Abstract

Distributed computational infrastructures, as well as the applications and services that they support, are increasingly becoming an integral part of society and affecting every aspect of life. As a result, ensuring their efficient and robust operation is critical. How-ever, the scale and overall complexity of these systems is growing at an alarming rate (current data centers contain tens to hundreds of thousands of computing and stor-age devices running complex applications), making the management of these systems extremely challenging and rapidly exceeding human capability. The large quantities of distributed system data, in the form of user and component interaction and status events, contain meaningful information that can be used to infer the states of different components or of the system as a whole. Accurate and timely knowledge of these states is essential for verifying the correctness and efficiency of the operation of the system, as well as for discovering specific situations of interest, such as anomalies or faults, that require the application of appropriate management actions. Autonomic systems/applications must therefore be able to effectively process the large amounts of distributed data and to characterize operational states in a robust,