01
Reproduce
Freeze representative inputs, traffic shape, hardware, and success metrics.
All services
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Rust Performance Optimization for Production Systems
Profile and improve Rust services using measured CPU, memory, allocation, latency, and throughput evidence—not speculative micro-optimizations.
Target outcome
A ranked performance model, reproducible benchmarks, narrow code changes, and proof showing which constraint moved and which did not.
Good fit when
- Rust APIs with high p95 or p99 latency
- Services whose memory or infrastructure cost has grown faster than traffic
- Async systems with lock contention, backpressure, or task saturation
- Teams that need a defensible baseline before a rewrite
What you receive
- Workload and benchmark definition
- CPU, allocation, async-runtime, and I/O profile
- Ranked bottleneck report tied to source locations
- Reviewed patches with before-and-after measurements
- Regression checks suitable for CI
How the work runs
02
Profile
Measure hot paths, allocations, contention, queueing, and I/O wait before editing.
03
Change narrowly
Optimize the responsible layer and keep architecture changes reversible.
04
Prove
Run identical workloads, compare variance, and document remaining limits.