Scalable AI Model Deployment with AWS SageMaker and EKS

As businesses increasingly leverage Artificial Intelligence (AI) to drive innovation, the need for scalable, efficient, and secure AI model deployment is critical. AWS SageMaker and Amazon Elastic Kubernetes Service (EKS) offer a robust solution for deploying Machine Learning (ML) models in a scalable and resilient environment. This article explores integrating AWS SageMaker with EKS to create a highly available, containerized infrastructure for AI model deployment. SageMaker simplifies the process of building, training, and tuning ML models, while EKS provides a powerful platform for running these models in production, ensuring scalability through Kubernetes' container orchestration capabilities. Together, they enable enterprises to deploy AI models that can scale seamlessly to meet varying demands, handle high workloads, and maintain performance, all while taking advantage of the cloud-native ecosystem.

Authors

Publication Details

Journal
International Journal of Computer Trends and Technology
Published
2024-11-30
DOI
https://doi.org/10.14445/22312803/ijctt-v72i11p114
Primary Topic
Advanced Computational Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Scalable AI Model Deployment with AWS SageMaker and EKS

J.R. Banerjee
International Journal of Computer Trends and Technology
Advanced Computational Techniques and Applications
article

Scalable AI Model Deployment with AWS SageMaker and EKS

J.R. Banerjee
article en

Abstract

As businesses increasingly leverage Artificial Intelligence (AI) to drive innovation, the need for scalable, efficient, and secure AI model deployment is critical. AWS SageMaker and Amazon Elastic Kubernetes Service (EKS) offer a robust solution for deploying Machine Learning (ML) models in a scalable and resilient environment. This article explores integrating AWS SageMaker with EKS to create a highly available, containerized infrastructure for AI model deployment. SageMaker simplifies the process of building, training, and tuning ML models, while EKS provides a powerful platform for running these models in production, ensuring scalability through Kubernetes' container orchestration capabilities. Together, they enable enterprises to deploy AI models that can scale seamlessly to meet varying demands, handle high workloads, and maintain performance, all while taking advantage of the cloud-native ecosystem.

International Journal of Computer Trends and TechnologyVol. 72(11)
Openalex Percentile: Top 76%
Advanced Computational Techniques and Applications
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