An Extensible Architecture for Detecting Violations of a Cloud Environment's Constraints during Legacy Software System Migration

Abstract

By utilizing cloud infrastructures or platforms as services, SaaS providers can counter fluctuating loads through smoothly scaling up and down and therefore improve resource- and cost-efficiency, or transfer responsibility for the maintenance of complete underlying software stacks to a cloud provider, for instance. Our model-based approach CloudMIG aims at supporting SaaS providers to semi-automatically migrate legacy software systems to the cloud. Thereby, the analysis of conformance with the specific constraints imposed by a cloud environment candidate along with the detection of constraint violations constitutes an important early phase activity. We present an extensible architecture for describing cloud environments, their corresponding constraints, and appropriate violation detection mechanisms. There exist predefined constraint types with specified domain semantics as well as generic variants for modeling arbitrary constraints. A software system's compliance can be examined with the assistance of so called constraint validators. They operate on discovered KDM-based models of a legacy system. Additional constraint validators can be plugged into the validation process as needed. In this context, we implemented a prototype and modeled the PaaS environment Google App Engine for Java. We report on a quantitative evaluation regarding the detected constraint violations of five open source systems.