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Frequently Reported Performance Data
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The following are the most frequently reported types of results data. The sections that follow describe what makes this data interesting to whom, as well as considerations for reporting that type of data. End-user response times Resource utilizations Volumes, capacities, and rates
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End-user response time is by far the most commonly requested and reported metric in performance testing. If you have captured goals and requirements effectively, this is a measure of presumed user satisfaction with the performance characteristics of the system or application. Stakeholders are interested in end-user response times to judge the degree to which users will be satisfied with the application. Technical team members are interested because they want to know if they are achieving the overall performance goals from a user s perspective, and if not, in what areas those goals not being met.
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Figure 16.1 Response Time
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Figure 16.2 Response Time Degradation
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Even though end-user response times are the most commonly reported performancetesting metric, there are still important points to consider. Eliminate outliers before reporting. Even one legitimate outlier can dramatically skew your results. Ensure that the statistics are clearly communicated. The difference between an average and a 90th percentile, for example, can easily be the difference between ship it and fix it. Report abandonment separately. If you are accounting for user abandonment, the collected response times for abandoned pages may not represent the same activity as non-abandoned pages. To be safe, report response times for non-abandoned pages with an end-user response time graph and response times and abandonment percentages by page on a separate graph or table. Report every page or transaction separately. Even though some pages may appear to represent an equivalence class, there could be differences that you are unaware of.
Resource Utilizations
Resource utilizations are the second most requested and reported metrics in performance testing. Most frequently, resource utilization metrics are reported verbally or in a narrative fashion. For example, The CPU utilization of the application server never exceeded 45 percent. The target is to stay below 70 percent. It is generally valuable to report resource utilizations graphically when there is an issue to be communicated.
Exemplar for Stakeholders
Figure 16.3 Processor Time
Exemplar for Technical Team Members
Figure 16.4 Processor Time and Queue
Additional Considerations
Points to consider when reporting resource utilizations include: Know when to report all of the data and when to summarize. Very often, simply reporting the peak value for a monitored resource during the course of a test is adequate. Unless an issue is detected, the report only needs to demonstrate that the correct metrics were collected to detect the issue if it were present during the test. Overlay resource utilization metrics with other load and response data. Resource utilization metrics are most powerful when presented on the same graph as load and/or response time data. If there is a performance issue, this helps to identify relationships across various metrics. If you decide to present more than one data point, present them all. Resource utilization rates will often change dramatically from one measurement to the next. The pattern of change across measurements is at least as important as the current value. Moving averages and trend lines obfuscate these patterns, which can lead to incorrect assumptions and regrettable decisions.
Volumes, Capacities, and Rates
Volume, capacity, and rate metrics are also frequently requested by stakeholders, even though the implications of these metrics are often more challenging to interpret. For this reason, it is important to report these metrics in relation to specific performance criteria
or a specific performance issue. Some examples of commonly requested volume, capacity, and rate metrics include: Bandwidth consumed Throughput Transactions per second Hits per second Number of supported registered users Number of records/items able to be stored in the database
Exemplar
Figure 16.5 Throughput
Additional Considerations
Points to consider when reporting volumes, capacities and rates include: Report metrics in context. Volume, capacity, and rate metrics typically have little stand-alone value. Have test conditions and supporting data available. While this is a good idea in general, it is particularly important with volume, capacity, and rate metrics. Include narrative summaries with implications. Again, while this is a good idea in general, it is virtually critical to ensure understanding of volume, capacity, and rate metrics.
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