Compensation-based vs. convergent deployment automation for services operated in the cloud

Abstract

Leading paradigms to develop and operate applications such as continuous delivery, configuration management, and the merge of development and operations (DevOps) are the foundation for various techniques and tools to implement automated deployment. To expose such applications as services (SaaS) to users and customers these approaches are typically used in conjunction with Cloud computing to automatically provision and manage underlying resources such as storage or virtual machines. A major class of these automation approaches follows the idea of converging toward a desired state of a resource (e.g., a middleware component deployed on a virtual machine). This is achieved by repeatedly executing idempotent scripts until the desired state is reached. Because of major drawbacks of this approach, we present an alternative deployment automation approach based on compensation and fine-grained snapshots using container virtualization. We further perform an evaluation comparing both approaches in terms of difficulties at design time and performance at runtime.