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Software Architecture with Python

You're reading from   Software Architecture with Python Design and architect highly scalable, robust, clean, and high performance applications in Python

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781786468529
Length 556 pages
Edition 1st Edition
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Author (1):
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Anand Balachandran Pillai Anand Balachandran Pillai
Author Profile Icon Anand Balachandran Pillai
Anand Balachandran Pillai
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Table of Contents (12) Chapters Close

Preface 1. Principles of Software Architecture FREE CHAPTER 2. Writing Modifiable and Readable Code 3. Testability – Writing Testable Code 4. Good Performance is Rewarding! 5. Writing Applications that Scale 6. Security – Writing Secure Code 7. Design Patterns in Python 8. Python – Architectural Patterns 9. Deploying Python Applications 10. Techniques for Debugging Index

Performance testing and measurement tools


These tools fall under two broad categories – namely, the ones used for performance testing and diagnostics, and the ones used for performance metrics gathering and instrumentation.

Performance testing and diagnostic tools can be classified further as follows:

  • Stress testing tools: These tools are used to supply workload to the system under test, simulating peak workloads in production. These tools can be configured to send a continuous stream of input to the application to simulate high stress or to periodically send a burst of very high traffic – much exceeding even peak stress – to test the robustness of the system. These tools are also called load generators. Examples of common stress testing tools used for web application testing include httpperf, ApacheBench, LoadRunner, Apache JMeter, and Locust. Another class of tools involves those that actually record real user traffic and then replay it via the network to simulate real user load. For example...

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