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dotnet/diagnostics

0
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1,319 stars·399 forks·C++·MIT·19 views

Diagnostics

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 stack trace analysis.

The platform includes native debugger extensions that integrate with standard debuggers to inspect managed code, threads, and internal runtime structures. It supports capturing lightweight managed heap memory graphs and process memory dumps by triggering garbage collection and object root stream capture. Additional capabilities include early source and symbol breakpoints, child process startup tracing, process discovery, and performance metric export in JSON or CSV formats.

Features

  • .NET Command Line Interfaces - Provides a command-line toolkit and library collection for monitoring performance and troubleshooting applications.
  • Debug Symbol Resolvers - Automatically downloads and resolves debugging symbols from remote symbol servers during stack trace analysis.
  • Runtime Debugging - Extends native debuggers to inspect managed code, threads, and internal structures in active runtimes.
  • Memory Dump Parsers - Captures and inspects process memory states using dedicated parsing utilities to diagnose runtime crashes.
  • Java Heap Dump Capturers - Gathers lightweight managed heap memory graphs by triggering garbage collection and capturing object root streams.
  • Debugger Extensions - Extends standard native debuggers with specialized plugins to inspect managed code and runtime structures.
  • Runtime Diagnostics - Provides diagnostic tools for inspecting internal state, threads, and runtime structures of execution engines.
  • Application Performance Monitoring - Tracks live performance counters and event streams from a running application to observe resource usage.
  • Heap Snapshot Capturers - Captures managed heap memory snapshots and process dumps by triggering garbage collection and object root stream capture.
  • Low-Overhead Runtime Event Streaming - Streams diagnostic events and performance counters in real time from running processes using a low-overhead circular buffer.
  • Runtime Memory Explorers - Captures and inspects process memory dumps and live heap snapshots to diagnose memory leaks.
  • Application Performance Profiling - Collects real-time diagnostic trace events and performance profiles to identify execution bottlenecks.
  • Performance Tracing Platforms - Collects real-time events and generates performance traces from running processes to identify execution bottlenecks.
  • Runtime Diagnostic Tracing - Captures diagnostic trace events from running applications across platforms without requiring a native profiler.
  • Symbolic Breakpoints - Establishes breakpoints on managed methods or source file line numbers early in the debugging session.
  • Debugging Symbol Managers - Connects to remote symbol servers or local directories to automatically download and resolve debugging symbols.
  • Performance Counter Sampling - Collects live performance counter values and metrics from target processes for lightweight health monitoring.
  • Inter-Process Communication - Communicates with target runtime processes across platforms using a custom inter-process communication protocol.
  • Real-Time Application Performance Monitors - Collects real-time event traces from running applications to identify performance bottlenecks and track execution.
  • Process Lifecycle Tracing - Launches application executables and immediately collects diagnostic traces from runtime startup.
  • Performance Monitoring - Collects runtime performance counter values over time for lightweight health monitoring in production.
  • Performance Metric Exports - Collects periodic counter data from a running process and exports it in JSON or CSV formats.

Star history

Star history chart for dotnet/diagnosticsStar history chart for dotnet/diagnostics

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with Diagnostics

These projects share indexed features with Diagnostics. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • nswbmw/node-in-debuggingnswbmw avatar

    nswbmw/node-in-debugging

    6,457View on GitHub↗

    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

    debugdebuggingguide
    View on GitHub↗6,457
  • google/perfettogoogle avatar

    google/perfetto

    5,558View on GitHub↗

    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

    C++
    View on GitHub↗5,558
  • what-studio/profilingwhat-studio avatar

    what-studio/profiling

    2,937View on GitHub↗

    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

    Pythondebuglive-profilingprofiling
    View on GitHub↗2,937
  • grafana/pyroscopegrafana avatar

    grafana/pyroscope

    11,503View on GitHub↗

    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

    Gocontinuous-profilingdeveloper-toolsdevops
    View on GitHub↗11,503
Compare all 30 related projects→

Frequently asked questions

What does dotnet/diagnostics do?

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…

What are the main features of dotnet/diagnostics?

The main features of dotnet/diagnostics are: .NET Command Line Interfaces, Debug Symbol Resolvers, Runtime Debugging, Memory Dump Parsers, Java Heap Dump Capturers, Debugger Extensions, Runtime Diagnostics, Application Performance Monitoring.

Which projects share features with dotnet/diagnostics?

Projects with overlapping indexed features include: 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…

Curated searches featuring Diagnostics

Hand-picked collections where Diagnostics appears.
  • Diagnostic navigation tools
  • a visual debugger for tracking code execution
  • Production diagnostic suites