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Autonomous Multi-Agent System for Cloud Architecture Design and Infrastructure Deployment
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence
DOI: https://doi.org/10.64388/IREV9I9-1715267
Abstract
Cloud infrastructure design and deployment traditionally require significant expertise in cloud services, networking, security, and Infrastructure-as-Code (IaC). Translating high-level business requirements into production-ready infrastructure can take days of manual effort and often involve multiple domain experts. This research presents Cloud Infrastructure Crew, an autonomous multi-agent system built using the CrewAI framework that automates cloud architecture design, IaC generation, and deployment validation. The system utilizes three specialized Large Language Model (LLM) powered agents that collaborate sequentially to convert business requirements into infrastructure artifacts such as architecture diagrams, Terraform configuration files, and deployment reports. A human-in-the-loop approval mechanism ensures architectural accuracy before infrastructure generation,also added at agents steps. Experimental evaluation shows that the proposed system significantly reduces infrastructure planning time from several days to minutes while maintaining transparency, auditability, and extensibility. The architecture is designed to be cloud-agnostic and supports integration with multiple LLM providers.
How to cite this paper
@article{1715267,
author = {Raunak B Sinha},
title = {Autonomous Multi-Agent System for Cloud Architecture Design and Infrastructure Deployment},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {9},
pages = {1484-1487},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1715267.pdf},
abstract = {Cloud infrastructure design and deployment traditionally require significant expertise in cloud services, networking, security, and Infrastructure-as-Code (IaC). Translating high-level business requirements into production-ready infrastructure can take days of manual effort and often involve multiple domain experts. This research presents Cloud Infrastructure Crew, an autonomous multi-agent system built using the CrewAI framework that automates cloud architecture design, IaC generation, and deployment validation. The system utilizes three specialized Large Language Model (LLM) powered agents that collaborate sequentially to convert business requirements into infrastructure artifacts such as architecture diagrams, Terraform configuration files, and deployment reports. A human-in-the-loop approval mechanism ensures architectural accuracy before infrastructure generation,also added at agents steps. Experimental evaluation shows that the proposed system significantly reduces infrastructure planning time from several days to minutes while maintaining transparency, auditability, and extensibility. The architecture is designed to be cloud-agnostic and supports integration with multiple LLM providers.},
month = {March},
doi = {https://doi.org/10.64388/IREV9I9-1715267}
}