Designing a Secure Hybrid Cloud Management Model for Enterprise Resource Optimization and Data Protection

The increasing adoption of hybrid cloud architectures has transformed enterprise IT operations by integrating private and public cloud environments for enhanced scalability, cost efficiency, and business continuity. However, this convergence introduces new complexities in data protection, workload orchestration, and governance, necessitating robust security-driven management frameworks. This review paper explores the design of a secure hybrid cloud management model that optimizes enterprise resources while safeguarding sensitive data across distributed infrastructures. It examines existing hybrid management paradigms-such as multi-cloud orchestration, containerization, and policy-based automation-highlighting their roles in improving interoperability and resilience. The study further analyzes security mechanisms including zero-trust frameworks, identity and access management (IAM), encryption at rest and in transit, and AI-based anomaly detection for proactive threat mitigation. By synthesizing recent developments in cloud service orchestration and data-centric protection strategies, the paper proposes an integrated model emphasizing automation, compliance alignment, and adaptive security controls. The proposed framework aims to enhance operational agility, minimize security vulnerabilities, and support regulatory adherence across multi-tenant environments. Ultimately, this research contributes to advancing secure hybrid cloud governance models that align with modern enterprise objectives for optimized resource utilization and end-to-end data protection.