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 هي مجموعة من أدوات الأداء مصممة لأخذ عينات من بيئات تشغيل Java، وتتبع تخصيصات الذاكرة، ومراقبة عدادات الأجهزة. تعمل كمحلل أخذ عينات منخفض التكلفة (low-overhead) لتطبيقات Java، حيث تجمع تتبعات المكدس وبيانات تخصيص الذاكرة دون انحياز لنقاط الأمان (safepoint). يوفر المشروع أدوات متخصصة لتوليد رسوم بيانية تفاعلية للهب (flame graphs) لتصور نقاط التنفيذ الساخنة في متصفح الويب. يتضمن مراقباً لعدادات أداء الأجهزة لتتبع أحداث النظام منخفضة المستوى مثل أخطاء ذاكرة التخزين المؤقت وأخطاء الصفحات. تغطي مجموعة الأدوات عدة مجالات تشخيصية، بما في ذلك تحليل استخدام وحدة المعالجة المركزية لتحديد الأساليب الساخنة، وتتبع تخصيص الذاكرة للتسريبات في الكومة (heap) والذاكرة الأصلية، وتحليل تنافس الخيوط (thread contention) للكشف عن اختناقات المزامنة عبر طبقات النظام المختلفة.

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 is a profiling tool for capturing the execution state of Go programs and transforming raw binary data into visual representations of program performance. It functions as a flame graph profiler and performance visualization utility that identifies expensive code paths through the collection of CPU and memory stack traces. The tool features a network-capable remote process profiler that connects to endpoints to capture and export execution profiles from Go binaries. It utilizes stochastic profiling to synthesize execution data into call graphs, allowing for the identification of bottle