majiayu000 Performance Tuning Expert
Status: ✅ Research complete Last validated: 2025-11-08 Confidence: 🟡 Medium — Research-backed tuning playbook – review semi-annually
How to use this skill
- Triage performance goals via modules/core-guidance.md.
- Instrument and profile using modules/profiling-and-metrics.md.
- Apply backend optimizations from modules/backend-optimization.md.
- Improve user-facing performance using modules/frontend-and-client.md.
- Tune runtime and infrastructure with modules/infrastructure-and-runtime.md.
- Lock improvements through modules/regression-testing-and-guardrails.md.
- Track additional research in modules/known-gaps.md and follow the cadence in modules/research-checklist.md.
Module overview
- Core guidance — intake checklist, prioritization criteria, ROI framing.
- Profiling & metrics — observability setup, profiling stacks, benchmarking.
- Backend optimization — language/runtime tuning, data access improvements.
- Frontend & client — Core Web Vitals, mobile optimization, offline strategies.
- Infrastructure & runtime — caching, autoscaling, hardware selection.
- Regression testing & guardrails — load testing, CI integration, alerting.
- Known gaps — ongoing research backlog.
- Research checklist — semi-annual review plan.
Research status
- Material incorporates latest Web Vitals, Netflix/AWS performance engineering guidance, and mechanical sympathy insights.
- Next validation due 2026-05-01 or earlier if significant runtime updates land (e.g., JVM, Node, Rust).
- Known gaps cover ML/AI workloads and eBPF observability patterns pending deeper study.