six-ddc/plow

A high-performance HTTP benchmarking tool that includes a real-time web UI and terminal display

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Summary Information

Updated 57 minutes ago
Added to GitGenius on September 15th, 2026
Created on June 13th, 2021
Open Issues & Pull Requests: 20 (+0)
GitHub issues: Enabled
Number of forks: 153
Total Stargazers: 4,514 (+0)
Total Subscribers: 29 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 14.5 hours
Mean response time: 117.7 days
90th percentile: 352.5 days
Tracked items: 3

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Issue Activity (beta)

Open issues: 1
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 454 days
Stale 30+ days: 1
Stale 90+ days: 1

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

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Detailed Description

Plow is an HTTP benchmarking tool that provides real-time performance metrics through both a web UI and terminal display.

Plow addresses the need to measure HTTP server performance under load with minimal overhead. It runs concurrent requests against a target URL and records execution time statistics, histograms, and percentiles in real time. The tool uses fasthttp instead of Go's standard net/http library to achieve higher throughput. It implements stream-based algorithms for computing histograms and quantiles, inspired by Prometheus, which keeps memory and CPU overhead low enough that the benchmarking process itself does not significantly impact the results being measured.

Plow suits developers and operators who need to quickly assess HTTP endpoint performance during development or in production environments. It works well for both short-duration tests and longer-running load scenarios, supporting execution modes based on connection count, request count, or time duration. The tool can be run via command line with options to specify concurrency level and test duration, and results are viewable both in the terminal and through a web interface. Binary distributions are available through multiple installation methods including Homebrew and Docker.

The project shows consistent maintenance with regular updates to address issues and incorporate improvements. Development activity demonstrates responsiveness to user feedback and bug reports. The codebase receives ongoing refinement to maintain performance characteristics and reliability.