# autocannon — Fast HTTP/1.1 Benchmarking Tool for Node.js

> Fast HTTP/1.1 benchmarking tool written in Node.js with support for HTTP pipelining and programmatic API usage.

## Install

Save in your project root:

# autocannon — Fast HTTP/1.1 Benchmarking Tool for Node.js

## Quick Use
```bash
# Install globally
npm install -g autocannon

# Basic benchmark: 10 connections, 10 seconds
autocannon -c 10 -d 10 http://localhost:3000/

# Pipeline 10 requests per connection
autocannon -c 100 -d 30 -p 10 http://localhost:3000/

# Use as a library in a script
# const autocannon = require('autocannon'); autocannon({ url: 'http://localhost:3000' })
```

## Introduction
autocannon is an HTTP/1.1 benchmarking tool written entirely in Node.js that can generate substantial load while providing detailed latency and throughput statistics. Its standout feature is HTTP pipelining support, which sends multiple requests on a single connection before waiting for responses, dramatically increasing throughput to servers that support it. The tool works both as a CLI binary and as a programmatic Node.js library, making it easy to embed benchmarks directly in test suites.

## What autocannon Does
- Sends HTTP/1.1 requests with configurable concurrency, duration, and pipelining depth
- Reports latency percentiles (p50, p75, p90, p97.5, p99, p99.9), throughput, and error counts
- Supports HTTP pipelining to push multiple requests per connection round-trip
- Exposes a programmatic API for embedding benchmarks in Node.js scripts and CI jobs
- Generates live progress output with requests per second and latency updates

## Architecture Overview
autocannon maintains a pool of persistent TCP connections, each managed by a Client object that tracks in-flight requests and measures response times. When pipelining is enabled, each client sends multiple requests without waiting for a response, relying on HTTP/1.1 ordered responses to match them. Timing data is collected in an HdrHistogram for accurate percentile computation with minimal memory overhead. The coordinator runs a timer loop that samples throughput every second and finalizes results when the duration expires.

## Self-Hosting & Configuration
- Install globally (`npm install -g autocannon`) or as a project dependency
- Set `-c` for connections, `-d` for duration in seconds, `-p` for pipeline depth
- Use `-m POST` with `-b 'body'` or `-i body.json` for non-GET requests
- Pass custom headers via `-H "Authorization: Bearer token"`
- Output JSON with `-j` for automated threshold checking in CI

## Key Features
- HTTP pipelining support for testing servers that handle queued requests efficiently
- Dual-mode: CLI tool for quick tests, npm library for programmatic benchmarks
- HdrHistogram-based latency tracking for accurate percentile measurements
- Live progress bar showing real-time requests per second and latency
- Pure Node.js — no native compilation step, runs wherever Node runs

## Comparison with Similar Tools
- **wrk** — C-based with higher peak RPS; autocannon offers pipelining and a programmatic JS API
- **hey** — simpler Go binary; autocannon adds pipelining and embeddable library mode
- **oha** — Rust TUI for visual feedback; autocannon is ideal for Node.js-native CI workflows
- **Vegeta** — constant-rate Go tool; autocannon uses open-model concurrency with optional pipelining
- **k6** — scriptable in JavaScript with cloud features; autocannon is lighter for pure HTTP throughput tests

## FAQ
**Q: What is HTTP pipelining and why does it matter?**
A: Pipelining sends multiple requests on one connection without waiting for each response. It reduces round-trip overhead and can reveal server bottlenecks that standard serial requests miss.

**Q: Can I use autocannon as a library in my tests?**
A: Yes. Require autocannon and call `autocannon(opts, callback)` to run benchmarks programmatically and assert on the results.

**Q: Does autocannon support HTTPS?**
A: Yes. Pass an `https://` URL and autocannon handles TLS automatically. Use `--no-strictSSL` for self-signed certificates.

**Q: How do I compare results between runs?**
A: Use `autocannon-compare` to diff two JSON result files and see if latency or throughput regressed.

## Sources
- https://github.com/mcollina/autocannon
- https://github.com/mcollina/autocannon/blob/master/README.md

---
Source: https://tokrepo.com/en/workflows/8965c7fb-41af-11f1-9bc6-00163e2b0d79
Author: AI Open Source