ElectroSphere: Electrical Electronics Engineering Bulletin
AI-Enhanced Infrastructure as Code (IaC) for Smart Configuration Management
Abstract
Atul Khanna and Chhaya Gunawat
The integration of Artificial Intelligence (AI) with Infrastructure as Code (IaC) is revolutionizing cloud infrastructure management by enabling intelligent automation, predictive analytics, and self-healing capabilities. Traditional IaC automated infrastructure provisioning, but AI-driven approaches enhance this process by optimizing resource allocation, reducing human errors, and ensuring real-time security compliance. This paper explores the application of machine learning (ML), reinforcement learning (RL), and natural language processing (NLP) in automating IaC workflows, predicting infrastructure failures, and dynamically adjusting configurations for performance and cost efficiency. Additionally, we analyze AI-powered anomaly detection for proactive issue resolution and self-remediating infrastructures that minimize downtime. Through case studies, simulations, and performance evaluations, we demonstrate how AI improves scalability, resilience, and operational efficiency in cloud environments. This research also highlights key challenges, including AI model interpretability, security concerns, and integration complexities, while proposing best practices for seamless AI-IaC adoption. The findings underscore AI’s transformative potential in modern IT ecosystems, paving the way for autonomous, intelligent infrastructure management in DevOps and cloud computing. The study explores various AI techniques applied in IaC, including machine learning algorithms for anomaly detection, predictive analytics for capacity planning, and natural language processing for intelligent code generation. By examining state-of-the-art methodologies, the research highlights the challenges, opportunities, and future directions of AI-driven configuration management in modern IT ecosystems. The findings underscore the transformative potential of AI in reshaping infrastructure automation, ensuring greater scalability, resilience, and efficiency [1].