Abstract: Although cluster-based multi-tier data centers provide a means for supporting scalable web applications, their ad-hoc configuration poses significant challenges to the performance and economical costs of multi-tier applications. This paper presents the design and implementation of MoKa - a utility-aware framework for modeling multi-tier data centers and planning their capacity and optimal configuration. The contribution of the paper is threefold. First, we identify two levels of configuration of cluster-based multi-tier data centers, local configuration that applies at server's level and architectural configuration that relates to the clusters of servers in a multi-tier architecture. The combination of these two levels of configuration improves the overall performance and cost of cluster-based multi-tier data centers. Second, we present a utility function for characterizing the impact of local and architectural configurations on the performance and cost of multi-tier systems. Third, we develop a utility-aware capacity planning algorithm for efficiently calculating the optimal local and architecural configuration of multi-tier data centers to provide guarantees on performance while minimizing the cost. Our experiments on a multi-tier e-commerce auction site show the effectiveness of MoKa Moreover, the experiments show that the combination of local and architectural configurations provides a 100% accurate utility for the multi-tier system, while with a single level of optimization (local or architectural) accuracy is limited between 20% and 90%.