Cloud Computing for Science and Engineering
by Ian Foster, Dennis B. Gannon
Publisher: The MIT Press 2017
Number of pages: 392
The book introduces the working scientist, engineer or student to cloud computing. It surveys the technology that underpins the cloud, new approaches to technical problems enabled by the cloud, and the concepts required to integrate cloud services into scientific work. It covers managing data in the cloud, 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.
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by Raghu Yeluri, Enrique Castro-Leon - Springer
The book highlights the fundamental technology components necessary to build and enable trusted clouds. Here is an explanation of the security and compliance challenges organizations face as they migrate mission-critical applications to the cloud.
by Jaydip Sen (ed.) - InTech
This book presents some applications in cloud frameworks along with some innovative design of algorithms and architecture for deployment in cloud environment. It is a valuable source for researchers, engineers, practitioners, and graduate students.
by Vijay Trehan - Red Hat
Cloud computing with Red Hat Enterprise Linux is a web-scale virtual computing environment powered by Amazon Web Services. It provides everything needed to develop and host applications: compute capacity, network bandwidth, storage capacity, etc.
by Alex Homer, et al. - Microsoft Press
The book contains design patterns and related guidance topics that articulate the benefits of applying patterns by showing how each piece can fit into cloud application architectures. It includes code samples and general advice on using each pattern.