Database administration routines involve manual or semi-automatic methods for monitoring the environment and solving problems that arise. In this work, we propose a novel alternative approac h to this task, which unifies two Artificial Intelligence techniques: Case Based Reasoning and Intelligent Agents. Our prototype, DBSitter, consists of a Multi-agent system for automatic monitoring and fault correcting in a relational DBMS, where problems are represented as Cases. In searching for better solutions, the system can also interact with the Database Administrator. The main functionalities provided are failure prediction and adaptation of problem - solving capabilities through the chosen learning mechanism.