Workload Characterization using CA's U.S. patented Neugents technology, provided in the CA MICS Capacity Planner, enables you to apply a clustering methodology to the analysis of your installation's workload. Workload characterization is an attractive approach to capacity planning and performance management problems because it allows the number of workload elements that need be considered in a study to be reduced from tens of thousands to only a few. Clustering methods are a statistical extension of scatter plots to identify similarities and differences between workloads. Scatter plots are often difficult to prepare and depend heavily on visual interpretation of the data. The need for visual interpretation limits the use of scatter plots to two or perhaps three axes. Clustering overcomes these disadvantages through its ability to recognize patterns in multiple dimensions. Using the CA MICS database as an input data source for clustering simplifies and extends the application of the technique. Note: Neugents technology is a prerequisite for using Workload Characterization. The following sections describe the analytic techniques, operational considerations, and reports used in the application.
This section contains the following topics:
15.4 Analytic Technique Tutorial
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