Awesome GitHub RepositoriesFlame Graph Generators

FlameGraph is a performance profiling and visualization toolkit designed to identify bottlenecks in software execution. It functions as a processing engine that transforms raw stack trace samples into interactive, hierarchical diagrams. By representing aggregated execution frequency as nested rectangles, the tool allows developers to visualize hot code paths and analyze system behavior across both kernel and user-space environments. The project distinguishes itself through its ability to perform differential profile analysis, which highlights performance regressions or improvements by compari

Async-profiler 是一套性能工具，旨在对 Java 运行时进行采样、跟踪内存分配并监控硬件计数器。它充当 Java 应用程序的低开销采样分析器，在没有安全点偏差的情况下收集堆栈跟踪和内存分配数据。 该项目提供用于生成交互式火焰图的专用实用程序，以在 Web 浏览器中可视化执行热点。它包括一个硬件性能计数器监视器，用于跟踪低级系统事件，如缓存未命中和页面错误。 该工具集涵盖了多个诊断领域，包括用于识别热点方法的 CPU 使用率分析、用于堆和原生内存泄漏的内存分配跟踪，以及用于揭示不同系统层之间同步瓶颈的线程争用分析。

This project is a comprehensive technical guide and diagnostic manual for analyzing memory, performance, and asynchronous behavior within Node.js applications. It provides detailed methods for asynchronous tracing, memory diagnostics, and performance analysis to resolve runtime errors and execution bottlenecks. The resource distinguishes itself by covering advanced diagnostic workflows, including the use of flame graphs for CPU profiling, the capture and comparison of heap snapshots for memory leak detection, and the mapping of asynchronous call stacks. It also provides technical guidance on

Parca is an always-on continuous profiling platform that captures CPU and memory usage from running applications without any code modifications. It uses eBPF kernel-level tracing to automatically discover and sample stack traces across infrastructure, and provides a web-based flame graph dashboard for interactive performance analysis. Its label-based query engine lets users slice and aggregate profiling data across dimensions such as service, container, or region, using a Prometheus-style selector syntax. Unlike basic profilers, Parca stores profile samples in a columnar format using Apache A

go-torch 是一个性能分析工具，用于捕获 Go 程序的执行状态并将原始二进制数据转换为程序性能的可视化表示。它作为火焰图分析器和性能可视化工具，通过收集 CPU 和内存堆栈跟踪来识别昂贵的代码路径。 该工具具有支持网络的远程进程分析器，可连接到端点以从 Go 二进制文件中捕获和导出执行配置文件。它利用随机分析将执行数据合成到调用图中，从而识别运行中应用程序的瓶颈。 该项目涵盖了从堆栈跟踪采样和远程配置文件获取到调用图合成的完整分析数据收集流水线。这些工作流最终生成基于 SVG 的火焰图，可视化函数深度和执行频率。