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Computational resources have such a significant influence on the operation of any software application, it is therefore important to understand how these applications utilize these resources. Modern resource-intensive enterprise and scientific applications are creating a growing demand for high performance computing infrastructures. They constantly interact with and rely heavily on complex resources. However, they often operate in resource-limited environments yet they often handle massive data, both in size and complexity. Software application services, processes or transactions compete for the much required but scarce resources. This creates the need to improve the existing resource allocation and management issue in such operational environments, as well as propose new ones, if necessary. Software developers try to analyze application operation environment using diverse analysis and design methods. Our aim therefore, is to design a tool that is able to work with a hybrid of adaptive and prediction-based resource management and allocation models while applying the priority based job scheduling algorithm to try and solve the application resource management challenges currently being faced in such environments, even if, partially.

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