server deployment

Overview of deploying AI servers: from capacity planning and GPU/CPU selection to storage, networking and model serving frameworks. Covers containerization, Kubernetes orchestration, autoscaling, and CI/CD for reliable releases. Emphasizes monitoring, security, governance, and cost optimization, with patterns for batch and real-time inference across cloud and edge.