qa-observability

name	qa-observability
description	Implement OpenTelemetry logs/metrics/traces, SLI/SLO gates, burn-rate alerts, and APM integrations. Use when adding or validating observability.

QA Observability and Performance Engineering

Use telemetry (logs, metrics, traces, profiles) as a QA signal and a debugging substrate.

Core references (see data/sources.json): OpenTelemetry, W3C Trace Context, and SLO practices (Google SRE).

Quick Start (Default)

If key context is missing, ask for: critical user journeys, service/dependency inventory, environments (local/staging/prod), current telemetry stack, and current SLO/SLA commitments (if any).

1. Establish the minimum bar: correlation IDs + structured logs + traces + golden metrics (latency, traffic, errors, saturation).
2. Verify propagation: confirm traceparent (and your request ID) flow across boundaries end-to-end.
3. Make failures diagnosable: every test failure captures a trace link (or trace ID) plus the correlated logs.
4. Define SLIs/SLOs and error budget policy; wire burn-rate alerts (prefer multi-window burn rates).
5. Produce artifacts: a readiness checklist plus an SLO definition and alert rules (use assets/checklists/template-observability-readiness-checklist.md and assets/monitoring/slo/*).

Default QA stance

• Treat telemetry as part of acceptance criteria (especially for integration/E2E tests).
• Require correlation: request_id + trace_id (traceparent) across boundaries.
• Prefer SLO-based release gating and burn-rate alerting over raw infra thresholds.
• Budget overhead: sampling, cardinality, retention, and cost are quality constraints.
• Redact PII/secrets by default (logs and attributes).

Core workflows

1. Establish the minimum bar (logs + metrics + traces + correlation).
2. Instrument with OpenTelemetry (auto-instrument first, then add manual spans for key paths).
3. Verify context propagation across service boundaries (traceparent in/out).
4. Define SLIs/SLOs and error budget policy; wire burn-rate alerts.
5. Make failures diagnosable: capture a trace link + key logs on every test failure.
6. Profile and load test only after telemetry is reliable; validate against baselines.

Quick reference

Task	Recommended default	Notes
Tracing	OpenTelemetry + Jaeger/Tempo	Prefer OTLP exporters via Collector when possible
Metrics	Prometheus + Grafana	Use histograms for latency; watch cardinality
Logging	Structured JSON + correlation IDs	Never log secrets/PII; redact aggressively
Reliability gates	SLOs + error budgets + burn-rate alerts	Gate releases on sustained burn/regressions
Performance	Profiling + load tests + budgets	Add continuous profiling for intermittent issues
Zero-code visibility	eBPF (OpenTelemetry zero-code) + continuous profiling (Parca/Pyroscope)	Use when code changes are not feasible

Navigation

Open these guides when needed:

If the user needs...	Read	Also use
A minimal, production-ready baseline	references/core-observability-patterns.md	assets/checklists/template-observability-readiness-checklist.md
Node/Python instrumentation setup	references/opentelemetry-best-practices.md	assets/opentelemetry/nodejs/opentelemetry-nodejs-setup.md, assets/opentelemetry/python/opentelemetry-python-setup.md
Working trace propagation across services	references/distributed-tracing-patterns.md	assets/checklists/template-observability-readiness-checklist.md
SLOs, burn-rate alerts, and release gates	references/slo-design-guide.md	assets/monitoring/slo/slo-definition.yaml, assets/monitoring/slo/prometheus-alert-rules.yaml
Profiling/load testing with evidence	references/performance-profiling-guide.md	assets/load-testing/load-testing-k6.js, assets/load-testing/template-load-test-artillery.yaml
A maturity model and roadmap	references/observability-maturity-model.md	assets/checklists/template-observability-readiness-checklist.md
What to avoid and how to fix it	references/anti-patterns-best-practices.md	assets/checklists/template-observability-readiness-checklist.md
Alert design and fatigue reduction	references/alerting-strategies.md	assets/monitoring/slo/prometheus-alert-rules.yaml
Dashboard hierarchy and layout	references/dashboard-design-patterns.md	assets/monitoring/grafana/template-grafana-dashboard-observability.json
Structured logging and cost control	references/log-aggregation-patterns.md	assets/observability/template-logging-setup.md

Implementation guides (deep dives):

• references/core-observability-patterns.md
• references/opentelemetry-best-practices.md
• references/distributed-tracing-patterns.md
• references/slo-design-guide.md
• references/performance-profiling-guide.md
• references/observability-maturity-model.md
• references/anti-patterns-best-practices.md
• references/alerting-strategies.md
• references/dashboard-design-patterns.md
• references/log-aggregation-patterns.md

Templates (copy/paste):

• assets/checklists/template-observability-readiness-checklist.md
• assets/opentelemetry/nodejs/opentelemetry-nodejs-setup.md
• assets/opentelemetry/python/opentelemetry-python-setup.md
• assets/monitoring/slo/slo-definition.yaml
• assets/monitoring/slo/prometheus-alert-rules.yaml
• assets/monitoring/grafana/grafana-dashboard-slo.json
• assets/monitoring/grafana/template-grafana-dashboard-observability.json
• assets/load-testing/load-testing-k6.js
• assets/load-testing/template-load-test-artillery.yaml
• assets/performance/frontend/template-lighthouse-ci.json
• assets/performance/backend/template-nodejs-profiling-config.js

Curated sources:

• data/sources.json

Scope boundaries (handoffs)

• Pure infrastructure monitoring (Kubernetes, Docker, CI/CD): ../ops-devops-platform/SKILL.md
• Database query optimization (SQL tuning, indexing): ../data-sql-optimization/SKILL.md
• Application-level debugging (stack traces, breakpoints): ../qa-debugging/SKILL.md
• Test strategy design (coverage, test pyramids): ../qa-testing-strategy/SKILL.md
• Resilience patterns (retries, circuit breakers): ../qa-resilience/SKILL.md
• Architecture decisions (microservices, event-driven): ../software-architecture-design/SKILL.md

Tool selection notes (2026)

• Default to OpenTelemetry + OTLP + Collector where possible.
• Prefer burn-rate alerting against SLOs over alerting on raw infra metrics.
• Treat sampling, cardinality, and retention as part of quality (not an afterthought).
• When asked to pick vendors/tools, start from data/sources.json and validate time-sensitive claims with current docs/releases if the environment allows it.

Fact-Checking

• Use web search/web fetch to verify current external facts, versions, pricing, deadlines, regulations, or platform behavior before final answers.
• Prefer primary sources; report source links and dates for volatile information.
• If web access is unavailable, state the limitation and mark guidance as unverified.