Architecting Secure, Automated Multi-Cloud Database Platforms Strategies for Scalable Compliance
Keywords:
Multi-cloud architecture, database security, automated compliance, scalability, disaster recovery.Abstract
As organizations increasingly adopt multi-cloud architectures to meet diverse business needs, ensuring the security and compliance of databases across these environments has become paramount. This research explores strategies for architecting secure, automated multi-cloud database platforms that not only support scalability but also guarantee adherence to regulatory compliance requirements. The focus is on overcoming challenges related to security, automation, and compliance in multi-cloud environments. By exploring the complexities introduced by the decentralized nature of multi-cloud systems, this paper discusses best practices in data encryption, identity and access management, disaster recovery, and compliance automation. The paper also highlights the importance of adopting robust encryption methods, establishing strong identity and access management (IAM) practices, automating compliance monitoring, and ensuring effective disaster recovery strategies. A key contribution of this research is the introduction of the M.C.A.R.E. Framework — Multi-cloud Automated Resilience and Enforcement — a five-layer model designed to normalize identity policies, enforce compliance baselines, remediate configuration drift, detect incidents in real time, and log encrypted data access across diverse cloud environments. This framework provides a reusable, platform-agnostic approach for securing mission-critical workloads with automation and auditability. Case studies from industries like finance and e-commerce demonstrate the successful implementation of these strategies. The research provides actionable insights into designing scalable and compliant multi-cloud database platforms, offering a comprehensive approach to addressing security threats, compliance complexities, and scalability issues across diverse cloud platforms. The study concludes with future directions for enhancing multi-cloud database security and compliance, focusing on the integration of AI, machine learning, blockchain, and standardized cross-cloud security frameworks.
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