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Architecting for DevOps and Continuous Deployment

Author:

Mojtaba ShahinAuthors Info & Claims

ASWEC ' 15 Vol. II: Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference

Pages 147 - 148

https://doi.org/10.1145/2811681.2824996

Published: 28 September 2015 Publication History

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Abstract

Development and Operations (DevOps) in the context of Continuous Deployment (CD) have emerged as an attractive software development movement, which tries to establish a strong connection between development and operations teams. CD is defined as the ability to quickly put new releases into production. We believe that DevOps/CD brings new challenges for architects, which considerably impacts both on their (architectural) design decisions and their organizational responsibilities. We assert that there is an important and urgent need of sufficient research work to gain a deep understanding of how DevOps/CD adoption can influence architecting, architectural decision-making processes and their outcomes in an organization. This PhD research is aimed at understanding and addressing new challenges for designing architectures for supporting DevOps in the context of CD.

References

[1]

Bass, L., Clements, P., and Kazman, R. 2012. Software architecture in practice. Addison Wesley.

Digital Library

Google Scholar

[2]

Bass, L., Weber, I., and Zhu, L. 2015. DevOps: A Software Architect's Perspective. Addison-Wesley Professional.

Digital Library

Google Scholar

[3]

Bellomo, S., Ernst, N., Nord, R., and Kazman, R. 2014. Toward Design Decisions to Enable Deployability: Empirical Study of Three Projects Reaching for the Continuous Delivery Holy Grail. In Proceedings of 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 702--707.

Digital Library

Google Scholar

[4]

Braun, V. and Clarke, V. 2006. Using thematic analysis in psychology. Qualitative research in psychology. 3, 2, 77--101.

Google Scholar

[5]

Chen, L. 2015. Towards Architecting for Continuous Delivery. In Proceedings of 12th Working IEEE/IFIP Conference on Software Architecture (WICSA), 131--134.

Digital Library

Google Scholar

[6]

Claps, G. G., Svensson, R. B, and Aurum, A. 2015. On the journey to continuous deployment: Technical and social challenges along the way. Information and Software Technology 57, 21--31.

Crossref

Google Scholar

[7]

Easterbrook, S., Singer, J., Storey, M.-A., and Damian, D. 2008. Selecting Empirical Methods for Software Engineering Research. In Guide to Advanced Empirical Software Engineering, F. Shull, J. Singer and D. K. Sjøberg Eds. Springer London, 285--311.

Google Scholar

[8]

Kitchenham, B. A. and Charters, S. 2007. Guidelines for performing systematic literature reviews in software engineering. Technical Report.

Google Scholar

[9]

Leppanen, M., Makinen, S., Pagels, M., Eloranta, V. P., Itkonen, J., Mantyla, M. V., and Mannisto, T. 2015. The Highways and Country Roads to Continuous Deployment. IEEE Software 32, 2, 64--72.

Digital Library

Google Scholar

[10]

Martini, A. and Bosch, J. 2015. The Danger of Architectural Technical Debt: Contagious Debt and Vicious Circles. In Proceedings of 12th Working IEEE/IFIP Conference on Software Architecture (WICSA), 1--10.

Google Scholar

[11]

Newman, S. 2015. Building Microservices. O'Reilly Media, Inc.

Google Scholar

[12]

Stol, K. J., and Fitzgerald, B. 2014. Research Protocol for a Case Study of Crowdsourcing Software Development. Technical Report.

Google Scholar

[13]

Waterman, M. G. 2014. Reconciling agility and architecture: a theory of agile architecture. Doctoral Thesis, Victoria University of Wellington.

Google Scholar

Cited By

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Azad NHyrynsalmi S(2024)Multivocal Literature Review on DevOps Critical Success FactorsProceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661236(520-527)Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1145/3661167.3661236
Kumar ANadeem MShameem M(2024)Metaheuristic-based cost-effective predictive modeling for DevOps project successApplied Soft Computing10.1016/j.asoc.2024.111834163:COnline publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1016/j.asoc.2024.111834
Azad NHyrynsalmi S(2024)Navigating Challenges and Pitfalls in DevOps-Driven Digital TransformationDisruptive Innovation in a Digitally Connected Healthy World10.1007/978-3-031-72234-9_10(115-128)Online publication date: 10-Sep-2024
https://doi.org/10.1007/978-3-031-72234-9_10
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Index Terms

Architecting for DevOps and Continuous Deployment
1. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Software architectures

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Information & Contributors

Information

Published In

ASWEC ' 15 Vol. II: Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference

September 2015

171 pages

ISBN:9781450337960

DOI:10.1145/2811681

Editors:
Fei-Ching (Diana) Kuo
Swinburne University of Technology, Australia
,
Stuart Marshall
Victoria University of Wellington, New Zealand
,
Haifeng Shen
Flinders University, Australia
,
Markus Stumptner
University of South Australia, Australia
,
M. Ali Babar
University of Adelaide, Australia

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Australian Comp Soc: Australian Computer Society

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 September 2015

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Extended-abstract
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Conference

ASWEC ' 15 Vol. II

ASWEC ' 15 Vol. II: ASWEC 2015 24th Australasian Software Engineering Conference

September 28 - October 1, 2015

SA, Adelaide, Australia

Acceptance Rates

ASWEC ' 15 Vol. II Paper Acceptance Rate 12 of 27 submissions, 44%;

Overall Acceptance Rate 12 of 27 submissions, 44%

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Citations

Cited By

View all

Azad NHyrynsalmi S(2024)Multivocal Literature Review on DevOps Critical Success FactorsProceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661236(520-527)Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1145/3661167.3661236
Kumar ANadeem MShameem M(2024)Metaheuristic-based cost-effective predictive modeling for DevOps project successApplied Soft Computing10.1016/j.asoc.2024.111834163:COnline publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1016/j.asoc.2024.111834
Azad NHyrynsalmi S(2024)Navigating Challenges and Pitfalls in DevOps-Driven Digital TransformationDisruptive Innovation in a Digitally Connected Healthy World10.1007/978-3-031-72234-9_10(115-128)Online publication date: 10-Sep-2024
https://doi.org/10.1007/978-3-031-72234-9_10
Sriraman GR. S(2023)A machine learning approach to predict DevOps readiness and adaptation in a heterogeneous IT environmentFrontiers in Computer Science10.3389/fcomp.2023.12147225Online publication date: 6-Oct-2023
https://doi.org/10.3389/fcomp.2023.1214722
Kumar ANadeem MShameem M(2023)Multicriteria decision‐making–based framework for implementing DevOps practices: A fuzzy best–worst approachJournal of Software: Evolution and Process10.1002/smr.2631Online publication date: 10-Nov-2023
https://doi.org/10.1002/smr.2631
Koushki NSondur SKant K(2022)Automated Configuration for Agile Software Environments2022 IEEE 15th International Conference on Cloud Computing (CLOUD)10.1109/CLOUD55607.2022.00074(511-521)Online publication date: Jul-2022
https://doi.org/10.1109/CLOUD55607.2022.00074
Faustino JAdriano DAmaro RPereira Rda Silva M(2022) DevOps benefits: A systematic literature review Software: Practice and Experience10.1002/spe.309652:9(1905-1926)Online publication date: 11-May-2022
https://doi.org/10.1002/spe.3096
Liu HHan QWang YHe FMao ZLi C(2020)An Analysis of DevOps Architecture for EMIS based on jBPM2020 International Conference on Service Science (ICSS)10.1109/ICSS50103.2020.00023(96-101)Online publication date: Aug-2020
https://doi.org/10.1109/ICSS50103.2020.00023
Arulkumar VLathamanju R(2019)Start to Finish Automation Achieve on Cloud with Build Channel: By DevOps MethodProcedia Computer Science10.1016/j.procs.2020.01.032165(399-405)Online publication date: 2019
https://doi.org/10.1016/j.procs.2020.01.032
Athamnah MPal AKant K(2018)A Framework for Misconfiguration Diagnosis in Interconnected Multiparty Systems2018 27th International Conference on Computer Communication and Networks (ICCCN)10.1109/ICCCN.2018.8487411(1-9)Online publication date: Jul-2018
https://doi.org/10.1109/ICCCN.2018.8487411
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