Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM62038
Volume:
10 |
4 |
April 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Science and Engineering
Dhanalakshmi Srinivasan Engineering College (Autonomous), Perambalur – 621 212, Tamil Nadu, India
Department of Computer Science and Engineering
Dhanalakshmi Srinivasan Engineering College (Autonomous), Perambalur – 621 212, Tamil Nadu, India
Department of Computer Science and Engineering
Dhanalakshmi Srinivasan Engineering College (Autonomous), Perambalur – 621 212, Tamil Nadu, India
Department of Computer Science and Engineering
Dhanalakshmi Srinivasan Engineering College (Autonomous), Perambalur – 621 212, Tamil Nadu, India
Department of Computer Science and Engineering
Dhanalakshmi Srinivasan Engineering College (Autonomous), Perambalur – 621 212, Tamil Nadu, India
The rapid adoption of cloud computing has led organizations to rely on multiple cloud service providers to improve availability, scalability, and vendor independence. Managing infrastructure across heterogeneous cloud platforms, however, introduces complexity and operational overhead. This paper presents a Multi-Cloud Object Storage Provisioning system that leverages Infrastructure as Code (IaC) principles through Terraform to automate and standardize object storage provisioning across AWS, Microsoft Azure, and Google Cloud Platform (GCP). A unified Terraform configuration deploys storage services — including S3 buckets, Azure Blob Storage containers, and GCP Cloud Storage buckets — while maintaining provider-specific flexibility. The proposed system incorporates a multi-cloud data consistency framework using passive servers and non-communicating clients, ensuring reliable synchronization without centralized coordination overhead. Experimental evaluation demonstrates improvements in availability, fault tolerance, response time, and scalability compared to single-cloud architectures. The results confirm that Terraform-based IaC automation significantly simplifies multi-cloud infrastructure management and provides a scalable foundation for cloud-native applications.
KEYWORDS
This paper presented a comprehensive Multi-Cloud Object Storage Provisioning system using Terraform, successfully deploying storage resources on AWS S3, Azure Blob Storage, and Google Cloud Storage through a single, unified IaC configuration. The system demonstrates that Terraform-based automation significantly simplifies multi-cloud infrastructure management, eliminates manual configuration errors, and provides a scalable, repeatable deployment process. The proposed data consistency architecture using passive servers and non-communicating clients ensures reliable synchronization without centralized coordination overhead. Performance evaluation confirmed improvements in fault tolerance, availability, response time, and scalability over traditional single-cloud systems. Security mechanisms including JWT authentication, TLS encryption, and provider-level access policies successfully protected all data operations. The project underscores the critical importance of IaC tools in achieving efficient, secure, and maintainable multi-cloud deployments, providing a strong foundation for future research in AI-driven cloud optimization, automated CI/CD pipelines, and advanced multi-cloud security architectures.
[1] M. Armbrust et al., "A View of Cloud Computing," Communications of the ACM, vol. 53, no. 4, pp. 50–58, 2010. [2] P. Mell and T. Grance, "The NIST Definition of Cloud Computing," NIST Special Publication 800-145, 2011. [3] HashiCorp, "Terraform Documentation," https://developer.hashicorp.com/terraform/docs, 2024. [4] N. Mhaisen and Q. M. Malluhi, "Data Consistency in Multi-Cloud Storage Systems with Passive Servers," IEEE Access, 2025. [5] J. Zheng et al., "Intent-Based Multi-Cloud Storage Management Powered by a Fine-Tuned Large Language Model," IEEE Access, 2025. [6] Raju P. B., K. Chandrasekaran, and V. Vijayakumar, "Efficient Multi-Cloud Storage Using Online Dynamic Replication," IEEE Access, 2023. [7] D. C. Diningrat, Suhardi, and B. Rahardjo, "Security Issues in Multi-Cloud: A Systematic Literature Review," IEEE Access, 2025. [8] M. A. Altahat, T. Daradkeh, and A. Agarwal, "Optimized Encryption-Integrated Strategy for Containers Scheduling in Multi-Cloud Data Centers," IEEE Access, 2024. [9] S. Fugkeaw et al., "FPRESSO: Fast and Privacy-Preserving SSO Authenticate with Dynamic Load Balancing for Multi-Cloud-Based Web Applications," IEEE Access, 2024. [10] S. Khan, A. Raza et al., "A Comprehensive Review on Scaling Machine Learning Workflows Using Cloud Technologies and DevOps," IEEE Access, 2024. [11] G. DeCandia et al., "Dynamo: Amazon's Highly Available Key-Value Store," ACM SIGOPS Operating Systems Review, vol. 41, no. 6, pp. 205–220, 2007. [12] S. Gilbert and N. Lynch, "Brewer's Conjecture and the Feasibility of Consistent, Available, Partition-Tolerant Web Services," ACM SIGACT News, vol. 33, no. 2, 2002. [13] R. Buyya, C. S. Yeo, and S. Venugopal, "Market-Oriented Cloud Computing: Vision, Hype, and Reality," Future Generation Computer Systems, vol. 25, no. 6, 2009. [14] E. M. Mendes and J. R. de Almeida Junior, "Hybrid Data Lake Entities Localization Optimization Based on Complex Networks," IEEE Access, 2026. [15] D. P. Kingma and J. Ba, "Adam: A Method for Stochastic Optimization," ICLR, 2015.
Publication Date
4/30/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
2
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...