1 Autonomic Tuning Expert – A framework for best-practice oriented autonomic database tuning

Databases are growing rapidly in scale and com-plexity. High performance, availability, and fur-ther service level agreements need to be satisfied under any circumstances to please customers. In order to tune the DBMS within their complex environments, highly skilled database administra-tors (DBAs) are required. Unfortunately, they are becoming rarer and more and more expensive. Improving performance analysis and moving to-wards the automation of large information man-agement platforms requires a more intuitive and flexible source of decision making. This paper points out the importance of best-practices knowledge for autonomic database tun-ing and addresses the idea of formalizing and stor-ing DBA expert tuning knowledge for the autonomic management process. We will focus our attention on the development of a reference system for best-practice oriented autonomic data-base tuning for IBM DB2 and subsequently evalu-ate our system's tuning performance under changing workload.