An AI-Based Auto-Scaling Mechanism for Efficient Cloud Resource Management using AWS SageMaker and S3

Makwana, Brijesh Girish (2025) An AI-Based Auto-Scaling Mechanism for Efficient Cloud Resource Management using AWS SageMaker and S3. Masters thesis, Dublin, National College of Ireland.

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Abstract

The study creates an auto-scaling performance in the cloud environment based on the techniques of Deep Reinforcement Learning (DRL) on AWS SageMaker and S3. In contrast to threshold-based scaling, the proposed method utilizes Proximal Policy Optimization (PPO) and Asynchronous Advantage Actor-Critic (A3C) algorithms, which are trained in a self-designed OpenAI Gym simulation of workloads. The models are deployed as SageMaker endpoints to make real-time scaling decisions by using live system metrics. In experiments, the solution minimized over-and under-provisioning, optimized resource utilization, and ensured SLA compliance in the face of varying loads. The resilience is proven by fault injection tests, which prove the practicality of DRL in adaptive and cost-effective cloud resource management.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Lugones, Diego UNSPECIFIED
Uncontrolled Keywords:	Deep Reinforcement Learning; Cloud Auto-Scaling; Proximal Policy Optimization (PPO); Asynchronous Advantage Actor-Critic (A3C); AWS SageMaker; Amazon S3; OpenAI Gym; Intelligent Resource Management; Real-Time Inference; Cloud Computing
Subjects:	Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Ciara O'Brien
Date Deposited:	30 Mar 2026 10:05
Last Modified:	30 Mar 2026 10:05
URI:	https://norma.ncirl.ie/id/eprint/9242

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