Resilient Hybrid Cloud Infrastructure Using Generative AI for Predictive Capacity Planning and Automated Operations
DOI:
https://doi.org/10.15680/IJCTECE.2025.0806046Keywords:
Hybrid Cloud, Generative AI, Predictive Capacity Planning, Automated Operations, Cloud Resilience, Workload Forecasting, Intelligent Infrastructure, Cloud AutomationAbstract
Resilient hybrid cloud infrastructure has become essential for enterprises that require scalable computing, continuous availability, operational flexibility, and efficient resource utilization across on-premises and cloud environments. Traditional capacity planning and infrastructure operations frequently depend on historical statistics, manually defined thresholds, and reactive intervention, which can result in overprovisioning, performance degradation, service interruptions, and inefficient resource allocation. This study proposes a resilient hybrid cloud infrastructure framework that integrates Generative Artificial Intelligence (GenAI) with predictive capacity planning and automated infrastructure operations. The proposed approach combines telemetry data, workload characteristics, infrastructure utilization metrics, application performance indicators, and operational events to generate predictive insights and intelligent recommendations. Generative AI models are incorporated to support workload forecasting, capacity scenario generation, operational reasoning, configuration assistance, anomaly interpretation, and automated remediation workflows. A policy-aware automation layer enables infrastructure resources to be dynamically provisioned, scaled, optimized, and recovered across heterogeneous cloud environments while maintaining governance and security constraints. The methodology evaluates forecasting accuracy, resource utilization, operational response time, scalability, resilience, and automation effectiveness. The framework is designed to reduce reactive infrastructure management and improve proactive decision-making through continuous intelligence. By combining predictive analytics with generative reasoning and automated operations, the proposed architecture provides a scalable foundation for resilient, adaptive, and intelligent hybrid cloud infrastructure management.
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