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Master Apache JMeter - From Load Testing to DevOps

You're reading from   Master Apache JMeter - From Load Testing to DevOps Master performance testing with JMeter

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Product type Paperback
Published in Aug 2019
Publisher
ISBN-13 9781839217647
Length 468 pages
Edition 1st Edition
Languages
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Authors (3):
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Bruno Demion (Milamber) Bruno Demion (Milamber)
Author Profile Icon Bruno Demion (Milamber)
Bruno Demion (Milamber)
Antonio Gomes Rodrigues Antonio Gomes Rodrigues
Author Profile Icon Antonio Gomes Rodrigues
Antonio Gomes Rodrigues
Philippe Mouawad Philippe Mouawad
Author Profile Icon Philippe Mouawad
Philippe Mouawad
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Toc

Table of Contents (14) Chapters Close

About the Book 1. Quick Start with JMeter FREE CHAPTER 2. JMeter Overview 3. Designing a Test Case 4. Important Concepts in JMeter 5. Preparing the Test Environment (Injectors and Tested Systems) 6. Being Productive with JMeter 7. Load Testing a Website 8. Load Testing Web Services 9. Load Testing a Database Server 10. Load Testing Message-Oriented Middleware (MOM) via JMS 11. Performing a Load Test 12. Visualizing and Analyzing the Load Testing Results 13. Integration of JMeter in the DevOps Tool Chain

Practice with JMeter

Let's move on to practice.

SOAP/XML-RPC Web Services

Our test application will be a web service named Calculator (an example provided with Netbeans 8.2):

Figure 8.5: Calculator

Let's use HTTP Request and add in the Path and Body Data our call to the CalculatorWSService web service:

Figure 8.6: Web Service Call

Do not forget to add an assertion to control our response:

Figure 8.7: Result control

Here, we check that there is no exception returned by the web service.

Our test plan will look like this:

Figure 8.8: Test Plan

And, the result of the execution is:

Figure 8.9: HTML Source Formatted rendering

Note

Here, we used HTML Source Formatted rendering for a better presentation of the answer. XML rendering is also possible.

You can see the result of a call to the web service, CalculatorWSService, which makes an addition of 5 and 8.

To make the dataset as large as possible, we'll use the __Random function...

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