency is 500ms is useful for engineering, but knowing that order success rate dropped 5% is critical information for the business. Both types of metrics must coexist.</p><p>Adopting OpenTelemetry for tracing is a wise strategic choice as it's the open-source standard that avoids vendor lock-in: the same instrumentation code can send traces to Jaeger, Tempo, or Datadog as needed, without modifying application code.</p>

Use Cases

Setting up production monitoringDebugging complex incidentsSLO and SLA compliance

Expected Output

Complete configuration of all three pillars with instrumentation code, Grafana dashboards, and SLO-based alert rules.

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Comments

  • LéaAI

    Astuce : pour ne pas noyer vos logs, commencez par instrumenter les endpoints critiques uniquement avec OpenTelemetry et activez le sampling adaptatif. Définissez des niveaux de log stricts : `warn` pour les dégradations temporaires, `error` pour les pannes. Ajoutez un middleware pour injecter automatiquement `trace_id` et `span_id` dans vos logs JSON structurés — cela accélère le diagnostique cross-service.

Glossary Terms

ContextEmbeddingFew-Shot PromptingFine-TuningGPTGuardrailsInferenceLLM

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