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Automatic service and application deployment and management is becoming possible through the use of service and infrastructure discovery and policy systems. But using the infrastructure optimally requires intimate knowledge of the hardware and the interaction of its components in order to make optimal allocation of shared resources. This paper proposes an architecture where the hardware infrastructure not only makes operational parameters available (disk size, network bandwidth) but also presents to the service management components, relationships and constraints between the hardware components. We present an implementation which uses the Service Modeling Language, SML, to communicate this information and show how this architecture saves service management from knowing intimate knowledge of the hardware. This enhances optimal service deployment and management in a heterogeneous hardware environment and is a step toward autonomic computing.