Kubernetes treats GPUs as atomic resources, forcing over-provisioning and low utilization in multi-tenant AI Notebooks. DRA and HAMi's vGPU virtualization solve this, but only if implemented correctly.

Part 1: Mechanics of GPU Sharing. How DRA alters resource requests and HAMi implements fractional GPU allocation. The hardware constraints: memory isolation, compute slicing.

Part 2: Production at Viettel Cloud. Deployment architecture, bottlenecks moving from test to production, and operational realities of fractional GPUs for data science workloads at telco scale.