Skill182 repo starsupdated 5d ago
prd-v08-monitoring-setup
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Install in Claude Code
Copygit clone --depth 1 https://github.com/mattgierhart/PRD-driven-context-engineering /tmp/prd-v08-monitoring-setup && cp -r /tmp/prd-v08-monitoring-setup/.claude/skills/prd-v08-monitoring-setup ~/.claude/skills/prd-v08-monitoring-setupThen start a new Claude Code session; the skill loads automatically.
Definition
SKILL.md
# Monitoring Setup Position in workflow: v0.8 Runbook Creation → **v0.8 Monitoring Setup** → v0.9 GTM Strategy ## Execution Mode Default is **standard**. See [`.claude/rules/08-skill-execution-modes.md`](../../rules/08-skill-execution-modes.md) for selection logic. | Mode | What this skill produces | |------|--------------------------| | **quick** | RED metrics on critical path only; 3–5 alerts linked to RUN-; single overview dashboard | | **standard** | RED + USE coverage; SLOs for tier-1 services; full alert routing to RUN-; dashboards by audience | | **deep** | Layered coverage (RED + USE + business + UX); multi-tier SLOs with error budgets; baseline calibration from staging; escalation routing | ## Consumes This skill requires prior work from v0.8 Runbook Creation and earlier stages: - **RUN-\* runbook entries** (from v0.8 Runbook Creation) — Incident response runbooks define alerting scenarios; critical alerts must link to RUN- procedures - **DEP-\* deployment entries** (from v0.8 Release Planning) — DEP- rollback thresholds and post-deploy validation steps inform MON- alert conditions and SLO targets - **API-\* endpoint contracts** (from v0.6 Technical Specification) — Define baseline latency, throughput, and error rates for application-layer metrics - **KPI-\* metrics** (from v0.3 Outcome Definition and v0.9 Launch Metrics) — Business metrics (signups, conversions, retention) inform dashboard design and business layer monitoring - **ARC-\* architecture decisions** (from v0.6 Architecture Design) — System structure determines which components to monitor (monolith has different metrics than distributed services) - **TECH-\* technology stack** (from v0.5 Technical Stack Selection) — Technology choices (database, cloud provider, APM tools) determine available metrics and monitoring tools This skill assumes DEP- and RUN- entries are complete with thresholds, rollback conditions, and incident procedures defined. ## Produces This skill creates/updates: - **MON-\* entries** (monitoring specifications, metric/alert/dashboard/SLO types) — Concrete monitoring rules with thresholds, alert conditions, dashboards, SLO definitions, linked to RUN- procedures - **Alert routing configuration** — Mapping of MON- alerts to notification channels and teams; links alerts to RUN- incident procedures - **Observability baseline** — Metrics gathered from staging/production, establishing normal operating ranges for alert thresholds All MON- entries are **operational monitoring specifications**, not confidence-based. They are: - **Measurable** (every metric has a source, unit, and aggregation method) - **Actionable** (every alert has a RUN- procedure; no orphaned alerts) - **Thresholded** (critical/warning severity with specific numeric conditions) - **Dashboarded** (MON- dashboard entries provide visibility to operators and stakeholders) - **SLO-backed** (SLO entries tie monitoring to product commitments) Example MON- entries: ```markdown MON-001: API Request Latency (p95) Type: Metric Layer: Application Owner: Backend Team Name: api.request.latency.p95 Description: 95th percentile response time for all API endpoints (from API-001–020) Unit: ms Source: Application APM (Datadog custom instrumentation) Aggregation: p95 over 5-minute window Retention: 90 days Linked IDs: API-001 to API-020, DEP-004 (baseline from staging) --- MON-002: High Latency Alert (Warning) Type: Alert Layer: Application Owner: Backend Team Metric: MON-001 (api.request.latency.p95) Condition: >500ms (from DEP-002 baseline) Window: 5 minutes Severity: Warning Runbook: RUN-001 (Performance Degradation Investigation) Notification: - Channel: Slack #backend-alerts - Recipients: Backend on-call, team notified during business hours Silencing: During scheduled maintenance windows (DEP-004 notifications) Linked IDs: MON-001, RUN-001, DEP-002 --- MON-003: Critical Latency Alert Type: Alert Layer: Application Owner: Backend Team Metric: MON-001 (api.request.latency.p95) Condition: >2000ms (SLA breach, from KPI-001 target) Window: 2 minutes Severity: Critical Runbook: RUN-001 (Performance Degradation Investigation) Notification: - Channel: PagerDuty (wake on-call) - Recipients: Backend on-call, Tech Lead, escalate if not acknowledged in 5 min Silencing: None (critical alerts never silenced) Linked IDs: MON-001, RUN-001, KPI-001 --- MON-004: API Availability SLO Type: SLO Layer: Application Owner: Platform Team Objective: API endpoints return non-5xx response Target: 99.9% uptime (from DEP-002 / KPI-001) Window: Rolling 30 days Error Budget: 43.2 minutes/month Alerting: - 50% error budget consumed → Warning to engineering (slow-burn alert) - 75% error budget consumed → Critical, freeze non-essential deploys - 100% error budget consumed → Post-incident review required (RUN-008 procedure) Linked IDs: API-001–020, DEP-003 (rollback triggers), RUN-008 (incident review) --- MON-005: System Health Dashboard Type: Dashboard Layer: Infrastructure + Application Owner: Platform Team Purpose: Quick health check for on-call engineers (run from RUN-002, RUN-001) Audience: On-call engineers, engineering leadership, ops team Panels: - API Request Rate (last 1h): Should be steady or increasing - API Latency (p50, p95, p99): Watch for p95/p99 creeping up - Error Rate by Endpoint: Any 5xx > 0 is concerning - Active Critical Alerts: Should be none - Database Connection Pool (from MON-006): Trending toward threshold - CPU/Memory by Service: Identify resource exhaustion - Deployment Status: Current version, time of last deploy Refresh: 30 seconds Linked IDs: MON-001, MON-002, MON-003, MON-006, DEP-001, RUN-001/002 --- MON-006: Database Connection Pool Utilization Type: Metric Layer: Infrastructure Owner: Database Team Name: db.connection_pool.utilized_percent Description: Percentage of available connections in use (from DEP-001 pool size) Unit: percentage Source: Database monitoring (RDS Enhanced Monitor