Due to the growth of cloud computing, data center environment has grown in importance and in use. Data centers are responsible for maintaining and processing several critical-value applications. Therefore, data center infrastructures must be evaluated in order to improve the high availability and reliability demanded for such environments. This work adopts Stochastic Petri Nets (SPN) to evaluate the impact of maintenance policies on the data center dependability. The main goal is to analyze maintenance policies, associated to SLA contracts, and to propose improvements. In order to accomplish this, an optimization strategy that uses Euclidean distance is adopted to indicate the most appropriate solution assuming conflicting requirements (e.g., cost and availability). To illustrate the applicability of the proposed models and approach, this work presents case studies comparing different SLA contracts and maintenance policies (preventive and corrective) applied on data center electrical infrastructures
