performance-engineering 开源项目推荐（423 个）

bojieli /ai-infra-book

《深入理解 AI Infra：量化分析与系统设计》（李博杰 著）开源书稿：从硬件约束和模型架构出发，量化推导 LLM 推理与训练系统设计。含全书正文、PDF、配套计算工具与实验

plasma-umass /coz

Coz: Causal Profiling

SciML /SciMLBook

并行计算和科学机器学习（SciML）：方法和应用（MIT 18.337J/6.338J）

RRZE-HPC /likwid

性能监控与基准测试套件

usamahz /cpu-performance-engineering

CPU 性能工程阅读路径，从一条指令到生产推理。仅采用一手资料，每节都配有可运行基准测试。

aviatesk /JET.jl

A code analyzer for Julia. No need for additional type annotations.

grafana /k6-operator

An operator for running distributed k6 tests.

morluto /flameox

Runtime evidence that helps agents trace, profile, and burn down hotspots in application and native code, GPU kernels, and inference stacks.

microsoft /MLOS

MLOS is a project to enable autotuning for systems.

aliesbelik /how-they-load

A curated collection of publicly available resources on how companies around the world perform load testing

portyu9 /k6-performance-testing-framework

Production-grade k6 performance testing framework for smoke, load, stress, and soak tests with GitHub Actions, Docker, thresholds, custom metrics, safety guardrails, and machine-readable results.

Alone-King /verso-optimized-takehome-solution

Ultra-Fast Python Solutions: 110x Speed Optimization Guide 2026

YahooArchive /daytona

An application-agnostic framework for automated performance testing and analysis.

JuliaPerf /LIKWID.jl

Julia wrapper for the performance monitoring and benchmarking suite LIKWID.

apiv /fuego

A component render time benchmarking suite for React

QAInsights /Learn-Locust-Series

🦗 Learn Locust from scratch 🐍

0franco /image-auditor

🔎 Rust TUI that finds & AI-fixes Lighthouse image issues (CLS, lazy loading, WebP, srcset) across your entire codebase in seconds.

be-next /awesome-performance-engineering

A curated, opinionated collection of tools and resources dedicated to Performance Engineering, covering both Observability and Performance Testing.

QAInsights /Learn-k6-Series

Learn k6 Series

QAInsights /JEval

⚡ JEval helps you to evaluate your JMeter test plan and provides recommendation before you start your performance testing. All contributions welcome 🙏.