Performance and Efficiency Evaluation of GitOps-Based Deployment Workflows

Authors

  • Giorgi Tseradze MSc (Information Systems), Business and Technology University, Tbilisi, Georgia Author
  • Giorgi Kuchava PhD (Engineering of Informatics), Associate professor, Georgian Technical University, Tbilisi, Georgia Author
  • Teimuraz Sturua Candidate of Technical Sciences, Associate professor, Georgian Technical University, Tbilisi, Georgia Author
  • Ana Khinchikashvili BSc (Information Technologies), Business and Technology University, Tbilisi, Georgia Author
  • Ekaterine Somkhishvili BSc (Information Technologies), Assistant, Business and Technology University, Tbilisi, Georgia Author
  • Ioseb Kartvelishvili Candidate of Technical Sciences, Professor, Georgian Technical University, Tbilisi, Georgia Author
  • Maka Mantskava PhD (Biology), Professor, European University, Tbilisi, Georgia Author
  • Shalva Chokhonelidze MSc (Computer Science), Senior Scientist, I.Beritashvili Center of Experimental Biomedicine, Tbilisi, Georgia Author
  • Nana Momtselidze PhD (Biology), Senior Scientist, I.Beritashvili Center of Experimental Biomedicine, Tbilisi, Georgia Author

Keywords:

GitOps, CI/CD, Kubernetes, Argo CD, Flux, DevOps, YAML

Abstract

GitOps represents a modern approach to infrastructure and software deployment that leverages Git to enable continuous, automated, and controlled operational processes. This study examines the core functional mechanisms of GitOps, including declarative configuration, the reconciliation loop, and the pull-based deployment model. Special attention is given to Argo CD and Flux as leading GitOps tools, with an emphasis on their integration with Kubernetes. The paper analyzes real-world operational workflows, architectural components, and security mechanisms associated with GitOps-based systems. The efficiency of GitOps is investigated across diverse application domains, ranging from technology startups to highly regulated industries, including banking and healthcare. A comparative analysis is conducted between GitOps-based approaches and traditional CI/CD models. The concluding section outlines future perspectives for the evolution and expansion of GitOps, including standardization efforts, scalability challenges, and the integration of emerging technologies such as artificial intelligence, serverless architectures, and edge computing. This work serves as a practical guideline for organizations seeking to adopt GitOps practices and improve the efficiency and reliability of their operational processes [1].

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References

Tseradze G., Kuchava G., Mantskava M., and Momtselidze N., “Evaluating GitOps Functionality: Efficiency Analysis and Software Enhancement Opportunities,” (in Georgian), Business and Technology University, pp. 175–176, 2025.

Tseradze G., “A Study of GitOps Functionality: Efficiency Analysis and Software Improvement Perspectives,” (in Georgian), Business and Technology University, 50 p., 2025.

C. Davis, GitOps and Kubernetes: Continuous Deployment with Argo CD, Flux, and Friends. Sebastopol, CA, USA: O’Reilly Media, 2021.

G. Kim, J. Humble, P. Debois, and J. Willis, The DevOps Handbook: How to Create World-Class Agility, Reliability, and Security in Technology Organizations. Portland, OR, USA: IT Revolution Press, 2016.

C. Davis, GitOps: Continuous Delivery for Kubernetes. O’Reilly Media, 2021.

T. Winters, T. Manshreck, and H. Wright, Software Engineering at Google: Lessons Learned from Programming Over Time. O’Reilly Media, 2020.

Kuchava G., Kartvelishvili I., and Vashalomidze S., “Using Chaos Engineering to Enhance the Resilience of Microservice Architecture: An Analysis of the ‘Online Boutique’ Case,” (in Georgian), Georgian Technical University, pp. 469–473, 2025.

C. Davis, Cloud Native Patterns: Designing Change-Tolerant Software. Shelter Island, NY, USA: Manning Publications, 2019.

Khinchikashvili A., Kuchava G., and Gaprindashvili A., “Local Area Network Navigation System Software and Hybrid Algorithms for Functionality,” (in Georgian), Business and Technology University, pp. 1–7, 2025.

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Published

26-02-2026

How to Cite

Performance and Efficiency Evaluation of GitOps-Based Deployment Workflows. (2026). Computational and Applied Science, 1(1), 66-85. https://casjournal.ge/index.php/cas/article/view/8