Performance optimization of deployed software-as-a-service applications

• We present an approach for detecting and analyzing so-called performance improvement opportunities (PIOs) using association rules, performance counters and the SARatio metric.
• A proof-of-concept case study is presented in which we show that the SARatio can be estimated using association rules and performance counters.
• We discuss an evaluation of our approach for PIO analysis done by a performance expert.

The goal of performance maintenance is to improve the performance of a software system after delivery. As the performance of a system is often characterized by unexpected combinations of metric values, manual analysis of performance is hard in complex systems. In this paper, we propose an approach that helps performance experts locate and analyze spots – so called performance improvement opportunities (PIOs) – for possible performance improvements. PIOs give performance experts a starting point for performance improvements, e.g., by pinpointing the bottleneck component. The technique uses a combination of association rules and performance counters to generate the rule coverage matrix, a matrix which assists with the bottleneck detection.In this paper, we evaluate our technique in two case studies. In the first one, we show that our technique is accurate in detecting the time frame during which a PIO occurs. In the second one, we show that the starting point given by our approach is indeed useful and assists a performance expert in diagnosing the bottleneck component in a system with high precision.