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A methodology to support load test analysis

Performance analysts rely heavily on load testing to measure the performance of their applications under a given load. During the load test, analyst strictly monitor and record thousands of performance counters to measure the run time system properties such as CPU utilization, Disk I/O, memory consumption, network traffic etc. The most frustrating problem faced by analysts is the time spent and complexity involved in analysing these huge counter logs and finding relevant information distributed across thousands of counters. We present our methodology to help analysts by automatically identifying important performance counters for load test and comparing them across tests to find performance gain/loss. Further, our methodology help analysts to understand the root cause of a load test failure by finding previously solved problems in test repositories. A case study on load test data of a large enterprise application shows that our methodology can effectively guide performance analysts to identify and compare top performance counters across tests in limited time thereby archiving 88% counter data reduction.