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Samply is a cross-platform CPU sampling profiler and performance analysis utility. It consists of a command-line tool for recording process stack traces at regular intervals and a visual interface for analyzing the resulting execution data.
The main features of mstange/samply are: Application Performance Profiling, Debug Symbol Resolvers, CPU Profilers, Native Stack Unwinders, CPU Execution Analysis, Symbol Resolution Engines, Call Stack Samplers, Execution Stack Samplers.
Open-source alternatives to mstange/samply include: uber-archive/go-torch — go-torch is a profiling tool for capturing the execution state of Go programs and transforming raw binary data into… nswbmw/node-in-debugging — This project is a comprehensive technical guide and diagnostic manual for analyzing memory, performance, and… microsoft/perfview — PerfView is a set of integrated profiling and tracing tools built on Windows Event Tracing for Windows (ETW), designed… kdab/hotspot — Hotspot is a graphical user interface for analyzing and visualizing performance data captured by the Linux perf tool.… bloomberg/memray — Memray is a memory profiler for Python that tracks heap allocations in both Python code and native C or C++… dotnet/diagnostics — The diagnostics project provides a cross-platform diagnostic infrastructure and command-line toolkit for monitoring…
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
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
PerfView is a set of integrated profiling and tracing tools built on Windows Event Tracing for Windows (ETW), designed to diagnose CPU, memory, and ETW-based performance issues in .NET applications. It captures ETW events to analyze runtime behavior, CPU usage, and memory allocations, serving as a .NET performance profiler that measures both CPU time and garbage collection events. The tool distinguishes itself with a diff comparison engine that compares two performance traces side-by-side to highlight changes in method costs and event rates. It renders profiled call stacks as flame graphs whe
Hotspot is a graphical user interface for analyzing and visualizing performance data captured by the Linux perf tool. It functions as a performance profiling visualizer and assembly-level profiler that maps performance costs to specific instructions synchronized with original source code. The project distinguishes itself through a remote symbol resolver that maps performance data from embedded targets to local host debug symbols and sysroots. It also includes a specialized off-CPU analysis tool designed to identify thread wait times and I/O blocks using kernel scheduler tracepoints. The tool