m10-performance

Analyze Rust performance bottlenecks using cargo bench, flamegraph, and criterion.

1.4k|110|Updated Jan 17, 2026
One-click install
npx skills add https://github.com/actionbook/rust-skills --skill m10-performance-actionbook
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: m10-performance
Source: https://github.com/actionbook/rust-skills/tree/main/skills/m10-performance
Command: npx skills add https://github.com/actionbook/rust-skills --skill m10-performance-actionbook

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps Rust developers locate and fix performance bottlenecks by guiding a disciplined workflow: measure first, identify hotspots, and apply targeted optimizations to reduce allocations, improve cache locality, and enhance parallelism.

Core Features & Use Cases

  • Profiling and Benchmarking: Use cargo bench, flamegraph, and criterion to quantify performance.
  • Memory and Cache Optimizations: Techniques to reduce allocations and improve data locality.
  • Parallelism and Concurrency: Apply rayon or multithreading to scale CPU-bound workloads.
  • Use Case: You have a Rust service that handles high-throughput data; this skill helps you find slow paths and propose fixes with minimal regressions.

Quick Start

Run cargo bench to baseline performance, install flamegraph, and generate a visual flamegraph for hotspots.

Frequently Asked Questions about m10-performance

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find performance bottlenecks in my Rust project?▼

To find Rust performance bottlenecks, you should measure first using cargo bench and generate a flamegraph to identify hotspots before applying targeted optimizations like reducing allocations or improving cache locality.

What is the best way to benchmark Rust code for high-throughput workloads?▼

The best way to benchmark Rust code is using criterion with cargo bench to establish measurable baselines, which helps quantify performance and ensure optimizations yield repeatable results without regressions.

Can I use flamegraph to analyze memory and cache locality issues in Rust?▼

Yes, flamegraph helps analyze CPU hotspots, while specific memory and cache optimizations in Rust involve techniques to reduce allocations and improve data locality based on those profiling measurements.

How do I scale CPU-bound Rust workloads with parallelism?▼

To scale CPU-bound Rust workloads, you can apply parallelism and concurrency using rayon or multithreading after establishing a baseline with cargo bench to verify the performance improvements.

Do I need measurable baselines before optimizing my Rust binary?▼

Yes, measurable baselines are required before optimizing a Rust binary to ensure a disciplined workflow where you pinpoint hotspots first and apply targeted optimizations that yield repeatable results.

When should I not use flamegraph for Rust profiling?▼

Flamegraph may be limited if you lack measurable baselines from cargo bench, as profiling requires established toolchains and quantifiable data to accurately identify hotspots and apply targeted optimizations.