Article in Journal ART-2016-08

BibliographyWettinger, Johannes; Breitenbücher, Uwe; Leymann, Frank: Enhancing Cloud Application DevOps Using Dynamically Tailored Deployment Engines.
In: Services Transactions on Cloud Computing. Vol. 4(1).
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 1-15, english.
Online, January 2016.
ISSN: 2326-7550.
Article in Journal.
CR-SchemaD.2.11 (Software Engineering Software Architectures)
C.2.4 (Distributed Systems)
Abstract

Shortening software release cycles increasingly becomes a critical competitive advantage as today's users, customers, and other stakeholders expect quick responses to occurring issues and feature requests. DevOps practices and Cloud computing are two key paradigms to tackle these issues by enabling rapid and continuous delivery of applications, utilizing automated software delivery pipelines. However, it is a complex and sophisticated challenge to implement such pipelines by installing, configuring, orchestrating, and integrating the required deployment automation solutions. Therefore, we present a method in conjunction with a framework and implementation to dynamically generate tailored deployment automation engines for specific application stacks, which 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 diverse deployment automation tooling. Beside a quantitative evaluation, we discuss two case studies in this context, one focusing on microservice architectures, the other one considering application functionality and its relation to deployment functionality.

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Department(s)University of Stuttgart, Institute of Architecture of Application Systems
Project(s)CloudCycle
SmartOrchestra
SitOPT
Entry dateAugust 17, 2016
   Publ. Department   Publ. Institute   Publ. Computer Science