Agent-Skills.md

Agent Skills: QA Observability and Performance Engineering

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

UncategorizedID: vasilyu1983/ai-agents-public/qa-observability

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vasilyu1983/ai-agents-public
vasilyu1983License: MIT
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frameworks/shared-skills/skills/qa-observability/SKILL.md

Skill Metadata

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.