Data Migration Strategies for Cloud-Native Applications: A Framework for Large-Scale Enterprises

Authors

  • Dr. Bhavesh Patel Independent Researcher, USA. Author

Keywords:

Cloud Native, Design Patterns, (SecaaS) Applications, Interclouds, Infrastructure, Delivery Models, Micro Service, Cutting-Edge Techniques

Abstract

Cloud-native computing emerges as a result of the growth of cloud computing delivery paradigms. As the most important online application development paradigm, cloud native computing has already garnered more and more interest from both business and academics. A defined research path on this issue is still lacking, despite the enthusiasm in the cloud-native industrial community. Adoption of state-of-the-art methods, technologies, frameworks, tools, and infrastructure is necessary for the creation of contemporary software applications. Although each category offers a wide range of alternatives, the common features include reduced cost, lightweight and scalable applications, and quicker delivery. Furthermore, testing, deployment, and operational automation have grown in importance. Considering how accessible and reasonably priced data is, cloud computing has a lot to offer. Because users often store sensitive data in cloud storage providers, which may not be trustworthy, ensuring cloud data security is an important consideration in the world of cloud computing. There is now a tendency towards "interclouds," also known as "multi-clouds" or "cloud-of-clouds." The organisation will see significant growth and profitability if it can operate cloud-native apps. The impact of cloud native security on business outcomes is significant. The architecture of cloud-native security is also covered in this article. This article highlights the new methods for creating and implementing Security-as-a-Service (SecaaS) applications leveraging cloud-native design paradigms. The immediate threat to computer systems and applications is not adequately addressed by the most recent SecaaS solutions. This issue is resolved by cloud-native design patterns, which combine micro service architectures with cloud-focused interface design to provide features like substantial optimisation and durability.

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References

[1] Voola, Pramod Kumar, Krishna Gangu, Pandi Kirupa Gopalakrishna, Punit Goel, & Arpit Jain. (2021). "AIDriven Predictive Models in Healthcare: Reducing Time-to-Market for Clinical Applications." International Journal of Progressive Research in Engineering Management and Science, 1(2): 118-129.

[2] Agrawal, Shashwat, Pattabi Rama Rao Thumati, Pavan Kanchi, Shalu Jain, & Raghav Agarwal. (2021). "The Role of Technology in Enhancing Supplier Relationships." International Journal of Progressive Research in Engineering Management and Science, 1(2): 96-106.

[3] Mahadik, Siddhey, Raja Kumar Kolli, Shanmukha Eeti, Punit Goel, & Arpit Jain. (2021). "Scaling Startups through Effective Product Management." International Journal of Progressive Research in Engineering Management and Science, 1(2): 68-81.

[4] Arulkumaran, Rahul, Shreyas Mahimkar, Sumit Shekhar, Aayush Jain, & Arpit Jain. (2021). "Analyzing Information Asymmetry in Financial Markets Using Machine Learning." International Journal of Progressive Research in Engineering Management and Science, 1(2): 53-67.

[5] Agarwal, Nishit, Umababu Chinta, Vijay Bhasker Reddy Bhimanapati, Shubham Jain, & Shalu Jain. (2021). "EEG Based Focus Estimation Model for Wearable Devices." International Research Journal of Modernization in Engineering, Technology and Science, 3(11): 1436.

[6] Kolli, R. K., Goel, E. O., & Kumar, L. (2021). "Enhanced Network Efficiency in Telecoms." International Journal of Computer Science and Programming, 11(3), Article IJCSP21C1004.

[7] Eeti, E. S., Jain, E. A., & Goel, P. (2020). Implementing data quality checks in ETL pipelines: Best practices and tools. International Journal of Computer Science and Information Technology, 10(1), 31-42.

[8] Venkata Ramanaiah Chintha, Priyanshi, Prof.(Dr) Sangeet Vashishtha, "5G Networks: Optimization of Massive MIMO", IJRAR - International Journal of Research and Analytical Reviews (IJRAR), E-ISSN 2348- 1269, P- ISSN 2349-5138, Volume.7, Issue 1, Page No pp.389-406, February2020.

[9] Cherukuri, H., Pandey, P., & Siddharth, E. (2020). Containerized data analytics solutions in on-premise financial services. International Journal of Research and Analytical Reviews (IJRAR), 7(3), 481-491.

[10] N. Naik, “Building a virtual system of systems using docker swarm in multiple clouds,” in 2016 IEEE International Symposium on Systems Engineering (ISSE). IEEE, 2016, pp. 1–3.

[11] V. K. Vavilapalli, A. C. Murthy, C. Douglas, S. Agarwal, M. Konar, R. Evans, T. Graves, J. Lowe, H. Shah, S. Seth et al., “Apache hadoop yarn: Yet another resource negotiator,” in Proceedings of the 4th annual Symposium on Cloud Computing, 2013, pp. 1–16.

[12] W. Li, Y. Lemieux, J. GAO, Z. Zhao, and Y. Han, “Service mesh: Challenges, state of the art, and future research opportunities,” in 2019 IEEE International Conference on Service-Oriented System Engineering (SOSE). IEEE, 2019, pp. 122–1225.

[13] F. Soppelsa and C. Kaewkasi, Native docker clustering with swarm. Packt Publishing Ltd, 2016.

[14] F. Liu, G. Tang, Y. Li, Z. Cai, X. Zhang, and T. Zhou, “A survey on edge computing systems and tools,” Proceedings of the IEEE, vol. 107, no. 8, pp. 1537–1562, 2019.

[15] W. Xu, “Test report on kubeedge’s support for 100,000 edge nodes,” 2022.

[16] R. Morabito, J. Kjällman, and M. Komu, “Hypervisors vs. lightweight virtualization: a performance comparison,” in 2015 IEEE International Conference on cloud engineering. IEEE, 2015, pp. 386–393.

[17] K. Kushwaha and N. Center, “How container runtimes matter in kubernetes?” 2017. [28] D. B. Rawat and S. R. Reddy, “Software defined networking architecture, security and energy efficiency: A survey,” IEEE Communications Surveys & Tutorials, vol. 19, no. 1, pp. 325–346, 2016.

[18] J. Deng, H. Hu, H. Li, Z. Pan, K.-C. Wang, G.-J. Ahn, J. Bi, and Y. Park, “Vnguard: An nfv/sdn combination framework for provisioning and managing virtual firewalls,” in 2015 IEEE Conference on Network Function Virtualization and Software Defined Network (NFVSDN). IEEE, 2015, pp. 107–114.

[19] M. A. Harrabi, M. Jeridi, N. Amri, M. R. Jerbi, A. Jhine, and H. Khamassi, “Implementing nfv routers and sdn controllers in mpls architecture,” in 2015 World Congress on Information Technology and Computer Applications (WCITCA). IEEE, 2015, pp. 1–6.

[20] M. Mahalingam, D. Dutt, K. Duda, P. Agarwal, L. Kreeger, T. Sridhar, and C. W. Mike Bursell, “Virtual extensible local area network (vxlan): A framework for overlaying virtualized layer 2 networks over layer 3 networks,” 2020.

[21] Sumit Shekhar, SHALU JAIN, DR. POORNIMA TYAGI, "Advanced Strategies for Cloud Security and Compliance: A Comparative Study", IJRAR - International Journal of Research and Analytical Reviews (IJRAR), E-ISSN 2348-1269, P- ISSN 2349-5138, Volume.7, Issue 1, Page No pp.396-407, January 2020.

[22] Adams, R., & Thomas, J. (2018). "Best Practices in Data Migration: A Review of the Literature." Journal of Data Management, 12(4), 245-260.

[23] Brown, L. M., & Smith, P. (2021). "Automation in Data Migration: Tools and Techniques." International Journal of Information Systems, 29(3), 145-162.

[24] Chen, Y., & Liu, H. (2019). "Challenges in Cross-Platform Data Migration: A Case Study." Journal of Enterprise Information Management, 32(2), 230-245.

[25] Garcia, M. (2022). "Leveraging Cloud Technologies for Effective Data Migration." Cloud Computing Review, 15(1), 85-102.

[26] Armbrust, M., Fox, A., Griffith, R., & Patterson, D. A. (2010). Above the clouds: A Berkeley view of cloud computing. ACM Transactions on Computer Systems (TOCS), 28(1), 1-4.

[27] Dean, J., & Ghemawat, S. (2008, December). MapReduce: Simplified data processing on large clusters. Communications of the ACM, 51(1), 107-113.

[28] Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT press.

[29] James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112). Springer.

[30] Mao, M., & Liu, Y. (2016). Review of research on cloud data migration. Journal of Computer and Communications, 4(2), 84-90.

[31] Mell, P., & Grance, T. (2011). The NIST definition of cloud computing (Special Publication 800-145). National Institute of Standards and Technology.

[32] Fehling, C., et al., Cloud computing patterns: fundamentals to design, build, and manage cloud applications. 2014: Springer. 14. Stine, M., Migrating to cloud-native application architectures. 2015: O'Reilly Media.

[33] Balalaie, A., A. Heydarnoori, and P. Jamshidi. Migrating to cloud-native architectures using micro services: an experience report. In European Conference on Service-Oriented and Cloud Computing. 2015. Springer.

[34] Dmitry, N. and S.-S. Manfred, On micro-services architecture. International Journal of Open Information Technologies, 2014. 2(9).

[35] Rahman, A.A.U. and L. Williams. Software security in devops: Synthesizing practitioners’ perceptions and practices. in 2016 IEEE/ACM International Workshop on Continuous Software Evolution and Delivery (CSED). 2016. IEEE.

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Published

2025-02-25

Issue

Section

Original Research Articles

How to Cite

Data Migration Strategies for Cloud-Native Applications: A Framework for Large-Scale Enterprises. (2025). International Journal of Artificial Intelligence, Computer Science, Management and Technology, 2(1), 32-46. https://ijacmt.com/index.php/j/article/view/18

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