“JMeter is old technology”, I hear this a lot. “Let’s use this tool or that tool instead of JMeter as it’s the latest”, I hear this a lot. “We need a lightweight tool without the GUI interface to write our tests as that will make us more agile”, I hear this a lot.

This article is the fourth part of a series of tutorials dedicated to Gatling Load Testing. Kraken is used to ease the debugging of Gatling simulations and to speed up the process of load testing a fake e-commerce website: PetStore. We will focuse on POST requests and script modularization: In the previous blog post we created a realistic Virtual User that browses the store without buying anything.

While developing Kraken’s frontend I quickly stumbled upon performance issues with Angular Material tree when too many nodes where opened. Kraken is an open source load testing IDE. As such, it displays a tree of directories and files used to script the load testing scenarios: You can have a look by creating a free account on the demo or check the source code of the UI on GitHub. It uses the latest version of Angular and components provided by Angular Material such as the tree.

This third version of Kraken represents one more step towards a load testing solution suitable to teams and enterprises. Kraken can already be installed on your own Kubernetes cluster thanks to Helm charts: You own all data and can handle the security inhouse. But until now it was lacking users management, making it cumbersome to use it for a team of performance testers. This point is now addressed in the version 3.0 thanks to Keycloak.

OctoPerf’s report engine provides many graphs to sort and presents test metrics in a comprehensive way. We’ve tried to improve it over the years so that you can access critical information very quickly. But requirements vary from one project to the other. In this post we will look at how you can configure the report to show you preferred metrics, and also all the shortcuts you can take to achieve this goal.

You may have spent a considerable amount of time configuring Postman requests for your in-house API tests, and you wish to use them without having to create them again from scratch on Octoperf. That’s one of the many situations where Octoperf’s compatibility with Jmeter is going to come in a handy.

JMeter has many plug-ins and downloadable JAR Files you can use to support your testing, it is also possible to write your own custom Jar files and use these as well. Why would you want to do that, you may say, well whilst it is unlikely that you would need to create anything too complicated. You may feel the need to create utilities to support your own in-house performance testing or just something to make your testing process easier.

Here we are for yet another new release of OctoPerf. We’ve actually released two minor versions since the last update post, but this time we will also release a long awaited feature, Microsoft Azure on demand load generators!

Variables, may they be constant or dynamic, are an essential part of load testing. We already learned how to manipulate these values by extracting and re-injecting them inside one Virtual User. But what if we need to share these values between several Virtual Users ? In this blog post, I will show you just how to do that, using the MQ technology.

This blog post is a guide to help you write Gatling scripts in order to load test web applications efficiently. It follows our second Gatling Simulation scripts parameterization article. We will continue to load test a fake e-commerce, and so we are going to improve our Virtual User to make it browse the store in a more humanly way. We start where the previous blog post ended, with a simulation script that uses a CSV feeder and a Regular Expression extractor to visit dynamic pages of the pet store.