Streamlining DevOps automation for Cloud applications using TOSCA as standardized metamodel
DevOps as an emerging paradigm aims to tightly integrate developers with operations personnel. This enables fast and frequent releases in the sense of continuously delivering new iterations of a particular application. Users and customers of today's Web applications and mobile apps running in the Cloud expect fast feedback to problems and feature requests. Thus, it is a critical competitive advantage to be able to respond quickly. Besides cultural and organizational changes that are necessary to apply DevOps in practice, tooling is required to implement end to end automation of deployment processes. Automation is the key to efficient collaboration and tight integration between development and operations. The DevOps community is constantly pushing new approaches, tools, and open source artifacts to implement such automated processes. However, as all these proprietary and heterogeneous DevOps automation approaches differ from each other, it is hard to integrate and combine them to deploy applications in the Cloud using an automated deployment process. In this paper we present a systematic classification of DevOps artifacts and show how different kinds of artifacts can be discovered and transformed toward TOSCA, which is an emerging standard. We present an integrated modeling and runtime framework to enable the seamless and interoperable integration of different approaches to model and deploy application topologies. The framework is implemented by an open source, end to end toolchain. Moreover, we validate and evaluate the presented approach to show its practical feasibility based on a detailed case study, in particular considering the performance of the transformation toward TOSCA. Classification of DevOps artifacts and their usage.Integrated, standards driven modeling runtime framework based on TOSCA.Discovery, transformation, and APIfication of DevOps artifacts.Enrichment and deployment of application topologies.Evaluation of artifact transformation and comprehensive case study.
Future Gener. Comput. Syst.