Studies on software reliability and performance reveal that long-running software systems show an increasing failure rate and/or a progressive degradation of their performance. This phenomenon is referred to as software aging, and it may eventually lead to an unacceptable level of system performance degradation and/or crash failure. A technique called software rejuvenation can be used to counteract software aging. This technique involves occasionally terminating an application or a system, cleaning its internal state and/or its environment, and restarting it. By removing the accrued error conditions and freeing up or defragmenting operating system resources, this technique proactively prevents unexpected future system outages. Unlike downtime caused by sudden failure occurrences, the downtime related to software rejuvenation can be scheduled at the discretion of the user or administrator, typically during the middle of the night or over weekends. This paper presents a generalized condition-based software rejuvenation model that is applicable to a wide range of applications. The rejuvenation model includes a stochastic deterioration process, a set of rejuvenation actions and their effects, and a schedule inspection policy that identifies the system deterioration. The optimal rejuvenation policy that minimizes the overall cost associated with the system is obtained using Markov decision processes. With minor modifications, the model can also be used for maximizing the system availability/capacity. This paper demonstrates the proposed model and the optimization procedure using an example of a web server subject to a two-dimensional software degradation process.