2017 Participants
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NAME: Patrick Shinn

Test Intelligence: Speeding the Analysis of Load Testing for Ultra-Large-Scale-Software Systems

Load testing is one of the means for evaluating the performance of Large Scale Systems (LSS). At the end of a load test, performance analysts must analyze thousands of performance counters from hundreds of machines under test. These performance counters are measures of run-time system properties such as CPU utilization, Disk I/O, memory consumption, and network traffic. Analysts observe counters to find out if the system is meeting its Service Level Agreements (SLAs). In my summer research, I will evaluate one supervised and three unsupervised approaches to help performance analysts to 1) more effectively compare load tests in order to detect performance deviations which may lead to SLA violations, and 2) to provide them with a smaller and manageable set of important performance counters to assist in root-cause analysis of the detected deviations. I plan to conduct a case study is based on load test data obtained from both a large scale industrial system and an open source benchmark application, which will run on the cluster of computers that built during my 2016 summer research.