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In this paper we study the soft real-time web cluster architecture needed to support e-commerce and related applications. Our testbed is based on an industry standard, which defines a set of Web interactions and database transactions with their deadlines, for generating real workload and bench-marking e-commerce applications. In these soft real-time systems, the quality of service (QoS) is usually defined as the fraction of requests that meet the deadlines. When this QoS is measured directly, regardless of whether the request missed the deadline by an epsilon amount of time or by a large difference, the result is always the same. For this reason, only counting the number of missed requests in a period avoids the observation of the real state of the system. Our contributions are theoretical propositions of how to control the QoS, not measuring the QoS directly, but based on the probability distribution of the tardiness in the completion time of the requests. We call this new QoS metric tardiness quantile metric (TQM). The proposed method provides fine-grained control over the QoS so that we can make a closer examination of the relation between QoS and energy efficiency. We validate the theoretical results showing experiments in a multi-tiered e-commerce web cluster implemented using only open-source software solutions.