Artikel in Tagungsband INPROC-2017-12

Endres, Christian; Breitenbücher, Uwe; Falkenthal, Michael; Kopp, Oliver; Leymann, Frank; Wettinger, Johannes: Declarative vs. Imperative: Two Modeling Patterns for the Automated Deployment of Applications.
In: Proceedings of the 9th International Conference on Pervasive Patterns and Applications (PATTERNS).
Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik.
S. 22-27, englisch.
Xpert Publishing Services, Februar 2017.
ISBN: 978-1-61208-534-0.
Artikel in Tagungsband (Konferenz-Beitrag).
CR-Klassif.C.0 (Computer Systems Organization, General)
D.2.9 (Software Engineering Management)
D.2.13 (Software Engineering Reusable Software)
KeywordsModeling Patterns; Application Deployment and Management; Automation; Cloud Computing

In the field of cloud computing, the automated deployment of applications is of vital importance and supported by diverse management technologies. However, currently there is no systematic knowledge collection that points out commonalities, capabilities, and differences of these approaches. This paper aims at identifying common modeling principles employed by technologies to create automatically executable models that describe the deployment of applications. We discuss two fundamental approaches for modeling the automated deployment of applications: imperative procedural models and declarative models. For these two approaches, we identified (i) basic pattern primitives and (ii) documented these approaches as patterns that point out frequently occurring problems in certain contexts including proven modeling solutions. The introduced patterns foster the understanding of common application deployment concepts, are validated regarding their occurrence in established state-of-the-art technologies, and enable the transfer of that knowledge.

Abteilung(en)Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Anwendersoftware
Universität Stuttgart, Institut für Architektur von Anwendungssystemen
Eingabedatum9. März 2017
   Publ. Institut   Publ. Informatik