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Distributed Computing with Python

You're reading from   Distributed Computing with Python Harness the power of multiple computers using Python through this fast-paced informative guide

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Product type Paperback
Published in Apr 2016
Publisher
ISBN-13 9781785889691
Length 170 pages
Edition 1st Edition
Languages
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Author (1):
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Rasheedh B Rasheedh B
Author Profile Icon Rasheedh B
Rasheedh B
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Table of Contents (10) Chapters Close

Preface 1. An Introduction to Parallel and Distributed Computing 2. Asynchronous Programming FREE CHAPTER 3. Parallelism in Python 4. Distributed Applications – with Celery 5. Python in the Cloud 6. Python on an HPC Cluster 7. Testing and Debugging Distributed Applications 8. The Road Ahead Index

Chapter 7. Testing and Debugging Distributed Applications

Distributed systems, both large and small, can be extremely challenging to test and debug, as they are spread over a network, run on computers that can be quite different from each other, and might even be physically located in different continents altogether.

Moreover, the computers we use could have different user accounts, different disks with different software packages, different hardware resources, and very uneven performance. Some can even be in a different time zone. Developers of distributed systems need to consider all these pieces of information when trying to foresee failure conditions. Operators have to work around all of these challenges when debugging errors.

So far, in this book, we have not spent much time on the extremely important issue of what to do when something goes either wrong or differently than we expect, and we instead concentrated on some of the tools that we can use to write and deploy our applications...

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