AI-Powered Cloud Cost Governance Systems: Automating Budget Management, Resource Allocation, and Policy Compliance for Optimize Cloud Expenditure

Authors

Charan Shankar Kummarapurugu

Abstract

The rapid adoption of cloud computing by enter- prises has introduced significant complexities in managing and controlling cloud expenditure, especially in multi-cloud environ- ments. Traditional approaches to cloud cost governance often rely on manual interventions and static rules, leading to inefficiencies and unpredictable costs. To address these challenges, this paper proposes an AI-powered cloud cost governance system that auto- mates budget management, resource allocation, and policy com- pliance. The system leverages machine learning models to predict resource demands and costs, enabling real-time adjustments to cloud resources based on both historical data and current usage patterns. Moreover, AI-driven policy enforcement ensures that pre-defined budgetary constraints are adhered to automatically, reducing human intervention and improving cost efficiency. A simulation study demonstrates the effectiveness of the proposed system, showing significant reductions in cloud spending and improved utilization of cloud resources. The paper concludes by discussing the future potential of integrating reinforcement learning to further enhance cloud governance systems.

Keywords

AI in Cloud Computing, Cloud Cost Gover- nance, Policy Automation, Resource Allocation, Budget Manage- ment, Multi-Cloud Optimization

AI-Powered Cloud Cost Governance Systems: Automating Budget Management, Resource Allocation, and Policy Compliance for Optimize Cloud Expenditure. Charan Shankar Kummarapurugu. 2023. IJIRCT, Volume 9, Issue 6. Pages 1-12. https://www.ijirct.org/viewPaper.php?paperId=2411032