awesome-performance-audit

# 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. Four audit tracks, run the ones in scope: - **A. Event-loop discipline** — 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. ## 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 snapshots for growth, GC traces for pressure, request/job correlation to connect symptoms to workloads. Read code paths and config (timeouts, body limits, pool sizes). Persist raw pulls (`ra...