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ANALYSIS AND COMPARISON OF CONTAINER ORCHESTRATION TOOLS IN ON-PREMISES AND CLOUD INFRASTRUCTURE

https://doi.org/10.55452/1998-6688-2026-23-1-22-36

Abstract

In large-scale cloud environments, virtualization plays a key role not only in application deployment and workload distribution but also in the effective management of platform services and resources. The use of containerization technology, alongside traditional approaches such as virtual machines, is becoming increasingly popular in modern cloud infrastructures. Containers provide a simpler and faster method of virtualization compared to virtual machines, accelerating the deployment and management of applications in isolated environments and thereby enabling more efficient resource utilization. For developers, containers offer a convenient solution for testing application components and building microservice-based architectures. As a result, containerization is becoming the preferred solution for modern cloud environments and current business needs. Therefore, this study is dedicated to examining modern and widely recognized container technologies. The article analyzes contemporary containerization and orchestration technologies using parameters such as container performance, scalability, and resource management. Particular attention is given to orchestrators such as Docker Swarm, Kubernetes, and Apache Mesos, as well as a range of container-based solutions, with an evaluation of the advantages and disadvantages of each technology. This work may be useful for IT specialists in selecting the most appropriate tools for application development and the implementation of their cloud strategies.

About the Authors

L. T. Kussepova
L.N. Gumilyov Eurasian National University,
Kazakhstan

Senior lecturer

Astana



G. T. Kussepova
L.N. Gumilyov Eurasian National University
Kazakhstan

Senior lecturer, PhD

Astana



References

1. Malviya, A., Dwivedi, R.K. A comparative analysis of container orchestration tools in cloud computing. 2022 9th International Conference on Computing for Sustainable Global Development (INDIACom) (IEEE, 2022), pp. 698–703. https://doi.org/10.23919/INDIACom54597.2022.9763171.

2. Kumar, R., Trivedi, M.C. Networking analysis and performance comparison of Kubernetes CNI plugins. Advances in Computer, Communication and Computational Sciences: Proceedings of IC4S 2019 (Springer Singapore, 2021), pp. 99–109.

3. Atlidakis, V., Godefroid, P., Polishchuk, M. Checking security properties of cloud service REST APIs. 2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST) (IEEE, 2020), pp. 387–397.

4. Pankowski, A., Powroźnik, P. Comparison of application container orchestration platforms. Journal of Computer Sciences Institute, 29, 383–390 (2023). https://doi.org/10.35784/jcsi.3823.

5. Acharya J.N., Suthar A.C. Docker container orchestration management: A review. International Conference on Intelligent Vision and Computing. Cham: Springer International Publishing, 2021, pp. 140–153. https://doi.org/10.1007/978-3-030-97196-0_12.

6. Moravcik, M., Segec, P., Kontsek, M., Uramova, J., & Papan, J. Comparison of lxc and docker technologies. 2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA) (IEEE, 2020), pp. 481–486. https://doi.org/10.1109/ICETA51985.2020.9379212.

7. Putri, A.R., Munadi, R., Negara, R.M. Performance analysis of multi services on container Docker, LXC, and LXD. Bulletin of Electrical Engineering and Informatics, 9(5), 2008–2011. https://doi.org/10.11591/eei.v9i5.1953.

8. Koziolek, H., Eskandani, N. Lightweight kubernetes distributions: A performance comparison of microk8s, k3s, k0s, and microshift. Proceedings of the 2023 ACM/SPEC International Conference on Performance Engineering, 2023, pp. 17–29. https://doi.org/10.1145/3578244.3583737.

9. Mercl, L., Pavlik, J. The comparison of container orchestrators. Third International Congress on Information and Communication Technology: ICICT 2018, London (Springer Singapore, 2019), pp. 677–685. https://doi.org/10.1007/978-981-13-1165-9_62.

10. Sen, A., Madria, S. Analysis of a cloud migration framework for offline risk assessment of cloud service providers. Software: Practice and Experience, 50(6), 998–1021 (2020).

11. Liu, Q. et al. PQA-Net: Deep no reference point cloud quality assessment via multi-view projection. IEEE transactions on circuits and systems for video technology, 31(12), 4645–4660 (2021).

12. Liu, Y. et al. Point cloud quality assessment: Dataset construction and learning-based no-reference metric. ACM Transactions on Multimedia Computing, Communications and Applications, 19(2s), 1–26 (2023).

13. Wang, S. et al. Non-local geometry and color gradient aggregation graph model for no-reference point cloud quality assessment. Proceedings of the 31st ACM International Conference on Multimedia, 2023, pp. 6803–6810.

14. Liu, P., Guitart, J. Performance comparison of multi-container deployment schemes for HPC workloads: an empirical study. The Journal of Supercomputing, 77(6), 6273–6312 (2021). https://doi.org/10.1007/s11227-020-03518-1.

15. Abraham, S., Paul, A.K., Khan, R.I.S., & Butt, A.R. On the use of containers in high performance computing environments. 2020 IEEE 13th International Conference on Cloud Computing (CLOUD) (IEEE, 2020), pp. 284–293. https://doi.org/10.1109/CLOUD49709.2020.00048.

16. Wong A.Y. et al. Threat modeling and security analysis of containers: A survey. arXiv preprint arXiv:2111.11475, 2021.

17. Parast F.K. et al. Cloud computing security: A survey of service-based models. Computers & Security, 114, 102580 (2022).

18. Zhang C. et al. Interval-valued intuitionistic uncertain linguistic cloud petri net and its application to risk assessment for subway fire accident. IEEE transactions on automation science and engineering, 19(1), 163–177 (2020).

19. Sen, A., Madria, S. Application design phase risk assessment framework using cloud security domains. Journal of Information Security and Applications, 55, 102617 (2020).

20. Ferreira, A.P., Sinnott, R. A performance evaluation of containers running on managed kubernetes services. 2019 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) (IEEE, 2019), pp. 199–208.


Review

For citations:


Kussepova L.T., Kussepova G.T. ANALYSIS AND COMPARISON OF CONTAINER ORCHESTRATION TOOLS IN ON-PREMISES AND CLOUD INFRASTRUCTURE. Herald of the Kazakh-British Technical University. 2026;23(1):22-36. (In Russ.) https://doi.org/10.55452/1998-6688-2026-23-1-22-36

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ISSN 1998-6688 (Print)
ISSN 2959-8109 (Online)