Artikel in Tagungsband INPROC-2017-25

Saatkamp, Karoline; Breitenbücher, Uwe; Kopp, Oliver; Leymann, Frank: Topology Splitting and Matching for Multi-Cloud Deployments.
In: Proceedings of the 7th International Conference on Cloud Computing and Services Science (CLOSER 2017).
Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik.
S. 247-258, englisch.
SciTePress, April 2017.
ISBN: 978-989-758-243-1.
Artikel in Tagungsband (Konferenz-Beitrag).
CR-Klassif.G.0 (Mathematics of Computing General)
H.0 (Information Systems General)
KeywordsApplication Deployment; Distribution; Splitting; Cloud Computing; TOSCA

For automating the deployment of applications in cloud environments, a variety of deployment automation technologies have been developed in recent years. These technologies enable specifying the desired deployment in the form of deployment models, which can be automatically executed. However, changing internal or external conditions often lead to strategical decisions that must be reflected in all deployment models of a company’s IT. Unfortunately, while creating such deployment models is difficult, adapting them is even harder as typically a variety of technologies must be replaced. In this paper, we present the Split and Match Method that enables splitting a deployment model following a manually specified distribution on the business layer. The method also enables automatically deploying the resulting model without the need for a manual intervention and, thus, significantly eases reflecting strategical decisions on the technical deployment layer. We present a formalization and algorithms to automate the steps of the method. Moreover, we validate the practical feasibility of the presented concepts by a prototype based on the TOSCA standard and the OpenTOSCA ecosystem.

Volltext und
andere Links
CLOSER 2017 website
Abteilung(en)Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Anwendersoftware
Universität Stuttgart, Institut für Architektur von Anwendungssystemen
Eingabedatum10. Mai 2017
   Publ. Institut   Publ. Informatik