Approaching the Cloud: Using Palladio for Scalability, Elasticity, and Efficiency Analyses

In cloud computing, software architects develop systems for virtually unlimited resources that cloud providers account on a pay-per-use basis. Elasticity management systems provision these resource autonomously to deal with changing workloads. Such changing workloads call for new objective metrics allowing architects to quantify quality properties like scalability, elasticity, and efficiency, e.g., for software design analysis. However, analysis approaches such as Palladio so far did not support these novel metrics, thus rendering such analyzes inefficient. To tackle this problem, we (1) extended Palladio’s simulation approach SimuLizar by additional metrics for scalability, elasticity, and efficiency and (2) integrated the Architectural Template language into Palladio allowing architects to model cloud computing environments efficiently. A novel analysis process guides software architects through these new capabilities. In this paper, we focus on illustrating this new process by analyzing a simple, self-adaptive system.