AI Model Management with AWS Cloud Infrastructure

Author(s)	Prabu Arjunan
Country	United States
Abstract	State-of-the-art AI development requires a strong infrastructure that could handle everything: from initial experimentation to the production deployment of a model. AWS offers an end-to-end suite of services that allows enterprises to build, train, deploy, and manage machine learning models at scale. This whitepaper details an enterprise approach to managing AI models using AWS Cloud Infrastructure with version control, reproducibility, and operational efficiency in mind.
Keywords	AWS Cloud, AWS SageMaker, MLOps, Model Registry, Machine Learning Pipeline, Model Deployment, Training Infrastructure, CodeCommit, API Gateway, Auto Scaling, Step Functions, CloudWatch, Infrastructure as Code, DevOps
Published In	Volume 15, Issue 4, October-December 2024
Published On	2024-11-05
Cite This	AI Model Management with AWS Cloud Infrastructure - Prabu Arjunan - IJSAT Volume 15, Issue 4, October-December 2024. DOI 10.5281/zenodo.14514123
DOI	https://doi.org/10.5281/zenodo.14514123
Short DOI	https://doi.org/g8wcf6

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