Modern cloud-native infrastructures face challenges validating and scaling storage systems due to limited hardware, tight timelines, and high costs. This talk introduces a CNCF aligned, AI driven framework using Large Language Models to create standards-compliant Digital Twins of storage devices for realistic, hardware-free simulation. Integrating SNIA Swordfish and DMTF Redfish within a containerized, Kubernetes-native pipeline, it leverages key CNCF projects, Kubernetes for orchestration, Prometheus and OpenTelemetry for metrics and observability, Flux/Argo CD for GitOps-driven deployment, and Envoy for secure service communication. LLMs synthesize JSON device models that emulate real hardware, enabling scalable, standards-based validation and orchestration across cloud environments, empowering engineers to "design anywhere, test everywhere" while ensuring strict SNIA/DMTF and CNCF compliance.