Autonomic Computing has recently contributed to the development of self-manageable Cloud services. It provides means to free Cloud administrators of the burden of manually managing varying-demand services while enforcing Service Level Agreements (SLAs). However, designing Autonomic Managers (AMs) that take into account services' runtime properties so as to provide SLA guarantees without the proper tooling support may quickly become a non-trivial, fastidious and error-prone task as systems size grows. In fact, in order to achieve well-tuned AMs, administrators need to take into consideration the specificities of each managed service as well as its dependencies on underlying services (e.g., a Sofware-as-a-Service that depends on a Platform/Infrastructure-as-a-Service). We advocate that Cloud services, regardless of the layer, may share the same consumer/provider-based abstract model. From that model we can derive a unique and generic AM that can be used to manage any XaaS service defined with that model. This paper proposes such an abstract (although extensible) model along with a generic constraint-based AM that reasons on abstract concepts, service dependencies as well as SLA constraints in order to find the optimal configuration for the modeled XaaS. The genericity of our approach are showed and discussed through two motivating examples and a qualitative experiment has been carried out in order to show the approache's applicability as well as to point out and discuss its limitations.