Migrating Legacy Ecommerce Systems to the Cloud: A Step-by-Step Guide
Keywords:
Legacy systems, cloud migration, microservices, CI/CD-driven cloud adoption roadmapAbstract
Usually based on antiquated monolithic structures, legacy e-commerce systems pose major obstacles in the dynamic, customer-oriented digital economy of today. These systems could be stiff, costly to operate, and incapable of allowing the scalability and agility required by contemporary businesses. Cloud migration is a convincing replacement since it allows companies to meet changing client expectations, improve performance, and inspire innovation. Still, cloud migration has hazards. Data integrity problems, transient downtime, regulatory limits, and organizational resistance all help to complicate the process. This document aims to provide technology executives and solution architects a clear, sensible framework to negotiate this transformation. It describes a whole, thorough migration methodology from evaluating legacy system constraints and defining cloud migration objectives to selecting the appropriate cloud model, using phased transitions, and enhancing post-migration performance. Combined throughout are useful lessons gained from a case study showing the development of a mid-sized retail platform to a hybrid cloud architecture. The book clarifies the "how" and the "why" of major decisions by combining technical aspects with strategic planning guidance. Ultimately, readers will have a good awareness of managing a cloud migration project, lowering risks, and optimizing long-term business value—which will enable them to guide their businesses through a significant digital era technical transition.
Downloads
References
Beserra, Patricia V., et al. "Cloudstep: A step-by-step decision process to support legacy application migration to the cloud." 2012 IEEE 6th international workshop on the maintenance and evolution of service-oriented and cloud-based systems (MESOCA). IEEE, 2012.
Linthicum, David S. Cloud computing and SOA convergence in your enterprise: a step-by-step guide. Pearson Education, 2009.
Thumburu, Sai Kumar Reddy. "Transforming Legacy EDI Systems: A Comprehensive Migration Guide." Journal of Innovative Technologies 5.1 (2022).
Scandurra, Patrizia, et al. "Challenges and assessment in migrating IT legacy applications to the cloud." 2015 IEEE 9th International Symposium on the Maintenance and Evolution of Service-Oriented and Cloud-Based Environments (MESOCA). IEEE, 2015.
Nosyk, Yevheniya. "Migration of a legacy web application to the cloud." (2018).
Varma, Yasodhara. “Scaling AI: Best Practices in Designing On-Premise & Cloud Infrastructure for Machine Learning”. International Journal of AI, BigData, Computational and Management Studies, vol. 4, no. 2, June 2023, pp. 40-51
Laszewski, Tom, and Prakash Nauduri. Migrating to the cloud: Oracle client/server modernization. Elsevier, 2011.
Paidy, Pavan. “Adaptive Application Security Testing With AI Automation”. International Journal of AI, BigData, Computational and Management Studies, vol. 4, no. 1, Mar. 2023, pp. 55-63
Gholami, Mahdi Fahmideh, et al. "Cloud migration process—A survey, evaluation framework, and open challenges." Journal of Systems and Software 120 (2016): 31-69.
Chaganti, Krishna. "Adversarial Attacks on AI-driven Cybersecurity Systems: A Taxonomy and Defense Strategies." Authorea Preprints.
da Silva Costa, Ana Gabriela. "Analysis of the Requirements and Methods of Cloud Migration to SaaS Model." (2021).
Vasanta Kumar Tarra, and Arun Kumar Mittapelly. “Predictive Analytics for Risk Assessment & Underwriting”. JOURNAL OF RECENT TRENDS IN COMPUTER SCIENCE AND ENGINEERING ( JRTCSE), vol. 10, no. 2, Oct. 2022, pp. 51-70
Opara-Martins, Justice. A decision framework to mitigate vendor lock-in risks in cloud (SaaS category) migration. Diss. Bournemouth University, 2017.
Sangeeta Anand, and Sumeet Sharma. “Big Data Security Challenges in Government-Sponsored Health Programs: A Case Study of CHIP”. American Journal of Data Science and Artificial Intelligence Innovations, vol. 1, Apr. 2021, pp. 327-49
Nalla, Kiran Kumar. "Navigating digital transformation: Best practices for cloud migration strategies in the enterprise." (2022).
Syed, Ali Asghar Mehdi, and Erik Anazagasty. “Hybrid Cloud Strategies in Enterprise IT: Best Practices for Integrating AWS With on-Premise Datacenters”. American Journal of Data Science and Artificial Intelligence Innovations, vol. 2, Aug. 2022, pp. 286-09
Kupunarapu, Sujith Kumar. "AI-Driven Crew Scheduling and Workforce Management for Improved Railroad Efficiency." International Journal of Science And Engineering 8.3 (2022): 30-37.
Rosado, David G., et al. "Security analysis in the migration to cloud environments." Future Internet 4.2 (2012): 469-487.
Paidy, Pavan. “Scaling Threat Modeling Effectively in Agile DevSecOps”. American Journal of Data Science and Artificial Intelligence Innovations, vol. 1, Oct. 2021, pp. 556-77
Hernández, José Antonio, Ammar Hasayen, and Javier Aguado. Cloud migration handbook Vol. 1: A practical guide to successful cloud adoption and migration. Lulu. com, 2019.
Veluru, Sai Prasad. “Real-Time Model Feedback Loops: Closing the MLOps Gap With Flink-Based Pipelines”. American Journal of Data Science and Artificial Intelligence Innovations, vol. 1, Feb. 2021, pp. 485-11
Alkhalil, Adel. A Model to support the decision process for migration to cloud computing. Diss. Bournemouth University, 2016.
Sangaraju, Varun Varma. "AI-Augmented Test Automation: Leveraging Selenium, Cucumber, and Cypress for Scalable Testing." International Journal of Science And Engineering 7 (2021): 59-68
Atluri, Anusha. “Breaking Barriers With Oracle HCM: Creating Unified Solutions through Custom Integrations ”. Essex Journal of AI Ethics and Responsible Innovation, vol. 1, Aug. 2021, pp. 247-65
Anoshin, Dmitry, Dmitry Shirokov, and Donna Strok. Jumpstart Snowflake: a step-by-step guide to modern cloud analytics. Apress, 2020.
Cardoso, Abílio. Applicability of it service management in the migration to cloud computing. Diss. Universidade Portucalense (Portugal), 2015.