  Ocean eddies play a significant role both on the sea surface and beneath it,
contributing to the sustainability of marine life dependent on oceanic
behaviors. Therefore, it is crucial to investigate ocean eddies to monitor
changes in the Earth, particularly in the oceans, and their impact on climate.
This study aims to pinpoint ocean eddies using AWS cloud services, specifically
SageMaker. The primary objective is to detect small-scale (<20km) ocean eddies
from satellite remote images and assess the feasibility of utilizing SageMaker,
which offers tools for deploying AI applications. Moreover, this research not
only explores the deployment of cloud-based services for remote sensing of
Earth data but also evaluates several YOLO (You Only Look Once) models using
single and multi-GPU-based services in the cloud. Furthermore, this study
underscores the potential of these services, their limitations, challenges
related to deployment and resource management, and their user-riendliness for
Earth science projects.
