Resilient Cloud Architecture: Automating Security Across Multi-Region AWS Deployments

Authors

  • Pavan Paidy AppSec Lead at FINRA, USA. Author
  • Krishna Chaganti Associate Director at S&P Global, USA. Author

DOI:

https://doi.org/10.63282/3050-9246.IJETCSIT-V5I2P109

Keywords:

Resilient architecture, AWS multi-region, Cloud security, Infrastructure as Code (IaC), Automation, Security orchestration, Compliance, High availability, DevSecOps, Zero trust, AWS Organizations, Disaster recovery

Abstract

Building robust cloud architecture has become more basic in modern IT strategy in an increasingly digital world where high availability & data security are more critical. This paper investigates how companies could achieve resilience & more security in multi-region AWS deployments, which by their very nature provide complexity due to remote resources, different compliance standards & changing threat environments. While manually protecting such settings is resource-intensive, human error is prone in this process, hence automation becomes transforming. Including security assessments, compliance checks, and incident response strategies into the deployment process helps teams to maintain a consistent security posture and stimulate innovation. Several AWS-native & more outside technologies that enable this including AWS Config, Security Hub, GuardDuty & also Infrastructure as Code (IaC) frameworks like Terraform and AWS CloudFormation are examined in this article. It describes how many technologies are coordinated to provide a proactive, self-healing security solution that runs without problems across several areas. This article presents an actual world case study showing how a global company automated security & more compliance across many AWS sites, hence improving uptime & lowering operating expense. Readers might expect realistic insights on building a scalable, resilient cloud architecture integrated with their security one that conforms with regulatory criteria & resists disruptions. Emphasizing automation as a basic feature, this article offers specific strategies for cloud architects, DevSecOps engineers, and IT executives to future-proof their AWS settings

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References

[1] Thumala, Srinivasarao. "Building Highly Resilient Architectures in the Cloud." Nanotechnology Perceptions 16.2 (2020).

[2] Lindén, Oskar. "Cross region cloud redundancy: A comparison of a single-region and a multi-region approach." (2023).

[3] Kupunarapu, Sujith Kumar. "AI-Enabled Remote Monitoring and Telemedicine: Redefining Patient Engagement and Care Delivery." International Journal of Science And Engineering 2.4 (2016): 41-48.

[4] Chaganti, Krishna Chaitanya. "The Role of AI in Secure DevOps: Preventing Vulnerabilities in CI/CD Pipelines." International Journal of Science And Engineering 9.4 (2023): 19-29.

[5] Sangeeta Anand, and Sumeet Sharma. “Role of Edge Computing in Enhancing Real-Time Eligibility Checks for Government Health Programs”. Newark Journal of Human-Centric AI and Robotics Interaction, vol. 1, July 2021, pp. 13-33

[6] Varma, Yasodhara. “Governance-Driven ML Infrastructure: Ensuring Compliance in AI Model Training”. International Journal of Emerging Research in Engineering and Technology, vol. 1, no. 1, Mar. 2020, pp. 20-30

[7] Asthana, Keshri, and Ankur Mittal. Cloud Architecture Demystified: Understand how to design sustainable architectures in the world of Agile, DevOps, and Cloud (English Edition). BPB Publications, 2023.

[8] Kambala, Gireesh. "Designing resilient enterprise applications in the cloud: Strategies and best practices." World Journal of Advanced Research and Reviews 17 (2023): 1078-1094.

[9] Kupunarapu, Sujith Kumar. "AI-Enhanced Rail Network Optimization: Dynamic Route Planning and Traffic Flow Management." International Journal of Science And Engineering 7.3 (2021): 87-95.

[10] Chaganti, Krishna C. "Advancing AI-Driven Threat Detection in IoT Ecosystems: Addressing Scalability, Resource Constraints, and Real-Time Adaptability."

[11] Gallagher, Damien, and Ruth G. Lennon. "Architecting multi-cloud applications for high availability using DevOps." 2022 IEEE International Conference on e-Business Engineering (ICEBE). IEEE, 2022.

[12] Chinamanagonda, Sandeep. "Focus on resilience engineering in cloud services." Academia Nexus Journal 2.1 (2023).

[13] Sangeeta Anand, and Sumeet Sharma. “Automating ETL Pipelines for Real-Time Eligibility Verification in Health Insurance”. Essex Journal of AI Ethics and Responsible Innovation, vol. 1, Mar. 2021, pp. 129-50

[14] Vasanta Kumar Tarra. “Claims Processing & Fraud Detection With AI in Salesforce”. JOURNAL OF RECENT TRENDS IN COMPUTER SCIENCE AND ENGINEERING ( JRTCSE), vol. 11, no. 2, Oct. 2023, pp. 37–53

[15] Sangaraju, Varun Varma, and Senthilkumar Rajagopal. "Applications of Computational Models in OCD." Nutrition and Obsessive-Compulsive Disorder. CRC Press 26-35.

[16] Varma, Yasodhara. “Secure Data Backup Strategies for Machine Learning: Compliance and Risk Mitigation Regulatory Requirements (GDPR, HIPAA, etc.)”. International Journal of Emerging Trends in Computer Science and Information Technology, vol. 1, no. 1, Mar. 2020, pp. 29-38

[17] Berenberg, Anna, and Brad Calder. "Deployment archetypes for cloud applications." ACM Computing Surveys (CSUR) 55.3 (2022): 1-48.

[18] Acharya, Kiran. "Assessing the Resilience of Adaptive Intrusion Prevention Systems in SaaS-Driven E-Retail Ecosystems." Journal of Emerging Cloud Technologies and Cross-Platform Integration Paradigms 6.12 (2022): 1-11.

[19] Oulaaffart, Mohamed. Automating Security Enhancement for Cloud Services. Diss. Université de Lorraine, 2023.

[20] Kupunarapu, Sujith Kumar. "Data Fusion and Real-Time Analytics: Elevating Signal Integrity and Rail System Resilience." International Journal of Science And Engineering 9.1 (2023): 53-61.

[21] Chaganti, Krishna. "Adversarial Attacks on AI-driven Cybersecurity Systems: A Taxonomy and Defense Strategies." Authorea Preprints.

[22] Boscain, Simone. AWS Cloud: Infrastructure, DevOps techniques, State of Art. Diss. Politecnico di Torino, 2023.

[23] Moreno-Vozmediano, Rafael, et al. "Orchestrating the deployment of high availability services on multi-zone and multi-cloud scenarios." Journal of Grid Computing 16 (2018): 39-53.

[24] Vasanta Kumar Tarra, and Arun Kumar Mittapelly. “AI-Driven Fraud Detection in Salesforce CRM: How ML Algorithms Can Detect Fraudulent Activities in Customer Transactions and Interactions”. American Journal of Data Science and Artificial Intelligence Innovations, vol. 2, Oct. 2022, pp. 264-85

[25] 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

[26] Yasodhara Varma. “Scalability and Performance Optimization in ML Training Pipelines”. American Journal of Autonomous Systems and Robotics Engineering, vol. 3, July 2023, pp. 116-43

[27] Aldwyan, Yasser. Intelligent Scaling of Container-based Web Applications in Geographically Distributed Clouds. Diss. University of Melbourne, Parkville, Victoria, Australia, 2021.

[28] Wilkins, Mark. AWS Certified Solutions Architect-Associate (SAA-C02) Cert Guide. Pearson IT Certification, 2021.

[29] Sangeeta Anand, and Sumeet Sharma. “Leveraging ETL Pipelines to Streamline Medicaid Eligibility Data Processing”. American Journal of Autonomous Systems and Robotics Engineering, vol. 1, Apr. 2021, pp. 358-79

[30] Yasodhara Varma. “Graph-Based Machine Learning for Credit Card Fraud Detection: A Real-World Implementation”. American Journal of Data Science and Artificial Intelligence Innovations, vol. 2, June 2022, pp. 239-63

[31] Sangaraju, Varun Varma. "AI-Augmented Test Automation: Leveraging Selenium, Cucumber, and Cypress for Scalable Testing." International Journal of Science And Engineering 7.2 (2021): 59-68.

[32] Vasanta Kumar Tarra, and Arun Kumar Mittapelly. “AI-Powered Workflow Automation in Salesforce: How Machine Learning Optimizes Internal Business Processes and Reduces Manual Effort”. Los Angeles Journal of Intelligent Systems and Pattern Recognition, vol. 3, Apr. 2023, pp. 149-71

[33] Sangaraju, Varun Varma. "Optimizing Enterprise Growth with Salesforce: A Scalable Approach to Cloud-Based Project Management." International Journal of Science And Engineering 8.2 (2022): 40-48.

[34] Chaganti, Krishna C. "Leveraging Generative AI for Proactive Threat Intelligence: Opportunities and Risks." Authorea Preprints.

[35] Mehdi Syed, Ali Asghar, and Erik Anazagasty. “Ansible Vs. Terraform: A Comparative Study on Infrastructure As Code (IaC) Efficiency in Enterprise IT”. International Journal of Emerging Trends in Computer Science and Information Technology, vol. 4, no. 2, June 2023, pp. 37-48

[36] Sangaraju, Varun Varma. "Ranking Of XML Documents by Using Adaptive Keyword Search." (2014): 1619-1621.

[37] Vasanta Kumar Tarra, and Arun Kumar Mittapelly. “Voice AI in Salesforce CRM: The Impact of Speech Recognition and NLP in Customer Interaction Within Salesforce’s Voice Cloud”. Newark Journal of Human-Centric AI and Robotics Interaction, vol. 3, Aug. 2023, pp. 264-82

[38] Narani, Sandeep Reddy, Madan Mohan Tito Ayyalasomayajula, and Sathishkumar Chintala. "Strategies For Migrating Large, Mission-Critical Database Workloads To The Cloud." Webology (ISSN: 1735-188X) 15.1 (2018).

[39] Mehdi Syed, Ali Asghar. “Hyperconverged Infrastructure (HCI) for Enterprise Data Centers: Performance and Scalability Analysis”. International Journal of AI, BigData, Computational and Management Studies, vol. 4, no. 4, Dec. 2023, pp. 29-38

[40] Sangeeta Anand, and Sumeet Sharma. “Leveraging AI-Driven Data Engineering to Detect Anomalies in CHIP Claims”. Los Angeles Journal of Intelligent Systems and Pattern Recognition, vol. 1, Apr. 2021, pp. 35-55

[41] Sangaraju, Varun Varma, and Senthilkumar Rajagopal. "Danio rerio: A Promising Tool for Neurodegenerative Dysfunctions." Animal Behavior in the Tropics: Vertebrates: 47.

[42] Yasodhara Varma, and Manivannan Kothandaraman. “Leveraging Graph ML for Real-Time Recommendation Systems in Financial Services”. Essex Journal of AI Ethics and Responsible Innovation, vol. 1, Oct. 2021, pp. 105-28

[43] 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.

[44] Vasanta Kumar Tarra, and Arun Kumar Mittapelly. “Data Privacy and Compliance in AI-Powered CRM Systems: Ensuring GDPR, CCPA, and Other Regulations Are Met While Leveraging AI in Salesforce”. Essex Journal of AI Ethics and Responsible Innovation, vol. 4, Mar. 2024, pp. 102-28

[45] Chaganti, Krishna Chaitanya. "AI-Powered Threat Detection: Enhancing Cybersecurity with Machine Learning." International Journal of Science And Engineering 9.4 (2023): 10-18.

[46] Kovalenko, Elena. "Advancements in Cloud-Based Infrastructure for Scalable Data Storage: Challenges and Future Directions in Distributed Systems." International Journal of AI, BigData, Computational and Management Studies 1.1 (2020): 12-20.

Published

2024-06-30

Issue

Section

Articles

How to Cite

1.
Paidy P, Chaganti K. Resilient Cloud Architecture: Automating Security Across Multi-Region AWS Deployments. IJETCSIT [Internet]. 2024 Jun. 30 [cited 2025 Oct. 3];5(2):82-93. Available from: https://www.ijetcsit.org/index.php/ijetcsit/article/view/167

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