Cloud-Native AI Platform for Real-Time Resource Optimization in Governance-Driven Project and Network Operations
DOI:
https://doi.org/10.15662/IJEETR.2023.0502005Keywords:
Cloud-native AI, real-time optimization, resource management, governance-driven operations, machine learning forecasting, automated orchestration, compliance automation, network operationsAbstract
Governance-driven digital environments increasingly require intelligent, transparent, and highly efficient systems to manage project and network operations at scale. This study presents a cloud-native AI platform designed to achieve real-time resource optimization while ensuring strict adherence to organizational and regulatory governance standards. The proposed platform integrates machine learning–based forecasting, intelligent workload balancing, and automated orchestration to dynamically allocate resources across distributed project and network ecosystems. Continuous monitoring and analytics-driven decision engines enhance operational visibility, reduce performance bottlenecks, and enable rapid response to system fluctuations. Governance is embedded through policy-based controls, compliance automation, and secure audit mechanisms that maintain accountability and consistency across all operational layers. Experimental evaluation demonstrates that the framework significantly improves resource efficiency, strengthens governance alignment, and enhances overall reliability in complex project and network environments. The platform establishes a scalable and intelligent foundation for next-generation operational management in regulated sectors.
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