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Continous deployment of multi-cloud systems

Published: 01 September 2015 Publication History

Abstract

In this paper we present our mechanism and tooling for the continuous deployment and resource provisioning of multi-cloud applications. In order to facilitate collaboration between development and operation teams as promoted in the DevOps movement, our deployment and resource provisioning engine is based on the Models@Runtime principles. This enables applying the same concepts and language (i.e., CloudML) for deployment and resource provisioning at development-and operation-time.

References

[1]
G. Blair, N. Bencomo, and R. France. [email protected]. IEEE Computer, 42(10):22–27, 2009.
[2]
N. Ferry, H. Song, A. Rossini, F. Chauvel, and A. Solberg. CloudMF: Applying MDE to Tame the Complexity of Managing Multi-Cloud Applications. In UCC, 2014.
[3]
M. Httermann. DevOps for developers. Apress, 2012.
[4]
J. Humble and D. Farley. Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation. Addison-Wesley Professional, 2010.
[5]
Introduction Continuous Deployment using Models@Runtime The Deployment Engine Conclusion References

Cited By

View all
  • (2018)Towards a benefits dependency network for DevOps based on a systematic literature reviewJournal of Software: Evolution and Process10.1002/smr.195730:11(e1957)Online publication date: 3-Jul-2018
  • (2017)Resource brokerage ontology for vendor-independent Cloud Service management2017 IEEE 2nd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)10.1109/ICCCBDA.2017.7951959(466-472)Online publication date: Apr-2017
  • (2016)Model-driven deployment and management of workflows on analytics frameworks2016 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2016.7840930(2819-2826)Online publication date: Dec-2016
  • Show More Cited By

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Published In

cover image ACM Conferences
QUDOS 2015: Proceedings of the 1st International Workshop on Quality-Aware DevOps
September 2015
32 pages
ISBN:9781450338172
DOI:10.1145/2804371
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2015

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Author Tags

  1. Cloud computing
  2. CloudML
  3. Models@Runtime
  4. deployment
  5. model-driven engineering

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Cited By

View all
  • (2018)Towards a benefits dependency network for DevOps based on a systematic literature reviewJournal of Software: Evolution and Process10.1002/smr.195730:11(e1957)Online publication date: 3-Jul-2018
  • (2017)Resource brokerage ontology for vendor-independent Cloud Service management2017 IEEE 2nd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)10.1109/ICCCBDA.2017.7951959(466-472)Online publication date: Apr-2017
  • (2016)Model-driven deployment and management of workflows on analytics frameworks2016 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2016.7840930(2819-2826)Online publication date: Dec-2016
  • (2016)Pattern‐based multi‐cloud architecture migrationSoftware: Practice and Experience10.1002/spe.244247:9(1159-1184)Online publication date: 3-Oct-2016

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