Description: Gatling is an open-source load testing framework based on modern technologies such as Scala, Akka, and Netty. Its design is aimed at facilitating the simulation of realistic load scenarios, allowing developers and QA teams to assess the performance of web applications under stress conditions. Gatling stands out for its ability to handle a large number of simultaneous users, making it an ideal tool for performance testing in high-demand applications. Additionally, its focus on functional programming and integration with continuous development tools makes it particularly appealing for teams looking to optimize their continuous integration pipelines. Gatling’s user interface provides detailed reports and graphs that allow users to effectively analyze the performance of their applications, facilitating the identification of bottlenecks and scalability issues. In summary, Gatling is not only a powerful tool for load testing but also seamlessly integrates into the software development lifecycle, helping to ensure that applications are robust and capable of handling the expected load in production.
History: Gatling was created by French developer Stéphane Landelle and was first released in 2012. Since its launch, it has significantly evolved, incorporating new features and improvements based on user community feedback. Its focus on functional programming and actor-based architecture, thanks to Akka, has set it apart from other load testing tools in the market.
Uses: Gatling is primarily used for load and performance testing of web applications, allowing development teams to identify scalability and performance issues before applications are deployed to production. It also integrates into continuous integration pipelines to automate performance testing in each development cycle.
Examples: A practical example of Gatling is its use in various web applications where thousands of users are simulated making requests simultaneously to assess how the system responds under load. Another case is its implementation in APIs, where response time and the ability to handle concurrent requests are measured.
