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LoadTest Report: Total Time Percentage Columns
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If you run a Load Test with the "Record individual hits" option turned on, an additional table with percentiles ranging from 10% to 99% will appear in your Load Test Report and Statistics view. I'd like to explain what these numbers mean.
Say we have the following numbers from a sample run:
| 99% | 95% | 90% | 70% | 50% | 10%|
| 1000 | 75 | 75 | 75 | 20 | 5 |
The columns from "99%" to "10%" correspond to percentiles for the execution time of a test. Assume that we have a "SOAP Client" test runs a 1000 times. The "50%" column corresponds to the 50th percentile, which amounts to 20 milliseconds. This means that of the 1000 times that the SOAP Client was executed, 500 times that test executed in 20 milliseconds and less. The "95%" column indicates that of the 1000 times the SOAP Client test was executed, 950 times that test executed in 75 milliseconds or less, and 50 times that test took more than 75 milliseconds to execute.
To sum up, these numbers help explain the execution time of tests at different time intervals. By using this data, we can get a detailed reading of the test execution time. Instead of assuming almost all tests (99%) executed under a 1000ms or less, we can assume that most tests (95%) took 75ms or less and the 1000ms may have been an outlier data point.
Say we have the following numbers from a sample run:
| 99% | 95% | 90% | 70% | 50% | 10%|
| 1000 | 75 | 75 | 75 | 20 | 5 |
The columns from "99%" to "10%" correspond to percentiles for the execution time of a test. Assume that we have a "SOAP Client" test runs a 1000 times. The "50%" column corresponds to the 50th percentile, which amounts to 20 milliseconds. This means that of the 1000 times that the SOAP Client was executed, 500 times that test executed in 20 milliseconds and less. The "95%" column indicates that of the 1000 times the SOAP Client test was executed, 950 times that test executed in 75 milliseconds or less, and 50 times that test took more than 75 milliseconds to execute.
To sum up, these numbers help explain the execution time of tests at different time intervals. By using this data, we can get a detailed reading of the test execution time. Instead of assuming almost all tests (99%) executed under a 1000ms or less, we can assume that most tests (95%) took 75ms or less and the 1000ms may have been an outlier data point.
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