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Within the Cloud application life cycle, Cloud monitoring takes an important role since the fulfilment of the requirements has to be continuously controlled in order to avoid saturation or under-utilisation of Cloud resources and to check the compliance of the signed SLAs with the real performance of the infrastructure. In fact, to ensure scalability and dependability, the user's applications are often distributed on several computational resources, such as virtual machines, storages and so on, and the customer often is able to retrieve information about the Cloud infrastructure only by acquiring monitoring services provided by the same vendor that is offering the Cloud resources. In this work we present a complete framework that covers all the monitoring activities that take place within a Cloud application life cycle, introducing autonomic monitoring facilities that, exploiting the agent technology capabilities, allows the monitoring infrastructure to automatically adapt itself to the execution environment. These facilities provide both robustness and performance control to the framework, reducing the invasiveness of the monitoring and allowing, only if necessary, a deeper analysis of the measured data.