miniprofiler/rack-mini-profiler

Profiler for your development and production Ruby rack apps.

View on GitHub ↗Jump to charts ↓

Summary Information

Updated 29 minutes ago
Added to GitGenius on September 17th, 2026
Created on September 6th, 2013
Open Issues & Pull Requests: 38 (+0)
GitHub issues: Enabled
Number of forks: 424
Total Stargazers: 3,904 (+0)
Total Subscribers: 55 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 13.9 days
Mean response time: 174.4 days
90th percentile: 486.3 days
Tracked items: 20

Most active contributors

Sign in to see contributor activity.

Charts & Analytics

Fetching additional details & charts...

Issue Activity (beta)

Open issues: 9
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,035 days
Stale 30+ days: 9
Stale 90+ days: 9

Recent activity

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

Top labels

  • enhancement (6)
  • bug (1)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

rack-mini-profiler is a profiling middleware for Ruby Rack applications that displays performance metrics directly in the browser during development and production.

The tool addresses the need to understand application performance bottlenecks by injecting a speed badge into every HTML page response. It captures detailed profiling data including database query timing, call-stack information via flame graphs, and per-request memory usage along with garbage collection statistics. The middleware integrates with Rails through ActiveSupport::Notifications rather than patching Rails methods directly, allowing it to gather timing information for template rendering, database queries, and other instrumented operations without invasive modifications to the framework.

Developers should adopt this tool if they need real-time visibility into request performance across development and production environments. It works well for Rails applications and other Rack-based frameworks where understanding query performance, gem overhead, and memory allocation patterns is important. The tool supports multiple databases including MySQL, PostgreSQL, and Oracle, as well as MongoDB through Mongoid. Teams running production applications benefit from the ability to profile live traffic without requiring separate profiling tools or log analysis.

The project is actively seeking community contributions to help with issue triage and repository restructuring efforts as part of a larger initiative to separate the central UI from language-specific implementations.