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.

This new release of OctoPerf brings a lot of long awaited features. This is all based on your feedback, so make sure to let us know what you would like to see in OctoPerf next! Of course we have a few plans of our own for the future, but I strongly believe that a good software can only result from a good collaboration between users and developers.

The principles behind performance testing API’s does not differ from the principles behind the performance testing of any application. Many API’s however are Asynchronous and a valid response from the API does not necessarily mean the transaction is complete which can cause a problem when measuring the performance of API’s. There are however ways around this and we will explore these in this post.

We have come a long way since the original release of the OctoPerf Enterprise Edition 30 months ago. We have added so many features since then that it felt important to regroup them in this blog post to highlight how easy it has become to install and manage your own OctoPerf server. I will refer to our documentation a lot because all of these features are detailed there. But documentation can sometimes make the decision process more difficult just because of the sheer amount of information it gives.