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Policy-based management provides a means for IT systems to operate according to business needs. Unfortunately, there is often an "impedance mismatch" between the policies administrators want and the controls they are given. Consider the Apache Web server. Administrators want to control CPU and memory utilizations, but this must be done indirectly by manipulating tuning parameters such as MaxClients and KeepAlive. There has been much interest in using feedback control to bridge the impedance mismatch. However, these efforts have focused on a single metric that is manipulated by a single control and hence have not considered interactions between controls such as those that are common in computing systems. This paper shows how multiple-input, multiple-output (MIMO) control theory can be used to enforce policies for interrelated metrics. MIMO is used both to model the target system, Apache in our case, and to design feedback controllers. The MIMO model captures the interactions between KA and MC, and can be used to identify infeasible metric policies. In addition, MIMO control techniques can provide considerable benefit in handling trade-offs between speed of metric convergence and sensitivity to random fluctuations while enforcing the desired policies.