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New book: Cloud Computing for Science and Engineering

I am excited to announce the availability of Cloud Computing for Science and Engineering, a new book written by Dennis Gannon and myself and published by MIT Press. The full text is also available online at, along with associated Jupyter notebooks and other supporting material.

Clouds operated by Amazon, Microsoft, Google, and others provide convenient on-demand access to storage and computing. They also provide powerful services for organizing data, processing data streams, machine learning, and many other tasks. Every scientist and engineer needs to understand what these services can and cannot do, and what the emergence of cloud means for their work. This book addresses that need, describing cloud computing and how you may apply it to advantage in science and engineering. It is highly practical, with many hands-on examples of how to use cloud to address specific problems that arise in technical computing. It provides actionable advice on how and when to apply cloud computing in your work.

The book covers cloud services for managing data, and how to program these services; computing in the cloud, from deploying single virtual machines or containers to supporting basic interactive science experiments to gathering clusters of machines to do data analytics; using the cloud as a platform for automating analysis procedures, machine learning, and analyzing streaming data; building your own cloud with open source software; and cloud security. It covers major services provided by the Amazon, Google, and Microsoft clouds and the research data management capabilities of the Globus cloud service. Two chapters by guest authors cover the Eucalyptus (Rich Wolski) and OpenStack (Stig Telfer) private cloud technologies. See the figure below and the Table of Contents for more information on what the book covers.



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