Modernizing Reinforcement Learning with AWS Cloud for Adaptive Cloud Infrastructure Governance and Resource Optimization
DOI:
https://doi.org/10.15662/IJEETR.2026.0804002Keywords:
Reinforcement Learning, AWS Cloud, Cloud Infrastructure, Adaptive Governance, Resource Optimization, Artificial Intelligence, Cloud Computing, Amazon EC2, Amazon SageMaker, AWS Auto Scaling, Cloud Resource Management, Intelligent AutomationAbstract
The rapid adoption of cloud computing has transformed enterprise information technology by providing scalable, flexible, and cost-efficient computing resources. However, managing dynamic cloud infrastructures while ensuring governance, security, performance, and cost optimization remains a significant challenge. Reinforcement Learning (RL), a branch of artificial intelligence that enables autonomous agents to learn optimal decision-making through continuous interaction with dynamic environments, has emerged as a promising solution for adaptive cloud infrastructure management. When integrated with Amazon Web Services (AWS), reinforcement learning can automate resource allocation, workload scheduling, infrastructure scaling, security policy enforcement, and operational governance. This study investigates the modernization of reinforcement learning techniques within AWS cloud environments to improve adaptive cloud infrastructure governance and resource optimization. The research examines existing reinforcement learning algorithms, AWS cloud services, governance frameworks, and intelligent automation strategies that support efficient cloud operations. A methodological framework is proposed to integrate reinforcement learning agents with AWS services such as Amazon EC2, AWS Lambda, Amazon CloudWatch, Amazon SageMaker, AWS Auto Scaling, and AWS Organizations for continuous optimization of cloud resources. The study also evaluates governance mechanisms including policy compliance, security monitoring, cost management, and service reliability. The findings demonstrate that reinforcement learning combined with AWS cloud technologies enhances operational efficiency, improves resource utilization, reduces infrastructure costs, strengthens governance, and supports autonomous decision-making in modern cloud-native enterprise environments
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