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.
Introduction Once upon a time documentation was one of the most important aspects of Quality Assurance and this was not limited to the functional test efforts but the non-functional testing as well. We spent days, weeks, months even creating Performance Test Strategies, Approaches, Plans, Test Case, Completion Reports etc. Most of these documents were required before any automation could be written and before a sensible performance testing framework could be considered.
Introduction If you are a performance testing specialist or a QA Manager or Programme Manager or anyone involved in the production of quality software then you understand why performance testing is required and its benefits in ensuring your products meet your Quality Criteria for release into production.
Introduction Creating complex performance testing scenarios in JMeter can be a complicated but necessary problem you will encounter as you build tests to mirror real user behaviour in your testing. There are many add-ins that can support you in the creation of these scenarios. Which is good if they do what you want them to do.
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.
