Another area where server virtualization provides business value is in adaptive computing. Adaptive computing consists of server systems that have the ability to autonomously reconfigure themselves to address changing requirements. Adaptive computing is also referred to as autonomous computing, grid computing, on-demand computing, or utility computing. On-demand computing as referred to in this book is different from adaptive computing.
Server virtualization can work well with adaptive computing initiatives because of the ease of virtual machine provisioning. For example, consider a bank of Web application servers in a load balanced cluster. The Web application utilization rises and the overall performance of the application decreases. The system then allocates resources on a virtualization host server on which it creates two additional virtual machines using the same Web application server image. Once the two virtual machines have been created they are booted up and added dynamically to the existing cluster. The two additional servers help spread the application's workload over more computing resources, thus increasing the overall application performance. When the application's utilization falls off, the two additional servers are no longer needed and they are powered off and deleted.
This type of adaptive computing can be applied to many applications that share a common set of virtualization host server resources on which to dynamically create virtual machines. In addition to dynamically responding to needs, adaptive computing systems can have capacity scheduled in order to help optimize computing resource utilization. For instance, during the week an application may have five virtual machines on which to perform its work, but over the weekend, three of the virtual machines may be scheduled to be reconfigured to work with a different application to help with back-end processing. Adaptive computing scenarios can be achieved with physical hardware, including traditional server and blade servers, but typically at an increased cost and increased level of complexity as compared to using server virtualization.Use the following table of contents to navigate to chapter excerpts, or click here to view Business cases for server virtualization in its entirety.
|ABOUT THE BOOK:|
|Advanced Server Virtualization focuses on the core knowledge needed to evaluate, implement and maintain an environment that is using server virtualization. It emphasizes the design, implementation and management of server virtualization from both a technical and a consultative point of view. It provides practical guides and examples, demonstrating how to properly size and evaluate virtualization technologies. This volume is not based upon theory, but instead on real-world experience in the implementation and management of large-scale projects and environments. Currently, there are few experts in this relatively new field, making this book a valuable resource. Purchase the book from Amazon|
|ABOUT THE AUTHORS:|
|David Marshall is currently employed as a software engineer for Surgient Inc., a software company based in Austin, Texas, that provides software solutions that leverage x86 server virtualization technologies. He holds a B.S. in finance and an Information Technology Certification from the University of New Orleans. He has been working with virtualization software for the past six years. Dave McCrory works as chief scientist for Surgient Inc. He has filed several patents around server virtualization and management of virtual machines and has worked with virtualization technology for more than five years. Wade A. Reynolds is employed as a senior consultant by Surgient Inc. He has been designing and implementing enterprise solutions based on virtualization technology on a daily basis for more than three years, including VMware ESX Server and Mircosoft Virtual Server from its pre-beta release.|
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