A Hybrid Infrastructure-as-Code Strategy for Scalable and Automated AI/ML Deployment in Telecom Clouds
DOI:
https://doi.org/10.15680/IJCTECE.2022.0506008Keywords:
Infrastructure-as-Code, Terraform, Ansible, telecom-grade deployments, AI/ML automation, multi-cloud, orchestration, configuration managementAbstract
Telecom operators are increasingly adopting AI/ML-driven applications for network optimization, predictive maintenance, and customer experience enhancement. However, deploying such workloads in telecom-grade environments requires consistent, scalable, and secure infrastructure provisioning. This paper explores Infrastructure-as-Code (IaC) approaches using Terraform and Ansible to accelerate AI/ML deployments across multi-cloud and on-premise telecom infrastructures. Terraform provides declarative provisioning for cloud and edge resources, while Ansible offers agentless configuration management and automation of AI/ML frameworks. By integrating these tools, the study demonstrates faster deployment cycles, reduced configuration drift, and improved compliance with telecom-grade performance and security requirements. Experimental analysis highlights significant reductions in setup time and improved reproducibility of AI/ML environments. The findings provide a blueprint for telecom operators to adopt IaC-driven automation for reliable, scalable, and compliant AI/ML service delivery
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