Complete observability strategy (logs, metrics, and tracing) for production
Implements the 3 pillars of observability using OpenTelemetry, Prometheus, Grafana, and open source tools to achieve full visibility into production systems.
Build an observability platform that enables proactive problem detection, rapid incident diagnosis, and full understanding of production system behavior using 3 pillars: structured logs, metrics, and distributed tracing.
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Prompt objective
Build an observability platform that enables proactive problem detection, rapid incident diagnosis, and full understanding of production system behavior using 3 pillars: structured logs, metrics, and distributed tracing.
Real use case
An HR tech startup experienced 3 production incidents last month, each taking an average of 4 hours to diagnose. The team discovers problems from user complaints, not from alerts. The CTO wants to implement real observability before the next Black Friday, when traffic triples.
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Prompt
Implement a complete Observability Strategy for:\\\\\\\\n\\\\\\\\nProject: [PROJECT NAME]\\\\\\\\nStack: [LANGUAGE/FRAMEWORK + DATABASE + CACHE + QUEUE]\\\\\\\\nInfrastructure: [AWS / GCP / AZURE / ON-PREMISE]\\\\\\\\nArchitecture: [MONOLITH / MICROSERVICES — NUMBER OF SERVICES]\\\\\\\\nCurrent volume: [REQUESTS/DAY]\\\\\\\\nTeam: [NUMBER] devs + [NUMBER] ops/SRE\\\\\\\\nSLA target: [UPTIME]% with RTO of [HOURS] and RPO of [HOURS]\\\\\\\\nRecent major incidents: [DESCRIBE THE TYPE OF ISSUE]\\\\\\\\nCurrent alerting/on-call tool: [E.G. PagerDuty, email, none]\\\\\\\\n\\\\\\\\n## PILLAR 1 — STRUCTURED LOGGING\\\\\\\\n\\\\\\\\n**Why structured (JSON) logs are mandatory:**\\\\\\\\n- Searchable by field: filter \\\\\\\\\\\\\\\\\\\\\\\`level=error AND service=payments\\\\\\\\\\\\\\\\\\\\\\\`\\\\\\\\n- Parseable by tools: ELK, Datadog, CloudWatch Insights\\\\\\\\n- Correlatable via \\\\\\\\\\\\\\\\\\\\\\\`correlationId\\\\\\\\\\\\\\\\\\\\\\\` / \\\\\\\\\\\\\\\\\\\\\\\`traceId\\\\\\\\\\\\\\\\\\\\\\\`\\\\\\\\n\\\\\\\\n**Required fields in every log entry:**\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\`\\\\\\\\\\\\\\\\\\\\\\\`\\\\\\\\\\\\\\\\\\\\\\\`json\\\\\\\\n{\\\\\\\\n \\\\\\\\Open directly in an AI — the text is pre-filled:
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