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
Perfetto is a platform for system-level performance tracing and analysis on Linux and Android. It combines a high-throughput trace recorder, a SQL-based query engine, and a browser-based visualizer into a single toolchain. The platform covers CPU scheduling and call-stack profiling, native and Java heap memory allocation tracking, GPU and graphics events, and system-wide counters such as CPU frequency and power consumption. The architecture decouples trace recording from offline analysis, using a compact protobuf format for event encoding and columnar storage for efficient SQL queries. The we
This project is a performance analysis suite for Python applications, providing tools for both application-wide profiling and granular code benchmarking. It enables developers to identify execution bottlenecks and measure function call frequency through a combination of deterministic tracing and statistical sampling methods. The tool distinguishes itself by offering a terminal-based interactive interface that allows for real-time navigation and filtering of complex call stacks. It supports non-intrusive data collection through signal-based process interception, enabling performance monitoring
Pyroscope is a continuous profiling platform designed to collect, store, and visualize application performance data. It functions as an application performance management suite that tracks historical resource usage to identify bottlenecks and detect performance regressions over time. The platform distinguishes itself through its use of kernel-level instrumentation and dynamic runtime hooks, which allow for performance monitoring without requiring manual code modifications or application restarts. It employs a sidecar agent architecture to offload telemetry processing, utilizing delta-encoded
The diagnostics project provides a cross-platform diagnostic infrastructure and command-line toolkit for monitoring runtime performance, analyzing memory dumps, and troubleshooting applications. It features a custom inter-process communication protocol for command and telemetry exchange across platforms, a low-overhead event pipe mechanism for streaming real-time diagnostic events and performance counters from running processes, and automated remote symbol resolution for…
dotnet/diagnostics 的主要功能包括:.NET Command Line Interfaces, Debug Symbol Resolvers, Runtime Debugging, Memory Dump Parsers, Java Heap Dump Capturers, Debugger Extensions, Runtime Diagnostics, Application Performance Monitoring。
dotnet/diagnostics 的开源替代品包括: nswbmw/node-in-debugging — This project is a comprehensive technical guide and diagnostic manual for analyzing memory, performance, and… google/perfetto — Perfetto is a platform for system-level performance tracing and analysis on Linux and Android. It combines a… what-studio/profiling — This project is a performance analysis suite for Python applications, providing tools for both application-wide… grafana/pyroscope — Pyroscope is a continuous profiling platform designed to collect, store, and visualize application performance data.… mstange/samply — Samply is a cross-platform CPU sampling profiler and performance analysis utility. It consists of a command-line tool… ufrisk/memprocfs — MemProcFS is a volatile memory analysis tool and cross-platform memory acquisition system. It functions as a memory…