Assess learners’ ability to evaluate and compare edge versus cloud ML deployment strategies for production systems, with emphasis on latency, privacy and regulatory compliance, total cost of ownership, and maintainability. Questions will require analyzing trade-offs (including hybrid architectures), identifying relevant metrics (e.g., inference latency, bandwidth, cost-per-inference, update velocity), and justifying deployment decisions given constraints such as hardware, data residency, monitoring/observability, scaling, and operational risk.