AKS GPU cluster deployment for vLLM

Technical guides detail the process of deploying vLLM on Azure Kubernetes Service (AKS) using a dedicated GPU node pool. The implementation focuses on creating a resilient runtime for AI inference by ensuring proper hardware allocation and observability.

The deployment workflow involves several critical steps: requesting GPU quotas through the Azure Portal, creating a resource group, and initializing an AKS cluster with a CPU system pool before adding the GPU-enabled node pool. To ensure operational visibility, the setup integrates a monitoring stack consisting of Prometheus, Grafana, and the NVIDIA DCGM exporter to track GPU and pod status.