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As enterprise services increasingly interconnect as networked services in a service-oriented architecture (SOA), service level management (SLM) is becoming a complex problem and can no longer be handled by traditional monitoring tools like Microsoft SMS. SLM is a process managing the quality of services demanded by clients and offered by providers. This paper presents two contributions to the research of SLM. First, instead of considering monitoring as an isolated service, it incorporates monitoring as an integral part of a comprehensive QoS management framework. This framework consists of QoS management concepts and services including service level contract management, admission control, resource management, monitoring, diagnostics, and adaptation. Using this framework, clients are able to negotiate quality of service contracts with providers and providers are able to optimize system resources to meet contract requirements. The second contribution is the incorporation of diagnostic service in the QoS management framework. Based on data feed from monitoring service, diagnostic service is able to detect any condition changes and to reason about the causes of any degradation conditions in the networked enterprise system. With condition detection and situation understanding, QoS management can then proactively activate adaptation mechanisms to maximize the system's ability to meet QoS contract requirements of concurrent clients. Our monitoring service uses both reporting approach and probing approach to acquire the information of the health status of elements of a networked system. The monitored data is then fed to our diagnostic service to reason about root causes of anomalies, using graphical models. Depending on the system health status and root causes, appropriate adaptations are triggered proactively to improve the system performance under the constraints of concurrent QoS contracts. We validate our SLM approach using QoS management services integrated in a publish/subscribe style of SOA. We then demonstrate via experiments some benefits of QoS monitoring, diagnostics, and adaptation services for responsiveness SLM.