Workload-aware System Monitoring Using Performance Predictions Applied to a Large-scale E-Mail System

Offering services in the internet requires a dependable operation of the underlying software systems with guaranteed quality of service. The workload of such systems typically significantly varies throughout a day and thus leads to changing resource utilisations. Existing system monitoring tools often use fixed threshold values to determine if a system is in an unexpected state. Especially in low load situations, deviations from the system´s expected behaviour are detected too late if fixed value thresholds (leveled for peak loads) are used. In this paper, we present our approach of a workload-aware performance monitoring process based on performance prediction techniques. This approach allows early detections of performance problems before they become critical. We applied our approach to the e-mail system operated by Germany´s largest e-mail provider, the 1&1 Internet AG. This case study demonstrates the applicability of our approach and shows its accuracy in the predicted resource utilisation with an error of mostly less than 10%.