AUTOMATED WORKLOAD FORECASTING - A LARGE COMPLEX SASe APPLICATION

نویسنده

  • Fay Wong
چکیده

In the area of computer performance and capacity planning, large amounts of operational data often have to be analyzed. Data analysis using SAS has been documented many times over the years. However, the most critical area of capacity planning-forecasting resource requirements--has received minimal attention as published papers or even as an area of development by most installations. Forecasting has usually been little more than a simple trend analysis. Workload forecast data is not readily available in the way IBM's SMF (System Monitoring Facility) or RMF (Resource Monitoring Facility) is. A considerable amount of an analysfs time is needed to solicit. organize, and analyze forecasting data. In installations that process a large number of unrelated applications, this process is very time-consuming and tedious. This paper presents a SAS system that has been developed to automate the workload forecasting process as much as possible. This system, called the Resource Utilization Projection System (RUPS), has evolved over several years and employs some unique approaches to forecasting problems. It also has been tailored to accommodate real wortd problems such as changing personnel and management's need for reports to assist forecasting. DisCUSsed are several creative techniques and procedures such as making seasonal adjustments and maximizing personnel involvement. One interesting item of discussion is an extremely effective and novel method to determine overhead factors (capture ratios) in estimating processor usage.

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تاریخ انتشار 2010