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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

The cloud and the HPC world


Chapter 5, Python in the Cloud, gave you a quick tour of the cloud in general and Amazon Web Services in particular. This is a hot topic nowadays, and the reason for this is simple: with relatively little upfront investment and virtually no wait, one can rent a few virtual machines together with, optionally, a database server and a data store. If the application needs more power, one can simply scale up the underlying infrastructure with the press of a button (and the swipe of a credit card).

Things, unfortunately, are never as simple as vendor brochures like to depict, especially when outsourcing a critical piece of infrastructure to a third party whose interests might not be perfectly aligned with ours.

A solid piece of advice is to always plan for the worst and keep automatic backups of the whole application and its software stack locally (or at the very least, on a separate provider). Ideally (but not that practically), one would have a scaled-down, but up...

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