Volume 2 Issue 1 | 2025 | View PDF
Paper Id:IJMSM-V2I1P110
doi: 10.71141/30485037/V2I1P110

PostgreSQL in the Kubernetes Ecosystem: Deployments and Management Strategies

Suresh Babu avula, Harsha Vardhan Reddy Kavuluri

Citation:
Suresh Babu avula, Harsha Vardhan Reddy Kavuluri, "PostgreSQL in the Kubernetes Ecosystem: Deployments and Management Strategies" International Journal of Multidisciplinary on Science and Management, Vol. 2, No. 1, pp. 94-103, 2025.

Abstract:
An open-source relational database with many users is PostgreSQL, which is reliable, extensible and compliant with SQL standards. The advent of container orchestration platforms like Kubernetes has completely transitioned database management to a magnitude we never knew before, with automated scaling, fault tolerance, and the use of resources. This paper details some deployment strategies for PostgreSQL in the Kubernetes ecosystem and discusses methods to manage such deployments and some optimization approaches. On Kubernetes, we give an in-depth analysis of supported Kubernetes-based PostgreSQL cluster configurations, High availability (HA), storage space, backup and recovery, and monitoring. We also talk about security practices and how to tune for performance and recover from a disaster. We then showcase the benefits and the deficiencies of the available PostgreSQL deployment tools by comparing Helm Charts, Operators (CrunchyData, Zalando) and StatefulSets. We also report on experimental results that show the effect of the different storage backends, resource allocation strategies and failover mechanisms on database performance. The findings suggest that Kubernetes is a powerful yet complex platform for PostgreSQL, and ensuring efficiency and reliability can only be done through strategic planning and specialized tools. We finish with recommendations for organizations interested in running Kubernetes for PostgreSQL deployments in production environments.

Keywords: PostgreSQL, Kubernetes, Database Management, High Availability, StatefulSets, Operators, Helm Charts.

References:
1. Karslioglu, M. (2020). Kubernetes-A Complete DevOps Cookbook: Build and manage your applications, orchestrate containers, and deploy cloud-native services. Packt Publishing Ltd.
2. Sivaraman, P., Prabaharan, G., Rajasekar, V., & Sarveshwaran, V. (2024, August). Efficient Auto Scaling of Pods in Kubernetes: Accelerating Continuous Delivery with KEPTN. In 2024 5th International Conference on Electronics and Sustainable Communication Systems (ICESC) (pp. 1350-1355). IEEE.
3. Sayfan, G. (2019). Hands-On Microservices with Kubernetes: Build, deploy, and manage scalable microservices on Kubernetes. Packt Publishing Ltd.
4. Khan, H. H., Zubair, S., Nasim, F., Akhter, S., Ghazanfar, M. N., & Azeem, S. (2024). Role of Kubernetes in DevOps Technology for the Effective Software Product Management. Journal of Computing & Biomedical Informatics, 7(01), 313-327.
5. Li, Z., Saldías-Vallejos, N., Rodríguez, M. A., & Rainer, A. (2022, December). On Kubernetes-aided Federated Database Systems. In 2022 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) (pp. 1-8). IEEE.
6. Using Kubernetes to Deploy PostgreSQL, Sereral, 2018. online. https://severalnines.com/blog/using-kubernetes-deploy-postgresql/
7. Weissman, B., & Nocentino, A. E. (2022). A Kubernetes Primer. In Azure Arc-enabled Data Services Revealed: Deploying Azure Data Services on Any Infrastructure (pp. 1-23). Berkeley, CA: Apress.
8. Shah, J., & Dubaria, D. (2019, January). Building modern clouds: using docker, kubernetes, and Google cloud platform. In 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 0184-0189). IEEE.
9. Perera, H. C. S., De Silva, T. S. D., Wasala, W. M. D. C., Rajapakshe, R. M. P. R. L., Kodagoda, N., Samaratunge, U. S. S., & Jayanandana, H. H. N. C. (2021, December). Database scaling on Kubernetes. In 2021 3rd International Conference on Advancements in Computing (ICAC) (pp. 258-263). IEEE.
10. Mehta, P. S. (2023). NoSQL databases in Kubernetes.
11. Vadlamani, V. (2024). PostgreSQL on Docker. In PostgreSQL Skills Development on Cloud (pp. 249-282). Apress, Berkeley, CA.
12. PostgreSQL Deployment in Kubernetes | The Complete Guide, Xenosnstock, online. https://www.xenonstack.com/blog/postgresql-deployment
13. Christudas, B. A. (2024). Microservices with Kubernetes. In Java Microservices and Containers in the Cloud: With Spring Boot, Kafka, PostgreSQL, Kubernetes, Helm, Terraform and AWS EKS (pp. 455-523). Berkeley, CA: Apress.
14. Mega, C. (2023, June). Orchestrating Information Governance Workloads as Stateful Services Using Kubernetes Operator Framework. In Symposium and Summer School on Service-Oriented Computing (pp. 125-143). Cham: Springer Nature Switzerland.
15. Vayghan, L. A., Saied, M. A., Toeroe, M., & Khendek, F. (2021). A Kubernetes controller for managing the availability of elastic microservice-based stateful applications. Journal of Systems and Software, 175, 110924.
16. Stanik, A., Höger, M., & Kao, O. (2013, December). Failover pattern with a self-healing mechanism for high availability cloud solutions. In 2013 International Conference on Cloud Computing and Big Data (pp. 23-29). IEEE.
17. Sharma, A. (2023). Evaluate Kubernetes for Stateful and highly available enterprise database solutions (Master's thesis, Oslomet-storbyuniversitetet).
18. Thomas, S. M. (2017). PostgreSQL High Availability Cookbook. Packt Publishing Ltd.
19. Recommended Approach for PostgreSQL in Kubernetes, Medium, online. https://medium.com/@simardeep.oberoi/recommended-approach-for-postgresql-in-kubernetes-83f6acc65303
20. Javadpour, A., Ja’Fari, F., Taleb, T., Benzaïd, C., Rosa, L., Tomás, P., & Cordeiro, L. (2024, September). Deploying Testbed Docker-based application for Encryption as a Service in Kubernetes. In 2024 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) (pp. 1-7). IEEE.
21. P. Mannem, R. Daruvuri, and K. K. Patibandla, “Leveraging Supervised Learning in Cloud Architectures for Automated Repetitive Tasks.,” International Journal of Innovative Research in Science,Engineering and Technology, vol. 13, no. 10, pp. 18127–18136, Oct. 2024, doi: 10.15680/ijirset.2024.1311004.