Infrastructure as Code (IaC) for Enterprise Cloud Migrations: Cost and Performance Optimization Strategies

Authors

  • Swetha Ravipudi Lucid Motors, USA Author
  • Gnanendra Reddy Muthirevula Tekvana Inc, USA Author
  • Vincent Kanka , Homesite, USA Author

Keywords:

Infrastructure as Code, cloud migration, performance optimization

Abstract

Infrastructure as Code (IaC) is emerged as a crucial model for enterprises undertaking cloud migration to AWS, Azure, or Google Cloud Platform (GCP), which enables automation, scalability, and cost efficiency. By utilising IaC tools like Terraform, Ansible, and AWS CloudFormation, Companies can achieve consistent infrastructure supply which reduces configuration drift and enhance deployment agility. The objective of this paper is to explore the role of IaC in optimising utilisation of cloud resources. This paper also focuses on cost reduction and performance enhancements strategies.

Downloads

Download data is not yet available.

References

M. Hüttermann, Infrastructure as Code: Managing Servers in the Cloud, 2nd ed.

Sebastopol, CA, USA: O’Reilly Media, 2021.

George, Jabin Geevarghese. "Advancing Enterprise Architecture for Post-Merger

Financial Systems Integration in Capital Markets laying the Foundation for Machine

Learning Application." Aus. J. ML Res. & App 3.2 (2023): 429.

Dash, S. "Architecting Intelligent Sales and Marketing Platforms: The Role of

Enterprise Data Integration and AI for Enhanced Customer Insights." Journal of

Artificial Intelligence Research 3.2 (2023): 253-291.

Singu, Santosh Kumar. "Migration strategies for legacy data warehousing systems to

cloud platforms." Internafional Journal of Science and Research (IJSR) 12, no. 12

(2023): 2164-2167.

George, Jabin Geevarghese. "HARNESSING GENERATIVE AI FOR ENTERPRISE

APPLICATION MODERNIZATION: ENHANCING CYBERSECURITY AND DRIVING

INNOVATION." INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN

ENGINEERING AND TECHNOLOGY (IJARET) 15.3 (2024): 377-392.

Dash, S. "Designing Modular Enterprise Software Architectures for AI-Driven Sales

Pipeline Optimization." Journal of Artificial Intelligence Research 3.2 (2023): 292-334.

Godbole, Aditi, Jabin Geevarghese George, and Smita Shandilya. "Leveraging Long-

Context Large Language Models for Multi-Document Understanding and

Summarization in Enterprise Applications." arXiv preprint arXiv:2409.18454 (2024).

Akhilandeswari, P., and Jabin G. George. "Secure Text Steganography." Proceedings

of International Conference on Internet Computing and Information Communications:

ICICIC Global 2012. Springer India, 2014.

Singu, Santosh Kumar. "Impact of Data Warehousing on Business Intelligence and

Analytics." ESP Journal of Engineering & Technology Advancements 2.2 (2022):

-113.

Santosh Kumar, Singu. "Maximizing financial intelligence-the role of optimized etl in

fintech data warehousing." INTERNATIONAL JOURNAL OF COMPUTER

ENGINEERING AND TECHNOLOGY (IJCET) 15, no. 4 (2024): 464-471.

R. McKenna, "Security Best Practices for Infrastructure as Code," in Proceedings of

the 2020 IEEE Symposium on Security and Privacy Workshops (SPW), 2020, pp.

–215.

C. Guo et al., "Enhancing Policy-as-Code for Cloud Security: A Machine Learning

Approach," IEEE Transactions on Cloud Computing, vol. 11, no. 2, pp. 35–49, 2023.

A. Sharma, D. Tiwari, and P. Kulkarni, "AI-Driven Optimization in Infrastructure as

Code for Cloud Cost Reduction," in Proceedings of the IEEE International

Conference on Machine Learning and Applications (ICMLA), 2022, pp. 167–172.

B. Burns and J. Beda, Kubernetes: Up and Running, 2nd ed. Sebastopol, CA, USA:

O’Reilly Media, 2022.

H. Kim, J. Han, and S. Cho, "A Scalable Serverless Framework for Cloud

Optimization Using IaC," IEEE Access, vol. 10, pp. 15230–15242, 2022.

M. Kavis, Architecting the Cloud: Design Decisions for Cloud Computing Service

Models (SaaS, PaaS, and IaaS), 1st ed. Hoboken, NJ, USA: Wiley, 2014.

N. Jones, "Monitoring and Observability for Infrastructure as Code," in Proceedings

of the IEEE International Workshop on Cloud Monitoring and Analytics (CMA), 2021,

pp. 56–63.

D. Farley, Modern Software Engineering: Doing What Works to Build Better Software

Faster, Boston, MA, USA: Addison-Wesley, 2021.

A. Jacobsen, M. Iqbal, and A. Mishra, "An Empirical Study on the Challenges of

Multi-Cloud IaC Implementations," IEEE Transactions on Cloud Computing, vol. 9,

no. 3, pp. 214–227, 2021.

K. Singh and R. Mangal, Security Automation with Terraform and AWS: Enhancing

IaC Security Practices, 1st ed. Birmingham, UK: Packt Publishing, 2022.

Downloads

Published

05-02-2024

How to Cite

[1]
Swetha Ravipudi, Gnanendra Reddy Muthirevula, and Vincent Kanka, “Infrastructure as Code (IaC) for Enterprise Cloud Migrations: Cost and Performance Optimization Strategies”, Newark J. Hum. Centric AI Robot Inter., vol. 4, pp. 84–122, Feb. 2024, Accessed: Dec. 21, 2025. [Online]. Available: https://njhcair.org/index.php/publication/article/view/19