Abstract

Cloud computing offers scalable and cost-effective access to computing resources, necessitating meticulous cost optimization. This project introduces an automated system for cloud cost optimization, amalgamating pricing analysis, service metrics, and resource utilization assessment. It encompasses an administrative portal for provider analysis and resource monitoring, alongside analytics modules tracking availability, latency, scalability, and pricing competitiveness. Leveraging REST APIs, machine learning, and tools like Terraform and Ansible, the system proposes cost-effective provider and instance allocations based on real-time and forecasted needs. Administrators can define allocation policies and scaling thresholds for automated adjustments. The system culminates in an intelligent software agent adept at efficiently administering cloud resources, minimizing costs while meeting application demands. It exemplifies the application of analytics, automation, and AI to continually optimize dynamic cloud infrastructure, surpassing manual or reactive approaches.