microsoft/procmon-for-linux

A Linux version of the Procmon Sysinternals tool

View on GitHub ↗Jump to charts ↓

Summary Information

Updated 57 minutes ago
Added to GitGenius on September 14th, 2026
Created on July 10th, 2020
Open Issues & Pull Requests: 33 (+0)
GitHub issues: Enabled
Number of forks: 295
Total Stargazers: 4,740 (+0)
Total Subscribers: 84 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 5.7 days
Mean response time: 130.4 days
90th percentile: 621.0 days
Tracked items: 16

Most active contributors

Sign in to see contributor activity.

Charts & Analytics

Fetching additional details & charts...

Issue Activity (beta)

Open issues: 14
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 863 days
Stale 30+ days: 14
Stale 90+ days: 13

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • investigate (6)
  • Future (2)
  • bug (1)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

Process Monitor for Linux is a system tracing tool that captures and displays syscall activity across processes on Linux systems.

The tool addresses the need to observe what system calls processes are making, which is essential for debugging, performance analysis, and understanding application behavior. It works by tracing syscall activity and presenting the results through an interactive terminal user interface, allowing developers to filter and examine events in real time. The tool can also operate in headless mode to write captured events to a database file for later analysis.

Developers working on Linux systems who are familiar with the Windows Procmon tool will find this a direct equivalent for their platform. It suits scenarios where understanding process behavior at the syscall level is necessary, such as troubleshooting application issues, analyzing performance bottlenecks, or investigating system interactions. The tool supports filtering by process ID and specific syscalls, making it practical for focused investigation rather than requiring analysis of all system activity.

The project maintains an active build pipeline with automated testing. Development follows a structured contribution process documented in dedicated guidelines, and the maintainers actively solicit feedback through multiple channels including GitHub issues and feature requests. The codebase is written in C and requires standard build tools and SQLite development libraries to compile.