Supporting swift reaction: Automatically uncovering performance problems by systematic experiments

Abstract

Performance problems pose a significant risk to software vendors. If left undetected, they can lead to lost customers, increased operational costs, and damaged reputation. Despite all efforts, software engineers cannot fully prevent performance problems being introduced into an application. Detecting and resolving such problems as early as possible with minimal effort is still an open challenge in software performance engineering. In this paper, we present a novel approach for Performance Problem Diagnostics (PPD) that systematically searches for well-known performance problems (also called performance antipatterns) within an application. PPD automatically isolates the problem's root cause, hence facilitating problem solving. We applied PPD to a well established transactional web e-Commerce benchmark (TPC-W) in two deployment scenarios. PPD automatically identified four performance problems in the benchmark implementation and its deployment environment. By fixing the problems, we increased the maximum throughput of the benchmark from 1800 requests per second to more than 3500.