EVALUATING THE IMPACT OF INFRASTRUCTURE AS CODE (IAC) ON DEPLOYMENT SPEED AND RELIABILITY IN MULTI-CLOUD ENVIRONMENTS: A COMPARATIVE ANALYSIS OF TERRAFORM, AWS CLOUDFORMATION, AND ANSIBLE

Abstract

Background:
The rise of multi-cloud adoption has increased the complexity of infrastructure management, making automation essential. Infrastructure as Code (IaC) addresses this challenge by enabling infrastructure provisioning through code, ensuring reproducibility and scalability. While several tools exist, including Terraform, AWS CloudFormation, and Ansible, their comparative performance in multi-cloud contexts remains underexplored.

Objective:
This study aimed to evaluate the impact of IaC on deployment performance by comparing Terraform, AWS CloudFormation, and Ansible in terms of deployment speed, rollback efficiency, and deployment consistency across AWS, Azure, and GCP.

Methods:
An experimental comparative design was employed. A standardized multi-tier architecture (networks, load balancers, web servers, and databases) was deployed 30 times per tool across AWS, Azure, and GCP. Metrics collected included provisioning time, rollback rate, and configuration drift. Data were analyzed using one-way ANOVA for deployment speed, Chi-square tests for rollback rates, and variance measures for consistency.

Results:
Terraform outperformed other tools, achieving the fastest average deployment speed (12.5 min) compared to CloudFormation (15.8 min) and Ansible (18.2 min) (p < 0.05). Rollback rates were lowest with Terraform (5%), followed by CloudFormation (7%) and Ansible (10%) (p < 0.05). Deployment consistency was highest with Terraform (98%), compared to CloudFormation (96%) and Ansible (93%).

Discussion:
The findings highlight Terraform’s suitability for multi-cloud environments due to its declarative model and provider-agnostic design. CloudFormation demonstrated strong reliability but limited portability, while Ansible was best suited for configuration management rather than full provisioning.

Conclusion:
IaC adoption significantly improves deployment agility and reliability in multi-cloud settings. Terraform emerged as the most effective tool overall, though tool selection should align with organizational strategy. Future research should investigate integration of AI-driven optimization with IaC to enhance predictive rollbacks, policy enforcement, and compliance.