Systems | Development | Analytics | API | Testing

It’s been a while since the last update post in july 2021, not that we haven’t updated OctoPerf since then but the additions we’ve made are not easy to share in a blog. Allow me to take an example.

In this Blog Post we are going to look at the GraphQL HTTP Request sampler and look at how GraphQL requests can also be made using a HTTP Request sampler in case you are for some reason restricted to an earlier version of JMeter (the sampler was only introduced in JMeter 5.4). We will also look at some of the principles of GraphQL.

Building performance tests that conform to a very specific level of load and concurrency is a standard approach to performance testing. You determine your peak levels of load and concurrency, and you build a test that meets this. You build soak test and scalability tests that conform to pre-determined levels of load and concurrency, and you execute these alongside the other scenarios you build to meet your performance requirements.

Pearson, founded in the 19th century, is one of the world leaders in providing education services all around the globe. Francisco Muniz is the Performance Architect for Pearson, responsible for Performance Alignment across Pearson’s Virtual Learning. This position entails working with many different parts of the organization, such as Architecture, Development, and QA. As such, Francisco was leading and overseeing the important Octoperf and Loadrunner software switching project.

There are many samplers that JMeter provides but I am willing to bet that the HTTP Request samplers is the most frequently used and, in this Blog Post, we are going to look at how this works and how it can be configured.

This post does not look at a particular aspect of JMeter nor does it give a detailed overview of how to use a particular tool that will compliment your performance testing with JMeter. What it is about is the principles of push to production pipelines and performance testing and while I have stated that this post is not specifically about JMeter in my experience JMeter is one of the best performance testing tools for this type of pipeline integration.

In this post we are going to look at WebSockets, specifically how JMeter can be used to test them. Web Sockets are not supported natively by JMeter but there are a couple of Plugins that you can use that work very nicely. One of them is called JMeter WebSocket Sampler by Maciej Zaleski and information on the library can be found here. The second and the one we will use for our post is also called JMeter WebSocket Sampler and is by Peter Doornbosch, more information on this Plugin can be found here.

Dynatrace is a cloud monitoring platform and is used by many organisations to measure the performance of their production systems and to set thresholds against which performance tolerance are measured. During testing Dynatrace can be used to monitor how the application under test responds during your performance tests as well as providing the capability to drill down into performance issues you may need to investigate.

You may have heard the term shift-left testing which is essentially moving the testing to an earlier stage in the project lifecycle, essentially the activity is moved to the left on the project timeline. The benefits of testing earlier have always been understood but not always happened when we consider performance testing which in some cases is still left until the very end of the delivery process.