Year: 2024
Type: article
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.
Author: Joyanta Banerjee
Institution: Amazon (United States)
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4407001577