Intelligent Secure Enterprise Kubernetes Infrastructure for Real-Time Cloud Healthcare Analytics
DOI:
https://doi.org/10.15662/IJEETR.2025.0703004Keywords:
Kubernetes, Healthcare Analytics, Cloud Computing, Enterprise Security, Real-Time Analytics, Zero-Trust Architecture, Container Orchestration, HIPAA Compliance, Microservices, AI-driven Infrastructure, DevSecOps, Cloud-Native HealthcareAbstract
The rapid digital transformation of healthcare has resulted in an unprecedented growth of real-time clinical, operational, and patient-generated data. To efficiently process, analyze, and secure this data at scale, modern healthcare enterprises require intelligent, cloud-native infrastructures capable of supporting dynamic workloads while ensuring regulatory compliance and patient data privacy. This paper proposes an Intelligent Secure Enterprise Kubernetes Infrastructure (ISEKI) designed specifically for real-time cloud healthcare analytics. The framework integrates Kubernetes-based container orchestration, zero-trust security architecture, AI-driven workload optimization, and compliance-aware governance mechanisms to deliver scalable, resilient, and secure healthcare analytics services. By leveraging microservices architecture, service mesh technologies, policy-based access control, encryption mechanisms, and AI-powered anomaly detection, the proposed infrastructure ensures high availability, operational agility, and robust protection against cyber threats. Furthermore, the system supports interoperability standards such as HL7 and FHIR to facilitate seamless integration with electronic health record systems. The proposed approach addresses key challenges including data sensitivity, latency constraints, regulatory compliance (HIPAA, GDPR), and dynamic scaling requirements. This study contributes a comprehensive architectural model, security framework, and implementation methodology tailored to enterprise healthcare environments operating in multi-cloud and hybrid-cloud ecosystems
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