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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

Cloud computing and AWS

AWS is the leading provider of cloud computing; that is to say, it is a collection of Internet-based, on-demand computing and storage services, usually with a pay-as-you-go pricing model.

Being able to access the vast pool of computing resources (real or virtualized) and storage units of a cloud provider, means that an application can scale both horizontally (by adding more machines) and vertically (by choosing more powerful hardware) on demand. The same application can, therefore, run with no or very little downtime while adapting to its user load, by increasing or reducing the resources it uses dynamically (and therefore, its cost per unit of time).

This ease of scaling resources, the ability to tap into the vast resources of a big cloud provider such as Amazon, the high availability of cloud infrastructure, and the low prices of computing and storage resources, can make the cloud a very attractive option for application deployment, even for a small company or an...

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