Find the right load testing tool for a web service by browsing the categorized list of options sorted alphabetically.
Pick a scripting-capable framework like k6 or Gatling for running automated performance tests in a CI/CD pipeline.
Locate tools for simulating slow or malformed HTTP connections to check how a server handles misbehaving clients.
Use Locust to write complex user behavior scenarios in Python when repeating the same request is not enough.
This repository is a curated list of tools for testing how fast a web server or API responds under load. If you have built a website or a web service and want to know how many requests per second it can handle, or how it behaves when many users hit it simultaneously, the tools collected here are what engineers reach for. The list is organized alphabetically and covers a wide range of options. Some tools, like Apache Bench (ab), have been around for decades and are simple to run from a terminal. Others, like Gatling and k6, offer scripting support and produce detailed reports, which suits teams running automated performance tests as part of a build pipeline. A few entries, like Locust, let you describe user behavior in Python code, which is useful when the test scenario is more complex than just sending the same request repeatedly. The list also includes tools for REST API testing and debugging beyond raw load generation, as well as tools for simulating slow or malformed HTTP connections, which is relevant for security testing and checking how servers handle poorly-behaved clients. Most tools listed are open source and run on the command line. The README notes the programming language each tool is written in, which matters if you want to contribute to or inspect the source code, but does not affect how you use them. This is a reference list rather than a tutorial. It points you to each tool's project page so you can evaluate options and choose what fits your stack and testing goals.
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Verify against the repo before relying on details.