Model-based evaluation is extensively used to estimate performance and reliability of dependable systems. Traditionally, those systems were small and self-contained, and the main challenge for model-based evaluation has been the efficiency of the solution process. Recently, the problem of specifying and maintaining complex models has increasingly gained attention, as modern systems are characterized by many components and complex interactions. Components share similarities, but also exhibit variations in their behavior due to different configurations or roles in the system. From the modeling perspective, variations lead to replicating and altering a small set of base models multiple times. Variability is taken into account only informally, by defining a sample model and explaining its possible variations. In this paper we address the problem of including variability in performability models, focusing on Stochastic Activity Networks (SANs). We introduce the formal definition of Stochastic Activity Networks Templates (SAN-T), a formalism based on SANs with the addition of variability aspects. Differently from other approaches, parameters can also affect the structure of the model, like the number of cases of activities. We apply the \mbox{SAN-T} formalism to the modeling of the backbone network of an environmental monitoring infrastructure. In particular, we show how existing SAN models from the literature can be generalized using the newly introduced formalism.