Planning and designing performance tests involves identifying key usage scenarios, determining appropriate variability across users, identifying and generating test data, and specifying the metrics to be collected. Ultimately, these items will provide the foundation for workloads and workload profiles. When designing and planning tests with the intention of characterizing production performance, your goal should be to create real-world simulations in order to provide reliable data that will enable your organization to make informed business decisions. Real-world test designs will significantly increase the relevancy and usefulness of results data. Key usage scenarios for the application typically surface during the process of identifying the desired performance characteristics of the application. If this is not the case for your test project, you will need to explicitly determine the usage scenarios that are the most valuable to script. Consider the following when identifying key usage scenarios:
Contractually obligated usage scenario(s)
Usage scenarios implied or mandated by performance-testing goals and objectives
Most common usage scenario(s)
Business-critical usage scenario(s)
Performance-intensive usage scenario(s)
Usage scenarios of technical concern
Usage scenarios of stakeholder concern
High-visibility usage scenarios 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. It is useful to identify the metrics related 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.
Source - Microsoft book
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