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Distributed Computing with Python

You're reading from  Distributed Computing with Python

Product type Book
Published in Apr 2016
Publisher
ISBN-13 9781785889691
Pages 170 pages
Edition 1st Edition
Languages
Toc

Table of Contents (15) Chapters close

Distributed Computing with Python
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
1. An Introduction to Parallel and Distributed Computing 2. Asynchronous Programming 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

Creating a private cloud


AWS is a great option for a large number of people and companies. At the same time, however, one might realize that the cost of using cloud services from AWS or other providers sometimes adds up to unsustainable levels. Other times, company policies or even data privacy requirements might discourage or even outright forbid the use of cloud resources altogether.

In these cases, one solution could be the creation of an internal, private cloud. This private cloud would use in-house hardware to provide the infrastructure to provision and run virtual machines (a la EC2) as well as a data-storage middleware (similar to what S3 offers), together with other services such as load balancers, database servers, and so on.

There are a number of free, open source, and actively maintained software stacks that make the creation and operation of a private cloud simple (or at least simpler). OpenStack (http://www.openstack.org), CloudStack (https://cloudstack.apache.org), and Eucalyptus...

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