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 is a suite of performance tools designed for sampling Java runtimes, tracking memory allocations, and monitoring hardware counters. It functions as a low-overhead sampling profiler for Java applications, collecting stack traces and memory allocation data without safepoint bias. The project provides specialized utilities for generating interactive flame graphs to visualize execution hotspots in a web browser. It includes a hardware performance counter monitor to track low-level system events such as cache misses and page faults. The toolset covers several diagnostic domains, in

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 ist ein Profiling-Tool zur Erfassung des Ausführungszustands von Go-Programmen und zur Transformation binärer Rohdaten in visuelle Repräsentationen der Programm-Performance. Es fungiert als Flame-Graph-Profiler und Performance-Visualisierungstool, das teure Codepfade durch die Sammlung von CPU- und Memory-Stack-Traces identifiziert. Das Tool verfügt über einen netzwerkfähigen Remote-Prozess-Profiler, der sich mit Endpunkten verbindet, um Ausführungsprofile von Go-Binaries zu erfassen und zu exportieren. Es nutzt stochastisches Profiling, um Ausführungsdaten in Call-Graphen zu synthetisieren, was die Identifizierung von Engpässen in laufenden Anwendungen ermöglicht. Das Projekt deckt die gesamte Pipeline der Profiling-Datenerfassung ab, von der Stack-Trace-Stichprobenentnahme und Remote-Profil-Akquise bis zur Call-Graph-Synthese. Diese Workflows gipfeln in der Generierung SVG-basierter Flame-Graphen, die Funktionstiefe und Ausführungshäufigkeit visualisieren.