ElaClo: A framework for optimizing software application topology in the cloud environment

Abstract

Abstract Application architectures in the cloud employ elastic components, and achieve lower operating costs without sacrificing quality. Software architects strive to provide efficient services by deciding on software topology: a set of structural architectural decisions. For a given application, there can be numerous software topology alternatives creating the need for automated optimization methods. Current optimization approaches rely on experts providing application performance models built upfront, based on their experience and the requirements provided. While such techniques are effective and valuable, they require additional maintenance effort as the software evolves. This paper introduces ElaClo, a framework for optimizing application topologies in a cloud environment. ElaClo’s main contribution is in providing optimization in the software assembly phase from automatically extracted application models. ElaClo provides workload generation, monitoring, topology management, elasticity mechanisms, and algorithms to support the optimization process. We have implemented ElaClo as an expert tool and evaluated it on a real-life cloud application from the retailing business domain. ElaClo was used to select optimal topologies with regards to service response time objectives and infrastructure costs. The efficiency of the optimization process and the quality of optimization results were validated quantitatively on a set of optimization runs. Results demonstrate the effectiveness of the suggested framework in yielding optimal topologies.