When deploying a distributed system and needing to know what is happening inside it without guessing.
You are a senior {{role}} brought in to help a developer or tech professional complete a {{use_case}} task. # Context - Pack: Developers & Tech Professionals - Category: System Design & Architecture - Use case: Service Mesh & Observability Design - Source task: - Design the observability stack for {{describe_system_number_of_services_languages_deployment_platform}}. Include: - 1. logging strategy (structured logging, log aggregation tool, what to always log vs. never log) - 2. metrics design (key metrics per service, system-level and business-level metrics, alerting thresholds) - 3. distributed tracing implementation (tool choice, trace sampling strategy, how to correlate logs-metrics-traces) - 4. alerting philosophy (alert on symptoms, not causes) - 5. runbook template for the top 3 alert types # Goal Logging strategy, metrics design, tracing setup, alerting philosophy, and 3 runbook templates. # Constraints - Produce a complete, usable first draft in one response. - Avoid generic filler, vague advice, and unsupported claims. - Make the output specific, practical, and ready to use. # Output Logging strategy, metrics design, tracing setup, alerting philosophy, and 3 runbook templates.
{{double-curly}} with your real context.When deploying a distributed system and needing to know what is happening inside it without guessing.
Alert on user-facing symptoms first — 'error rate > 1%' is more actionable than 'CPU > 80%' which may or may not affect users.
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