Article in Proceedings INPROC-2015-17

BibliographyWettinger, Johannes; Breitenbücher, Uwe; Leymann, Frank: DynTail - Dynamically Tailored Deployment Engines for Cloud Applications.
In: Proceedings of the 8th International Conference on Cloud Computing (CLOUD).
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 421-428, english.
IEEE Computer Society, June 2015.
Article in Proceedings (Conference Paper).
CR-SchemaD.2.11 (Software Engineering Software Architectures)
C.2.4 (Distributed Systems)
Abstract

Shortening software release cycles increasingly becomes a critical competitive advantage, not exclusively for software vendors in the field of Web applications, mobile apps, and the Internet of Things. Today's users, customers, and other stakeholders expect quick responses to occurring issues and feature requests. DevOps and Cloud computing are two key paradigms to enable rapid, continuous deployment and delivery of applications utilizing automated software delivery pipelines. However, it is a highly complex and sophisticated challenge to implement such pipelines by installing, configuring, and integrating corresponding general-purpose deployment automation tooling. Therefore, we present a method in conjunction with a framework and implementation to dynamically generate tailored deployment engines for specific application stacks to deploy corresponding applications. Generated deployment engines are packaged in a portable manner to run them on various platforms and infrastructures. The core of our work is based on generating APIs for arbitrary deployment executables such as scripts and plans that perform different tasks in the automated deployment process. As a result, deployment tasks can be triggered through generated API endpoints, abstracting from lower-level, technical details of different deployment automation tooling.

Department(s)University of Stuttgart, Institute of Architecture of Application Systems
Project(s)CloudCycle
SitOPT
Entry dateApril 21, 2015
   Publ. Institute   Publ. Computer Science