AI-Driven Automated Infrastructure as Code Platform for Scalable Cloud-Native Enterprise Deployments and Operational Resilience

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Published: 2024-11-12
DOI: https://doi.org/10.15662/IJRPETM.2024.0706029
Keywords:
Artificial Intelligence, Infrastructure as Code, Cloud-Native Computing, DevOps Automation, Kubernetes, Terraform, Cloud Infrastructure, Predictive Analytics, Operational Resilience, Policy as Code, Enterprise Cloud, Hybrid Cloud

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Dr A. V. Kalpana
Department of Computer Science and Engineering, SRM Institute of Science & Technology, Chennai, India

Abstract

Artificial Intelligence (AI) and Infrastructure as Code (IaC) have emerged as transformative technologies for modern cloud-native enterprise infrastructure by enabling intelligent automation, consistent resource provisioning, operational resilience, and scalable application deployment. Traditional infrastructure management approaches rely heavily on manual configuration, fragmented operational workflows, and reactive maintenance, leading to configuration drift, deployment delays, security vulnerabilities, and increased operational costs. This research proposes an AI-driven automated Infrastructure as Code platform that integrates machine learning, DevOps automation, cloud-native orchestration, policy-as-code, predictive analytics, and continuous monitoring to support scalable enterprise deployments and resilient cloud operations. The proposed framework automates infrastructure provisioning, configuration validation, security compliance, workload optimization, resource scaling, anomaly detection, and disaster recovery through intelligent decision-making. AI models continuously analyze infrastructure telemetry, deployment history, workload behavior, resource utilization, and operational events to predict failures, optimize infrastructure allocation, and recommend proactive remediation strategies. Infrastructure definitions are maintained through version-controlled declarative templates, ensuring consistency across hybrid and multi-cloud environments. Continuous monitoring and governance mechanisms further improve infrastructure reliability, compliance, and service availability. The platform significantly reduces manual intervention, accelerates deployment cycles, minimizes operational risks, enhances cloud security, and optimizes infrastructure performance. Ultimately, the proposed framework supports enterprise digital transformation by providing secure, scalable, self-healing, and intelligent cloud-native infrastructure capable of adapting to dynamic business requirements and evolving operational challenges.

Article Details

Issue

Vol. 7 No. 6 (2024): International Journal of Research Publications in Engineering, Technology and Management

Section

Articles

How to Cite

AI-Driven Automated Infrastructure as Code Platform for Scalable Cloud-Native Enterprise Deployments and Operational Resilience. (2024). International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(6), 11695-11704. https://doi.org/10.15662/IJRPETM.2024.0706029

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