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ABSTRACT
Agile development and operations (DevOps) is a model for delivering software as a service that comprises a set of practices and tools combining the responsibilities for both developing and operating the software into a single team. DevOps has been shown to offer advantages over traditional, waterfall-based software development methods. Agile software development practices have radically changed how developers realize software, breaking traditional structures. DevOps enables the team to continuously deliver software. The scope of DevOps is different, as it focuses on the relation between the development and operations teams. Both the academic literature and business press opine on DevOps implementation challenges and failures. The literature on DevOps is abundant but fails to convey with clarity what DevOps is. The lack of a homogeneous and clear conceptualization of DevOps is considered a major obstacle to the diffusion of this methodology.
We perform a systematic literature review to identify, review, and synthesise all the relevant studies published in the field of information systems and software engineering between 2012 and 2020. As a result of our review, we derive a conceptual model providing a logical categorisation and a clear definition of the conceptual elements of DevOps.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Supplemental data
Supplemental data for this article can be accessed here.
Notes
1. Holz, B., & West, M. (Citation2019). Agile in the Enterprise 2019 – Results Summary. Gartner. https://circle.gartner.com/Portals/2/Resources/pdf/Agile%20in%20the%20Enterprise%202019%20-%20Results%20Summary%20(updated).pdf
2. Details about the scoring of each criterion can be found in the original work of Ivarsson and Gorschek (Citation2011).
3. Details of the supporting studies can be found in Appendix I
4. Details of the supporting studies can be found in Appendix I
5. Autoscaling refers to the automatic allocation of resources depending on the load requirements possible in cloud environments.
6. Details of the supporting studies can be found in Appendix I