Article in Proceedings INPROC-2018-49

BibliographyHarzenetter, Lukas; Breitenbücher, Uwe; Falkenthal, Michael; Guth, Jasmin; Krieger, Christoph; Leymann, Frank: Pattern-based Deployment Models and Their Automatic Execution.
In: 11th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2018).
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 41-52, english.
IEEE Computer Society, December 2018.
DOI: 10.1109/UCC.2018.00013.
Article in Proceedings (Conference Paper).
CR-SchemaD.2.9 (Software Engineering Management)

The automated deployment of cloud applications is of vital importance. Therefore, several deployment automation technologies have been developed that enable automatically deploying applications by processing so-called deployment models, which describe the components and relationships an application consists of. However, the creation of such deployment models requires considerable expertise about the technologies and cloud providers used—especially for the technical realization of conceptual architectural decisions. Moreover, deployment models have to be adapted manually if architectural decisions change or technologies need to be replaced, which is time-consuming, error-prone, and requires even more expertise. In this paper, we tackle this issue. We introduce a meta-model for Pattern-based Deployment Models, which enables using cloud patterns as generic, vendor-, and technology-agnostic modeling elements directly in deployment models. Thus, instead of specifying concrete technologies, providers, and their configurations, our approach enables modeling only the abstract concepts represented by patterns that must be adhered to during the deployment. Moreover, we present how these models can be automatically refined to executable deployment models. To validate the practical feasibility of our approach, we present a prototype based on the TOSCA standard and a case study.

Department(s)University of Stuttgart, Institute of Architecture of Application Systems
Entry dateDecember 23, 2018
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