How do I run a basic load test with Vegeta?

Use the attack command with a target, e.g., 'echo GET http://example.com | vegeta attack -duration=5s | vegeta report'. This sends requests at the default rate and outputs a text report with latency metrics.

Vegeta vs Apache JMeter: which is better for HTTP testing?

Vegeta excels at constant rate testing with precise control and avoids coordinated omission, while JMeter offers a GUI and more protocol support. Choose Vegeta for accurate, scriptable HTTP load tests.

Can Vegeta handle authentication in API requests?

Yes, you can add headers like Authorization with the -header flag or include basic auth in URLs, as shown in the http format examples in the README.

What does 'coordinated omission' mean in load testing?

It's a flaw where testers ignore delays during request generation, skewing latency metrics. Vegeta avoids this by accurately measuring latency even during bursts, ensuring realistic performance data.

How to generate dynamic request bodies with Vegeta?

Use the JSON format with base64 encoding and tools like jq for streaming, as demonstrated in the 'Generated targets' section, allowing for custom body generation on the fly.

Is Vegeta good for long-term stress testing?

Yes, with the -duration flag, but ensure system limits like file descriptors are tuned, and consider distributed setups for high volumes to avoid resource exhaustion.

Open-Awesome

Vegeta

MITGov12.13.0

A versatile HTTP load testing tool and library designed to drill HTTP services with a constant request rate.

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25.2k stars1.4k forks0 contributors

What is Vegeta?

Vegeta is an open-source HTTP load testing tool and library written in Go. It is designed to generate a constant rate of HTTP requests against target services, enabling developers to measure performance, identify bottlenecks, and validate system reliability under load. It solves the problem of inaccurate load testing by avoiding coordinated omission and providing detailed latency metrics.

Target Audience

Backend engineers, DevOps professionals, and performance testers who need to stress-test HTTP APIs, microservices, or web applications with precise control over request rates and comprehensive reporting.

Value Proposition

Developers choose Vegeta for its accuracy in load testing, ease of use via a composable CLI, and flexibility as both a standalone tool and a Go library. Its ability to avoid coordinated omission and support distributed testing makes it a reliable choice for production-grade performance validation.

Overview

HTTP load testing tool and library. It's over 9000!

Use Cases

Best For

Stress testing HTTP APIs and microservices with constant request rates
Measuring latency percentiles and throughput for performance benchmarking
Distributed load testing across multiple machines for high-volume scenarios
Integrating load testing into CI/CD pipelines via its CLI or Go library
Generating detailed performance reports in JSON, text, or histogram formats
Validating system reliability under simulated production traffic patterns

Not Ideal For

Testing non-HTTP services like gRPC, WebSockets, or databases
Teams preferring graphical user interfaces for test configuration and real-time monitoring
Scenarios requiring complex, stateful test logic without external scripting tools
Projects needing built-in support for protocol-specific features like WebSocket handshakes

Pros & Cons

Pros

Constant Rate Precision

Allows defining exact request rates per time unit, enabling realistic traffic simulation as highlighted in the attack command options.

Accurate Latency Metrics

Avoids coordinated omission, a common flaw in load testing, ensuring reliable latency measurements even during request bursts.

UNIX Composability

CLI designed for easy integration into scripts and pipelines, supporting tools like jq for dynamic target generation as shown in examples.

Extensive Reporting Options

Provides multiple report formats including JSON, histograms, and HDR plots for comprehensive performance analysis.

Cons

HTTP Protocol Limitation

Only supports HTTP/HTTPS, so it cannot be used for testing other protocols like gRPC or WebSockets without significant workarounds.

Manual Distributed Setup

Distributed testing requires external orchestration tools like pdsh, adding complexity compared to tools with built-in cluster management.

Prometheus Integration Issues

Prometheus support has limitations such as inaccurate timestamps and out-of-band configuration, as admitted in the README's limitations section.

Frequently Asked Questions

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