Performance Knowledge Discovery for Modeling
نویسندگان
چکیده
Performance modeling has long been considered a difficult science requiring expertise from seasoned capacity planners. Currently there has been a shift in the area of performance modeling towards ease-of-use and automation of the entire process. Automation not only hides this difficult science from the users but also delivers immediate Return on Investment for administrators with deploy and run mentality. One area that has not been sufficiently explored in this process of automation is the Knowledge Discovery from the collected performance data. This paper talks about the discovery of knowledge from the performance data and how this knowledge combined with some of the automatic workload characterization techniques can help in creating a good first cut of the workload definition specific to the user environment.
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