Introduction The Beanshell Interpreter in JMeter can act as a server which as stated in the JMeter documentation is accessible by telnet or http. So what, I hear you say, well this can be useful and we will explore some of these uses in this Blog Post. Before we move on the definition of a Beanshell can be found on the official Web Site.
This blog post is a tutorial for writing Gatling scripts to load test web applications. It follows our first getting started with Gatling simulation scripts article. The application under test is a fake e-commerce. We are going to create a Virtual User that browses articles in this shop. To create a dynamic load test we will cover several topics.
Gatling is a load testing tool for measuring the performance of web applications. As such, it supports the following protocols: HTTP, WebSockets, Server-sent events. Other protocols are also supported either by Gatling itself (like JMS) or by community plugins. Gatling load testing scenarios are defined in code, more specifically using a specific DSL. This guide focuses on the basics of writing a simulation to test an HTTP application: OctoPerf’s sample PetStore.
In December, we updated OctoPerf to use the latest JMeter version. Although, as a minor version, it doesn’t bring a lot of new features, it is always better to stay up to date with the latest bugfixes. We had to implement a small change in OctoPerf because JMeter now properly enforces the cache control headers in every situation. To avoid any confusion, cache control headers have now been disabled by default in OctoPerf.
Kraken is a load testing IDE based on Gatling. As such, Kraken provides a complete development environment to software programmers and load testers that seek to make the most out of Gatling.
When we consider performance testing most of the focus of the approach is placed on the script creation activity and making sure that requirements are covered, these are very important parts of your performance testing approach but so is the Test Execution. The frequency at which you run your tests is important and can save you time and effort in your script maintenance. A good performance testing execution strategy gives you the maximum amount of benefit it can by finding performance issues early.
