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In order to manage a service to meet the agreed upon SLA, it is important to design a service of the required capacity and to monitor the service thereafter for violations at runtime. This objective can be achieved by translating SLOs specified in the SLA into lower-level policies that can then be used for design and enforcement purposes. Such design and operational policies are often constraints on thresholds of lower level metrics. In this paper, we propose a systematic and practical approach that combines fine-grained performance modeling with regression analysis to translate service level objectives into design and operational policies for multi-tier applications. We demonstrate that our approach can handle both request-based and session-based workloads and deal with workload changes in terms of both request volume and transaction mix. We validate our approach using both the RUBiS e-commerce benchmark and a trace-driven simulation of a business-critical enterprise application. These results show the effectiveness of our approach.