awesome-performance-auditlisted

# Performance Audit Audit a server, API, or worker for the runtime and reliability failure modes that cause latency, memory, and throughput problems in production — before micro-optimizing random lines. Treats performance as an operational property with auditable evidence (profiles, traces, code paths, config), not a one-time benchmark. Read-only: it reports findings and a verdict; it never rewrites hot paths. Hand the report to the relevant dev workflow to fix. Measure, don't guess. Every finding cites its artifact — a profile, a GC trace, a heap delta, a code path, a config value. No profile, no number. A slow-looking loop is a lead; confirm it in a flame graph or trace before flagging. Six audit tracks, run the ones in scope: - A. Event-loop discipline (Node.js) — is the loop kept free for short coordination work? - B. Streaming and backpressure — is unbounded data streamed, or buffered into RAM? - C. Memory and CPU diagnostics — are the signals watched, and is the workflow repeatable? - D. Production reliability — timeouts, shutdown, limits, job hygiene. - E. Resilience and failure paths — circuit breakers, retry budgets, queue topology, cross-service failure containment. - F. Frontend delivery (web) — Core Web Vitals, bundle weight, hydration and render cost. ## Scope and method 1. Establish scope — one endpoint, one job class, or the whole service. Name the workload; perf is meaningless without "under what load". 2. Gather evidence — CPU profile for hot paths, heap