I like that Gatling is a non-GUI, developer-centric tool. The fact that scripts can even be AI-generated is pretty cool, and I find the memory footprint per script to be actually minuscule. It's efficient enough that I can use a single VM to run over 500 threads. I also appreciate how Gatling can be integrated into our dev workflows, allowing Claude to auto-generate Gatling scripts as we develop and build APIs. Additionally, AI can go through Postman collections to create a complete Gatling suite of scripts. Setting up Gatling was rather easy, with no problems there.

What I like most about Gatling is how easy it is to create and maintain performance tests. As an automation tester, I find its code-based approach more flexible than record-and-playback tools. It integrates smoothly with CI/CD pipelines, generates clear and detailed reports, and helps identify performance issues quickly. Overall, it's a reliable tool that makes performance testing efficient and fits well into modern automation workflows.

What I like most about Gatling is its flexibility and the ability to build complex performance test scenarios as code. It gives me full control over test flows, dynamic data, request generation, and different load injection models. I particularly appreciate that Gatling can be extended beyond standard HTTP testing. In my case, I use it for complex SOAP-based scenarios with dynamic request generation, WS-Security signing, custom mock services, and multi-step transaction flows. The Java-based DSL also makes it easier to structure, maintain, and reuse test components compared to traditional GUI-based performance testing tools. Another strong point is the clear separation between test logic, request generation, and load profiles, which makes the test project easier to develop and integrate into CI/CD pipelines.