Book Image

Master Apache JMeter - From Load Testing to DevOps

By : Antonio Gomes Rodrigues, Bruno Demion (Milamber), Philippe Mouawad
Book Image

Master Apache JMeter - From Load Testing to DevOps

By: Antonio Gomes Rodrigues, Bruno Demion (Milamber), Philippe Mouawad

Overview of this book

Load tests help identify the maximum number of requests a software system can handle. One popular open source tool for load testing is JMeter. By leveraging the features and capabilities of JMeter, you can perform extensive load testing and fix issues in your application before they become problematic. This book is written by JMeter developers and begins by discussing the whole process, including recording a script, setting it up, and launching it, enabling you to almost immediately start load testing. You'll learn the best practices that you must follow while designing test cases. You'll also explore the different protocols offered by JMeter through various real-world examples. Finally, you'll see how to integrate JMeter into the DevOps approach and create professional reports. You'll discover ways to use the eco-system of JMeter to integrate new protocols, enrich its monitoring, and leverage its power through the use of the cloud. By the end of this book, you'll know all that's needed to perform comprehensive load testing on your applications by using all the best practices and features of JMeter.
Table of Contents (14 chapters)

Parameters to Take into Account when Creating a Scenario

Our list of scenarios is defined, but there are still many challenges in order to implement them in the most realistic way.

Here is a non-exhaustive list of important parameters for the implementation of our scenarios.

Vary User Input

In order to avoid testing only the performance of the cache of the targeted solution, it is necessary to vary the user inputs (values in the forms, login/password, and so on).

On the other hand, do make sure that you don't overly diversify the user input values at the risk of ending up with an application cache that appears to be inefficient because of an unrealistically wide data range.

Note

Monitor the metric cache hit ratio delivered by cache servers to validate the fact that the inputs chosen reflect reality.

If the hit ratio is too high, and higher than the production cache hit ratio, the dataset is not large enough.

If the hit ratio is too low, and lower than the production cache hit ratio, the dataset...