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By Tim Browning

Intends to use the recommendations of capability making plans to desktops with a mix of size, modelling and analytical tools for exact projection of desktop workload and source characterization

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96S>X and is the main factor in computing a confidence interval. The closer the upper and lower confidence interval values are to the forecast line, the better the fit. For planning purposes, it is recommended that this kind of analysis be combined with other statistical studies and the results of simulation models of expected workloads. 1 Identifying Business Elements The first part of a natural forecasting unit approach requires developing a business element model that identifies the business elements.

Nevertheless, critical PCs serving as file servers in a business-critical context can be the subject of professional capacity planning. 8 Double hump curve The trend in the early 1990s seems to be toward mainframe-like capabilities on small and much less expensive computer systems. It is tempting for the businessperson to believe that these smaller systems can be managed cheaply as well. However, without appropriate systems management disciplines and the unmanaged growth of departmental systems, businesses of the next 20 years may be faced with catastrophic complexity, uncertain capacity, and uncontrollable costs.

Average utilization over critical service peri­ ods may be summarized on monthly or even quarterly levels in order to show trends or growth patterns over longer duration than typically used by per­ formance analysts. The utilization of any device, without resorting to the more complex mathematics of queuing theory, can be expressed by the utilization law. A general mathematical expression of the utilization law is: «-Îwhere U "*]=*» (1) T V ) Q is the number of completions Bas the busy time of device i during observation period T _ , „ Number of Completions Q Throughput Xi ^ τ ^ = Mean Service Time Si = Total Time Served Bj Number Served Q Chapter 2 · The Metrics of Capacity Planning—Foundations 25 This expression of utilization has the advantage that no assumptions need be made about variable distribution or interarrivai times.

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