Journal of Advanced Engineering Technology and Management
ISSSN (Online): 3049-3684
Volume: 2 Issue: 1 | Open Access | 16 August 2026
From Cloud Infrastructure to Intelligent Healthcare Systems: A Human-Centered Framework for Secure, Scalable, and Trustworthy AI Operations
Mahesh Chandra, Research Scholar, Chitkara University
Abstract
The convergence of cloud computing, Artificial Intelligence (AI), microservices, infrastructure automation and clinical data sets is driving innovation in next-generation healthcare systems. Healthcare systems demand technologies that can ingest diverse clinical data, enable AI-driven reasoning, scale compute capacity, and enforce security, privacy, data integrity and human accountability. Yet, infrastructure as code, AI, and clinical data are often designed and managed in silos. In this post, we present a human-centered architecture combining cloud infrastructure automation, Kubernetes-native orchestration, Large Language Model (LLM)-powered microservices, clinical data integrity, identity governance, and human accountability. Our architecture is informed by ongoing research into Infrastructure as Code (IaC), Kubernetes for production workloads, LLM-powered microservices, clinical data integrity, and the Cardiac Data Integrity Score (CDIS). The foundation for trustworthy healthcare AI includes four capabilities: infrastructure, AI, data integrity and human governance. Infrastructure provides compute capability, AI delivers cognitive and analytical processing, data integrity ensures trustworthy data, and humans bring context and judgement. This paper lays out a layered architecture reference and introduces a continuum of AI autonomy such that machine-generated decisions are bounded by available data, security permissions, confidence scoring and clinical review. We envision the future of healthcare AI will be less autonomous systems and more governed socio-technical systems where cloud-native infrastructure and AI empower humans and humans are ultimately accountable for patient care.
Keywords: Healthcare AI, Cloud Infrastructure, Kubernetes, Infrastructure as Code, Large Language Models, Microservices, Clinical Data Integrity, Human-Centered AI, Data Governance, Trustworthy AI, Digital Health
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