Web server performance measurement and modeling techniques

Abstract

The popularity of the Internet, and the usage of the world wide web in particular, has grown rapidly in recent years. Thousands of companies have deployed Web servers and their usage rates have increased dramatically. Our research has focused on measuring, analyzing and evaluating the performance of Internet and Intranet Web servers with a goal of creating capacity planning models. We have created layered queuing models (LQMs) and demonstrated their superiority to traditional queuing network models since they incorporate layered resource demands. Along the way we built a tool framework that enables us to collect and analyze the empirical data necessary to accomplish our goals. This paper describes the custom instrumentation we developed and deployed to collect workload metrics and model parameters from large-scale, commercial Internet and Intranet Web servers. We discuss the measurement issues pertaining to model parametrization and validation. We describe an object-oriented tool framework that significantly improves the productivity of analyzing the nearly 100 GBs of measurements collected during this workload study interval. Finally, we describe the LQM we developed to estimate client response time at a Web server. The model predicts the impact on server and client response times as a function of network topology and Web server pool size. We also use it to consider the consequences of server system configuration changes such as decreasing the HTTP object cache size.