QA Observability and Performance Engineering

data/sources.json

Quick Start (Default)

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

Navigation

references/core-observability-patterns.md

assets/checklists/template-observability-readiness-checklist.md

references/opentelemetry-best-practices.md

assets/opentelemetry/nodejs/opentelemetry-nodejs-setup.md

assets/opentelemetry/python/opentelemetry-python-setup.md

references/distributed-tracing-patterns.md

assets/checklists/template-observability-readiness-checklist.md

references/slo-design-guide.md

assets/monitoring/slo/slo-definition.yaml

assets/monitoring/slo/prometheus-alert-rules.yaml

references/performance-profiling-guide.md

assets/load-testing/load-testing-k6.js

assets/load-testing/template-load-test-artillery.yaml

references/observability-maturity-model.md

assets/checklists/template-observability-readiness-checklist.md

references/anti-patterns-best-practices.md

assets/checklists/template-observability-readiness-checklist.md

references/alerting-strategies.md

assets/monitoring/slo/prometheus-alert-rules.yaml

references/dashboard-design-patterns.md

assets/monitoring/grafana/template-grafana-dashboard-observability.json

references/log-aggregation-patterns.md

assets/observability/template-logging-setup.md

• 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

• 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

• 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.