Performance Extrapolation for Load Testing Results of Mixture of Applications

Load testing of IT applications faces the challenge of providing high quality test results that would represent the performance in production like scenarios, without incurring high cost of commercial load testing tools. It would help IT projects to be able to test with a small number of users and extrapolate to scenarios with much larger number of users. Such an extrapolation strategy when applied to mixture of application workloads running on a shared server environment must take into consideration application characteristics (CPU/IO intensive, memory bound) as well the server capabilities. The goal is to predict the performance of mixture workload, the maximum throughput offered by the application mix and the maximum number of users supported by the system before the throughput starts degrading. In this paper, we propose an extrapolation strategy that analyses a system workload mix based on its service demand on various resources and extrapolates its performance using simple empirical modeling techniques. Moreover, its ability to extrapolate throughput of an application mixture even if there is a change in the mixture, can help in capacity planning of the system.