Observability Designer
Design production-ready observability strategies combining metrics, logs, and traces.
Before & after
Same prompt, same agent — the only difference is the skill.
I can help you design an observability strategy for your new microservice. There are three pillars you'll want to consider: metrics, logs, and traces. Metrics give you the aggregate view, logs help with debugging, and traces show you the flow of requests across services. You might want to start by identifying your key business metrics and technical metrics. I could walk you through the golden signals framework or help you think about SLO design. What's your current observability stack—Prometheus, Datadog, something else? Once I understand your setup, I can help you design a strategy that fits your needs.
OBSERVABILITY STRATEGY FOR MICROSERVICE SERVICE DETAILS • Name: OrderProcessor (payment flow) • Criticality: Tier 1 (revenue-impacting) • Traffic: 50 req/sec (peak 120 req/sec) GOLDEN SIGNALS LATENCY • Metric: p50, p95, p99 response time (ms) • Target: p95 < 200ms • Alert: p95 > 250ms for 2 min ERROR RATE • Metric: 5xx errors / total requests • Target: < 0.1% (0.001 error rate) • Alert: > 0.5% for 1 min TRAFFIC • Metric: requests per second • Target: normal range 40-80 req/sec • Alert: < 10 req/sec (possible outage) or > 150 req/sec (spike) SATURATION • Metric: CPU (% used), Memory (%), Database connections (active/pool size) • Target: CPU < 60%, Memory < 70% • Alert: CPU > 80% or Memory > 85% SLI/SLO DEFINITION Service Level Indicator: Successful requests (HTTP 2xx) / Total requests • Good: response < 200ms AND status 2xx • Bad: timeout OR 5xx error • Window: 30-day rolling Service Level Objective: 99.5% (99.5% of requests succeed) → Budget: 3.6 minutes of downtime per 30 days → Used this month: 1.2 minutes (67% of budget remaining) LOG LEVELS & RETENTION • ERROR: Failed payment attempt, database timeout, circuit breaker open → 30 days • WARN: Retry attempt, slow query (>500ms) → 7 days • INFO: Request received, order processed, payment confirmed → 3 days • DEBUG: SQL queries, stack traces → 1 day (dev only) TRACES • Instrumentation: OpenTelemetry SDK • Sample rate: 10% (high-volume), 100% for errors • Propagate trace IDs across services (HTTP headers) • Key spans: database call, payment gateway call, response ALERTS (Escalation: Slack → PagerDuty if p1) Severity: P1 (immediate) • Error rate > 1% for 1 minute • Latency p95 > 500ms for 3 minutes → Action: Page on-call engineer Severity: P2 (investigate within 1 hour) • Error rate > 0.5% for 5 minutes • Memory usage > 85% → Action: Slack alert to team Severity: P3 (track for next sprint) • Database connection pool nearing capacity • Warn logs > 10 per second → Action: Logged for retro review
About this skill
name: observability-designer description: Use when Design production-ready observability strategies combining metrics, logs, and traces.
Observability Designer
Design production-ready observability strategies combining metrics, logs, and traces. Includes SLI/SLO design, golden-signals monitoring, alert optimization. Use when adding observability to a new service, refactoring alerting that is too noisy, or designing an SLO program before scaling production load.
What you get
- Public GitHub repo (alirezarezvani/claude-skills)
- the observability-designer skill folder with SKILL.md. Part of a 337-skill / 30-agent / 70-command install.
Customize your output
- Fork the repo and adapt the skill's instructions and references to your workflow.
Example output
Activates automatically when your request matches Observability Designer; chains with the other skills, agents, and commands in the collection.
Best for
Creators, builders, and teams using Claude Code.
SKILL.md preview
---
name: observability-designer
description: Design production-ready observability strategies combining metrics, logs, and traces, including golden-signals monitoring, SLI/SLO design, and alert-noise reduction.
version: 1.0.0
category: Development / Engineering
author: AgentVolt
license: proprietary
tags:
- development
- engineering
---
# Observability Designer
Design production-ready observability strategies combining metrics, logs, and traces, including golden-signals monitoring, SLI/SLO design, and alert-noise reduction.
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