Book Image

Performance Testing with JMeter 3 - Third Edition

By : Bayo Erinle
Book Image

Performance Testing with JMeter 3 - Third Edition

By: Bayo Erinle

Overview of this book

JMeter is a Java application designed to load and test performance for web application. JMeter extends to improve the functioning of various other static and dynamic resources. This book is a great starting point to learn about JMeter. It covers the new features introduced with JMeter 3 and enables you to dive deep into the new techniques needed for measuring your website performance. The book starts with the basics of performance testing and guides you through recording your first test scenario, before diving deeper into JMeter. You will also learn how to configure JMeter and browsers to help record test plans. Moving on, you will learn how to capture form submission in JMeter, dive into managing sessions with JMeter and see how to leverage some of the components provided by JMeter to handle web application HTTP sessions. You will also learn how JMeter can help monitor tests in real-time. Further, you will go in depth into distributed testing and see how to leverage the capabilities of JMeter to accomplish this. You will get acquainted with some tips and best practices with regard to performance testing. By the end of the book, you will have learned how to take full advantage of the real power behind Apache JMeter.
Table of Contents (17 chapters)
Title Page
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Index

Summary


We covered quite a lot of ground in this chapter. We learned how we can distribute a load using different techniques when executing test plans. We learned how to have JMeter work in a master/node configuration. With the help of tools such as Vagrant, we made a daunting task really easy. We learned how to spin off several node machines on the same physical box (or different boxes) and use a master node to control them all from a JMeter GUI. While convenient, we saw that this method was limiting in terms of scalability. As the number of slave nodes grew, the master quickly became a bottleneck due to high I/O generated from several nodes trying to report progress to it. To overcome such restrictions and ultimately achieve infinite scalability, we learned how to run several test machines in parallel to execute our test plans. In the process, we leveraged the AWS infrastructure and saw how we can use the cloud to aid more efficient testing, thereby helping us reach our goals.

In the last...