Developing and Evaluating a Tool for Automating the Process of Modelling Web Server Workloads : An Explorative Feasibility Study in the Field of Performance Testing

University essay from Karlstads universitet/Handelshögskolan

Abstract: As the Internet has become increasingly important for people and for businesses that rely on it to create revenue, Internet unavailability can have major consequences. A common cause to unavailability is performance related problems. In order to evade such problems, the system’s quality characteristics in terms of performance need to be evaluated, which is commonly done with performance testing. When performance tests are conducted, the system under test is driven by an artificial workload or a sample of its natural workload while performance related metrics are measured. The workload is a very important aspect of performance testing, proved by measured performance metrics being directly dependent on the workload processed by the system under test. In order to conduct performance tests with representative workloads, the concept of workload modelling should be considered. Workload models attempt to model all relevant features of the workload experienced by a system within a given period of time. A workload model is created by set of consecutive activities that together constitute a process. This explorative feasibility study focuses on exploring, describing and evaluating the feasibility of a tool for automating the process of modelling Web server workloads for performance testing. A literature review was conducted in this student thesis, from which a research model was developed that describes the key factors in the process of modelling Web server workloads for performance testing, the relationships between these factors and their variables. The key factors constitute of four sub-processes and the relationships between them are the sequence flow, i.e. the order of events in the process. The process is initiated by the sub-process Establish Workload Data, where the workload data are retrieved and sanitised. The workload data are then categorised in homogeneous groups called workload entities, which is done in the Identify Workload Entities sub-process. Each workload entity has some associated workload attributes that are identified in the Identify Workload Attributes sub-process. In the last sub-process, Represent Workload, statistical methods, such as standard deviation and arithmetic mean, are applied in order to represent the workload in graphs and tables. Based on the research model and in order to evaluate the feasibility of a tool, a prototype was developed. The feasibility was evaluated through analysis of the primary empirical data, collected from an interview with a field expert who had tested the prototype. The analysis indicated that developing a tool for automating the process of modelling Web server workloads for performance testing is indeed feasible, although some aspects should be addressed if such a tool was to be realised. Analysis implied that an important aspect of modelling Web server workloads for performance testing is that the modeller must be in controller of what is being modelled. The prototype that was developed is highly static, i.e. it is not possible to create customised workload models. Therefore, if the tool is going to be realised, functionality for customising workload models should be added to the tool. Another important aspect that should be addressed if the tool is going to be realised is graphical representation of multiple workload attributes. The analysis indicated that there might be correlations between workload attributes. It is therefore important to be able to graphically represent multiple workload attributes together so that such correlations can be identified.

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