Standing Up a GPU Cluster on AKS for vLLM
This article is Part of a series on running vLLM on AKS and walks through creating an AKS cluster with a GPU node pool, deploying vLLM onto it, and wiring up Prometheus and Grafana for visibility. Companion pieces: Choosing the right GPU | Why your autoscaler flaps | Source Setup Summary Cloud: Azure GPU node: Standard_NV36ads_A10_v5 (1× A10, 24 GB) Image / model: vllm/vllm-openai:latest serving…
This article details the process of setting up an AKS cluster with a GPU node pool for vLLM. It covers the sequence of steps required, from requesting a GPU quota through Azure Portal, to deploying vLLM onto the cluster, and configuring observability tools such as Prometheus and Grafana. The steps are arranged in a specific order, as each step builds upon the previous one.
The article also explains key concepts like cluster autoscaler, node taints, tolerations, and the NVIDIA device plugin, which are crucial for the GPU node to function correctly.
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