The peer-to-peer paradigm shows the potential to provide the same functionality and quality like client/server based systems, but with much lower costs. In order to control the quality of peer-to-peer systems, monitoring and management mechanisms need to be applied. Both tasks are challenging in large-scale networks with autonomous, unreliable nodes. In this paper we present a monitoring and management framework for structured peer-to-peer systems. It captures the live status of a peer-to-peer network in an exhaustive statistical representation. Using principles of autonomic computing, a preset system state is approached through automated system re-configuration in the case that a quality deviation is detected. Evaluation shows that the monitoring is very precise and lightweight and that preset quality goals are reached and kept automatically.