ANALYSIS OF SUCCESS FACTORS AND ACTIONS IN DEVOPS PROJECTS USING FUZZY SET THEORIES
https://doi.org/10.26583/vestnik.2024.6.5
EDN: PNXKFF
Abstract
In the rapidly evolving field of software development, companies are increasingly using the DevOps paradigm to improve speed and quality. However, managing DevOps processes comes with significant challenges. Although the Project Management Body of Knowledge (PMBOK) provides industry-independent best practices, there is a gap in understanding the feasibility of achieving its success factors in DevOps projects. The purpose of the study is to identify key success factors in IT DevOps project management that are considered important but are not always realized in practice. A questionnaire survey was conducted using fuzzy set theory and fuzzy hierarchy analysis method to solve multi-criteria decision making problems. The analysis resulted in a ranked list of actions, with two groups: actions that are neglected and actions that are given more attention than required. These results indicate inconsistencies between recognized success factors and actual management practices. Addressing these mismatches is critical to improving DevOps project management efficiency, optimizing resource allocation, and improving project success rates. These findings provide a basis for developing strategies that better integrate PMBOK principles into DevOps processes.
About the Authors
E. I. LevadniyRussian Federation
R. M. Romanov
Russian Federation
References
1. Liu S., Wu B., Meng Q. Critical affecting factors of IT project management. 2012 International Conference on Information Management, Innovation Management and Industrial Engineering. IEEE, 2012. Vol. 1, Pp. 494–497.
2. Guide A. Project management body of knowledge (pmbok® guide). Project Management Institute, 2001. Vol. 11. No. 1. Pp. 7–8.
3. Levadny E.I., Romanov R.M. [Study of the integration of DevOps project management with PMBOK using fuzzy set theory]. Sovremennye problemy fiziki i tekhnologii: Sbornik tezisov dokladov XI mezhdunarodnoy molodezhnoy nauchnoy shkoly-konferentsii, Moskva, 23–25 aprelya 2024 goda [Proc. XI Int. Youth Scientific School-Conference «Modern Problems of Physics and Technology», Moscow, April 23–25, 2024]. Moscow: National Research Nuclear University MEPhI, 2024. Pp. 322–323 (in Russian).
4. Banica L., Radulescu M., Rosca D., Hagiu A. Is DevOps another project management methodology? Informatica Economica, 2017. Vol. 21. Iss. 3. Pp. 39–51.
5. Moeez M. Mahmood R, Asifet H. et al. Comprehensive Analysis of DevOps: Integration, Automation, Collaboration, and Continuous Delivery. Bulletin of Business and Economics (BBE), 2024. Vol. 13. No. 1. DOI: 10.61506/01.00253.
6. Bass L., Weber I., Zhu L. DevOps: A software architect's perspective. Addison-Wesley Professional, 2015. 425 p.
7. Erich F.M.A., Amrit C., Daneva M. A qualitative study of DevOps usage in practice. Journal of software: Evolution and Process, 2017. Vol. 29. Iss. 6. Article e1885.
8. DOI: 10.1002/smr.1885.
9. Maroukian K., Gulliver S.R. Leading DevOps practice and principle adoption. arXiv preprint arXiv:2008.10515, 2020. DOI: 1.48550/arX 0iv.2008.10515.
10. Luz W.P., Pinto G., Bonifácio R. Adopting DevOps in the real world: A theory, a model, and a case study . Journal of Systems and Software, 2019. Vol. 157. Pp. 110384.
11. Akbar M.A. et al. DevOps project management success factors: A decision-making framework. Software: Practice and Experience, 2024. Vol. 54. Iss. 2. Pp. 257–280.
12. Dubois D, Prade H. Decision-making under fuzziness. in Gupta M.M., Pagade R.K., and Yager R.R. Advances in Fuzzy Set Theory and Applications. Elsevier/North-Holland, 1979. Pp. 279– 302.
13. Chen C.T. Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy sets and systems, 2000. Vol. 114. No 1. Pp. 1–9.
14. Mardani A., Jusoh A., Zavadskas E.K. Fuzzy multiple criteria decision-making techniques and applications–Two decades review from 1994 to 2014. Expert systems with Applications, 2015. Vol. 42. No. 8. Pp. 4126–4148.
15. Chang D.Y. Applications of the extent analysis method on fuzzy AHP . European journal of operational research, 1996. Vol. 95. No. 3. Pp. 649–655.
16. Chang D.Y. Extent analysis and synthetic decision. Optimization techniques and applications, 1992. Vol. 1. No. 1. Pp. 352–355.
Review
For citations:
Levadniy E.I., Romanov R.M. ANALYSIS OF SUCCESS FACTORS AND ACTIONS IN DEVOPS PROJECTS USING FUZZY SET THEORIES. Vestnik natsional'nogo issledovatel'skogo yadernogo universiteta "MIFI". 2024;13(6):411-421. (In Russ.) https://doi.org/10.26583/vestnik.2024.6.5. EDN: PNXKFF