Preserving QoS of e-commerce sites through self-tuning

Abstract

The Quality of Service (QoS) of e-commerce sites plays a crucial role in attracting and retaining customers. The workload experienced by these sites tends to vary in a very dynamic way. The complexity of the sites combined with the large short-terms variations of the workload calls for automated methods for site configuration. This paper describes a method for dynamically monitoring and tuning e-commerce sites so that desired QoS levels are attained. Our approach uses hill climbing techniques combined with analytic queuing models to guide the search for the best combination of configuration parameters. We validate our approach in an experimental setting by comparing the QoS levels of a TPC-W e-commerce site with and without control. We showed that under increasing loads, the controlled system meets its QoS goals, while the uncontrolled site fails to do so.