bojand/ghz

Simple gRPC benchmarking and load testing tool

View on GitHub ↗Jump to charts ↓

Summary Information

Updated 1 hour ago
Added to GitGenius on September 20th, 2026
Created on March 13th, 2018
Open Issues & Pull Requests: 101 (+0)
GitHub issues: Enabled
Number of forks: 284
Total Stargazers: 3,353 (+0)
Total Subscribers: 25 (+0)

Charts & Analytics

Fetching additional details & charts...

Issue Activity (beta)

Open issues: 12
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 663 days
Stale 30+ days: 12
Stale 90+ days: 10

Recent activity

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

Top labels

  • WEB (1)
  • question (1)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

ghz is a gRPC benchmarking and load testing tool written in Go that measures the performance and throughput of gRPC services.

The tool addresses the need to evaluate gRPC service performance under various load conditions. It works by sending requests to gRPC endpoints and collecting metrics on response times, throughput, and error rates, allowing developers to understand how their services perform and identify bottlenecks.

The tool suits teams building or operating gRPC services who need to validate performance characteristics before deployment or monitor behavior under load. It is useful for both one-off performance investigations and as part of continuous integration pipelines. The project provides multiple installation methods including prebuilt binaries, Homebrew, and Docker, making it accessible regardless of development environment. It can be used both as a command-line tool and as a Go package for programmatic integration into testing workflows.

The project maintains steady activity with regular updates and responsiveness to issues. Development follows a structured approach with clear build processes documented for compilation from source using make or Go tooling directly. The codebase requires Go 1.11 or later and is organized to support both standalone usage and library integration.