Workload-aware anomaly detection for Web applications
Journal of Systems and Software
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E-commerce systems are typically QoS-sensitive, so QoS-oriented tunings of e-commerce servers are very important for such systems. However, existing e-commerce benchmarks are insufficient for supporting QoS-oriented tunings, because some critical QoS features of e-commerce systems cannot be precisely evaluated by them. One example of these features is the integrality of service, which is usually expressed as a session, provided to customers. This paper presents a QoS-oriented e-commerce benchmark, which is named Bench4Q and is an extension of TPC-W supporting QoS-oriented tuning of e-commerce servers. The main features of Bench4Q include: (1) supporting session-based metrics analysis and (2) simulating QoS-sensitive load for QoS-oriented capacity analysis. We illustrate the promising benefits of these features for QoS-oriented tuning of an e-commerce server by a series of Bench4Q benchmarking on a typical e-commerce server.