Principle:Kserve Kserve GPU Cluster Preparation

Knowledge Sources	NVIDIA Device Plugin HuggingFace Hub
Domains	Infrastructure, GPU_Computing, Security
Last Updated	2026-02-13 00:00 GMT

Overview

An infrastructure preparation pattern that configures GPU nodes and model access credentials for LLM inference workloads.

Description

GPU Cluster Preparation ensures the Kubernetes cluster has the prerequisites for running LLM inference:

• GPU nodes: NVIDIA device plugin installed, exposing nvidia.com/gpu as a schedulable resource.
• Model credentials: HuggingFace token stored in a Kubernetes Secret, bound to a ServiceAccount for model download authentication.

This is the foundational step for LLM serving: without GPU resources and model access, the LLMInferenceService pods cannot start or download models.

Usage

Complete this before deploying any LLMInferenceService. Verify GPU availability with kubectl get nodes -o json | jq '.items[].status.capacity["nvidia.com/gpu"]'.

Theoretical Basis

# Prerequisites checklist (NOT implementation code)
1. NVIDIA device plugin deployed (DaemonSet)
   - Exposes nvidia.com/gpu resource on nodes
2. GPU nodes labeled and available
3. HuggingFace token Secret created
4. ServiceAccount bound to Secret
5. StorageClass available for PVC (if using PVC model storage)

Related Pages

Implemented By

• Implementation:Kserve_Kserve_GPU_Cluster_Credentials