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Identify Target Load Levels
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A customer visit to a Web site comprises a series of related requests known as a user session. Users with different behaviors who navigate the same Web site are unlikely to cause overlapping requests to the Web server during their sessions. Therefore, instead of modeling the user experience on the basis of concurrent users, it is more useful to base your model on user sessions. User sessions can be defined as a sequence of actions in a navigational page flow, undertaken by a customer visiting a Web site. Without some degree of empirical data, target load levels are exactly that targets. These targets are most frequently set by the business, based on its goals related to the application and whether those goals are market penetration, revenue generation, or something else. These represent the numbers you want to work with at the outset. As soon as Web server logs for a pre-production release or a current implementation of the application become available, you can use data from these logs to validate and/or enhance the data collected by using the resources above. By performing a quantitative analysis on Web server logs, you can determine: The total number of visits to the site over a period of time (month/week/day). The volume of usage, in terms of total averages and peak loads, on an hourly basis. The duration of sessions for total averages and peak loads, on an hourly basis. The total hourly averages and peak loads translated into overlapping user sessions to simulate real scalability volume for the load test. By combining the volume information with objectives, key scenarios, user delays, navigation paths, and scenario distributions from the previous steps, you can determine the remaining details necessary to implement the workload model under a particular target load.
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Identify Metrics to Be Captured During Test Execution
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When identified, captured, and reported correctly, metrics provide information about how your application s performance compares to your desired performance characteristics. In addition, metrics can help you identify problem areas and bottlenecks within your application.
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It is useful to identify the metrics that relate to the performance acceptance criteria during test design so that the method of collecting those metrics can be integrated into the tests when implementing the test design. When identifying metrics, use either specific desired characteristics or indicators that are directly or indirectly related to those characteristics.
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Considerations
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Consider the following key points when designing a test: Real-world test designs are sensitive to dependencies outside the control of the system, such as humans and other systems interacting with the application. Realistic test designs are based on real operations and data, not mechanistic procedures. Realistic test designs produce more credible results and thus enhance the value of performance testing. Realistic simulation of user delays and think times is crucial to the accuracy of the test. If users are likely to abandon a task for any reason, this should be accounted for in your test design. Remember to include common user errors in your scenarios. Component-level performance tests are an integral part of real-world testing. Real-world test designs can be more costly and time-consuming to implement, but they deliver far more accurate results to the business and stakeholders. Extrapolation of performance results from unrealistic tests can be inaccurate as the system scope increases, and frequently lead to poor decisions. Involve the developers and administrators in the process of determining which metrics are likely to add value and which method best integrates the capturing of those metrics into the test. Beware of allowing your tools to influence your test design. Better tests almost always result from designing tests on the assumption that they can be executed and then adapting the test or the tool when that assumption is proven false, rather than by not designing particular tests based on the assumption that you do not have access to a tool to execute the test.
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