Designing Cloud-Native Enterprise Systems by Modernizing Applications with Microservices and Kubernetes Platforms

Dr.Vimal Raja Gopinathan

doi:10.15662/IJRAI.2025.0805015

Authors

Dr.Vimal Raja Gopinathan Senior Principal Consultant, Oracle Financial Service Software Ltd, Washington, USA Author

DOI:

https://doi.org/10.15662/IJRAI.2025.0805015

Keywords:

Cloud-native, Microservices, Kubernetes, Application Modernization, Containerization, Enterprise Systems, Distributed Systems

Abstract

The growing need to scale, make enterprise systems efficient and flexible has led to the implementation of cloud-native architecture, micro-service and containerization platforms such as Kubernetes. In this research article, the authors investigate how cloud-native enterprise systems are designed through the upgrading of the legacy application using microservices and their implementation on Kubernetes platforms. It is a detailed architecture of how to re-architecture monolith applications into a distributed system based on microservices that are more scalable, maintainable and have fault tolerance. The paper discusses major aspects of this modernization process, e.g., service decomposition, containerization, orchestration, and deployment strategies. It also emphasizes the use of Kubernetes to orchestrate the containers, which allows automatic scaling, self-healing and deployment of microservices. The article provides case studies and real life examples to illustrate how this approach has been effective in the enterprise world setting. Other issues that the research touches upon are the issues of data consistency, security and the difficulties of the administration of distributed systems. Finally, the work is a useful source of information to organizations that need to modernize their applications and be cloud-native to remain competitive in the rapidly changing world of technology

References

[1] D. Balla, C. Simon, and M. Maliosz, "Adaptive scaling of Kubernetes pods," IEEE/IFIP Network Operations and Management Symposium, pp. 1–5, 2020.

[2] S. Chintalapudi, "A playbook for enterprise application modernization using microservices and headless CMS," International Journal of Engineering & Extended Technologies Research (IJEETR), vol. 7, no. 4, pp. 10293–10302, 2025.

[3] L. Toka, G. Dobreff, B. Fodor, and B. Sonkoly, "Machine learning-based scaling management for Kubernetes edge clusters," IEEE Trans. Network and Service Management, vol. 18, no. 1, pp. 958–972, 2021.

[4] Ponugoti, M. (2022). Integrating full-stack development with regulatory compliance in enterprise systems architecture. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(2), 6550–6563

[5] Z. Ding and Q. Huang, "COPA: A combined autoscaling method for Kubernetes," IEEE Int. Conf. on Web Services (ICWS), pp. 416–425, 2021.

[6] Q. T. Nguyen, et al., "Horizontal autoscaling in Kubernetes using custom metrics," Int. J. of Cloud Computing, vol. 12, no. 4, pp. 325–337, 2022.

[7] A. Abdel Khaleq and I. Ra, "Intelligent microservices autoscaling module using reinforcement learning," Cluster Computing, pp. 1–12, 2023.

[8] Sriramoju, S. (2024). Designing scalable and fault-tolerant architectures for cloud-based integration platforms. International Journal of Future Innovative Science and Technology (IJFIST), 7(6), 13839–13851.

[9] V. K. Sharma and D. G. Thakur, "Dynamic Resource Management in Kubernetes Using Multi-Metric Evaluation," WSEAS Trans. on Computers, vol. 21, pp. 202–211, 2022.

[10] A. P. Dimitrov and I. D. Nikolov, "Observability-Driven Scaling Policies in Cloud Platforms," WSEAS Trans. on Systems and Control, vol. 17, pp. 155–165, 2023.

[11] Surisett, L. S. (2024). AI-driven API security: Architecting resilient gateways for hybrid cloud ecosystems. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(1), 9964–9974

[12] M. S. Elkhodr and N. Ali, "Adaptive Load Management in Containerized Systems," WSEAS Trans. on Information Science and Applications, vol. 20, pp. 111–120, 2024.

[13] L. Baresi and G. Quattrocchi, "COCOS: A scalable architecture for containerized heterogeneous systems," IEEE Int. Conf. on Software Architecture, pp. 103–113, 2020.

[14] Anumula, S. R. (2023). Resilience engineering for intelligent enterprise platforms. International Journal of Engineering & Extended Technologies Research (IJEETR), 5(1), 5954–5965.

[15] J. Santos, T. Wauters, B. Volckaert, and F. De Turck, "gym-hpa: Efficient auto-scaling via reinforcement learning," NOMS, IEEE, pp. 1–9, 2023.

[16] B. C. Vadde and V. B. Munagandla, "Cloud-Native DevOps: Leveraging Microservices and Kubernetes for Scalable Infrastructure," Int. J. of Machine Learning Research in Cybersecurity and Artificial Intelligence, vol. 15, no. 1, pp. 545–554, 2023.