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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%.