Tsunami Case Study

Feb 3rd, 2012
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Strayer University
Course: IT
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With the ever growing demand for storage capacity and the ability to meet archiving queries, organizations have turned to emerging technologies and methods in handling archiving requirements. From the implementation of internal storage expansion units to the inception, development, and implementation of highly sophisticated storage area networking platforms, organizations must consider alternatives. However, what organizations must also consider is the potentially astronomical cost associated with long term archiving as well as system performance degradation. Lastly, to effective implement a viable functioning storage network, GPU co-processing and redundant servers should be considered.

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Tsunami Case StudyStudent Name HereStrayer UniversityDr. Richard BrownSubmission DateContentsAbstractWith the ever growing demand for storage capacity and the ability to meet archiving queries, organizations have turned to emerging technologies and methods in handling archiving requirements. From the implementation of internal storage expansion units to the inception, development, and implementation of highly sophisticated storage area networking platforms, organizations must consider alternatives. However, what organizations must also consider is the potentially astronomical cost associated with long term archiving as well as system performance degradation. Lastly, to effective implement a viable functioning storage network, GPU co-processing and redundant servers should be considered.Analyze Performance DegradationEvery computer system or networking infrastructure at some point will reduce its performance from previous configurations in which the performance issues become noticeable. From the basic public user to network administrators, everyone accessing network resources will notice this dramatic observation. According to Authors G. Bruce Berriman and Steven L. Groom, the increase in achievable data has generated concerns of data set storing and the performance function to efficiently conduct requested operations (Groom, 2011, pp. 52-56). The largest contribution to performance degradation is a d

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