Stratus ML: A Layered Cloud Modeling Framework

Abstract

The main quest for cloud stakeholders is to find an optimal deployment architecture for cloud applications that maximizes availability, minimizes cost, and addresses portability and scalability. Unfortunately, the lack of a unified definition and adequate modeling language and methodologies that address the cloud domain specific characteristics makes architecting efficient cloud applications a daunting task. This paper introduces Stratus ML: a technology agnostic integrated modeling framework for cloud applications. Stratus ML provides an intuitive user interface that allows the cloud stakeholders (i.e., providers, developers, administrators, and financial decision makers) to define their application services, configure them, specify the applications' behaviour at runtime through a set of adaptation rules, and estimate cost under diverse cloud platforms and configurations. Moreover, through a set of model transformation templates, Stratus ML maintains consistency between the various artifacts of cloud applications. This paper presents Stratus ML and illustrates its usefulness and practical applicability from different stakeholder perspectives. A demo video, usage scenario and other relevant information can be found at the Stratus ML webpage.