We present three algorithms for detecting the need for software rejuvenation by monitoring the changing values of a customer-affecting performance metric, such as response time. Applying these algorithms can improve the values of this customer-affecting metric by triggering rejuvenation before performance degradation becomes severe. The algorithms differ in the way they gather and use sample values to arrive at a rejuvenation decision. Their effectiveness is evaluated for different sets of control parameters, including sample size, using simulation. The results show that applying the algorithms with suitable choices of control parameters can significantly improve system performance as measured by the response time.