--- title: "Implement GPU-as-a-Service with Kueue and NVIDIA MIG" url: https://daily.dev/posts/implement-gpu-as-a-service-with-kueue-and-nvidia-mig-wtjs3in1t source_url: https://developers.redhat.com/articles/2026/06/29/implement-gpu-as-a-service-kueue type: article source: "Red Hat Developer" published: 2026-06-29T07:29:27.283Z updated: 2026-06-29T07:29:50.454Z tags: ["kubernetes", "gpu", "openshift"] reading_time: 5 upvotes: 0 comments: 0 language: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Implement GPU-as-a-Service with Kueue and NVIDIA MIG **[Red Hat Developer](https://daily.dev/sources/rhdev)** · 5 min read · 0 upvotes · 0 comments ## Summary GPU-as-a-Service (GPUaaS) addresses the common problem of expensive, underutilized GPUs in organizations by enabling self-service reservation of GPU slices. The approach uses Red Hat OpenShift with Kueue (a Kubernetes queueing and quota system) and NVIDIA Multi-Instance GPU (MIG) technology. MIG allows a single physical GPU to be partitioned into isolated slices of varying sizes, while Kueue manages resource pools, fair sharing, and quota enforcement via ClusterQueues. A custom OpenShift web console plug-in lets developers book GPU time slots through a calendar UI without writing YAML, generating native Kueue resources under the hood. Once a reservation is made, developers can deploy models from the OpenShift AI model catalog using preconfigured hardware profiles that tie deployments to their reserved MIG slice. This enables long-running inference workloads and batch jobs like fine-tuning to share GPU resources elastically under defined access policies. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Architecting GPUaaS for Enterprise AI On-Prem](https://daily.dev/posts/architecting-gpuaas-for-enterprise-ai-on-prem-u2jlj0atd) · Towards Data Science · 3 upvotes · 0 comments - [Dynamic GPU slicing with Red Hat OpenShift and NVIDIA MIG](https://daily.dev/posts/dynamic-gpu-slicing-with-red-hat-openshift-and-nvidia-mig-guv0pfilf) · Red Hat Developer · 1 upvotes · 0 comments - [GPU Sharing in Kubernetes: How to Cut Costs and Boost GPU Utilization with Cast AI](https://daily.dev/posts/gpu-sharing-in-kubernetes-how-to-cut-costs-and-boost-gpu-utilization-with-cast-ai-hivlvubhj) · Cast AI · 0 upvotes · 0 comments - [Multitenant AI inference with dynamic resource allocation on OpenShift](https://daily.dev/posts/multitenant-ai-inference-with-dynamic-resource-allocation-on-openshift-krqyihtg7) · Red Hat Developer · 0 upvotes · 0 comments - [Fractional GPUs and GPU Rightsizing: Stop Wasting Whole Cards](https://daily.dev/posts/fractional-gpus-and-gpu-rightsizing-stop-wasting-whole-cards-wjy0saqyp) · Cast AI · 1 upvotes · 0 comments --- Tags: [#kubernetes](https://daily.dev/tags/kubernetes), [#gpu](https://daily.dev/tags/gpu), [#openshift](https://daily.dev/tags/openshift) [View this post on daily.dev](https://daily.dev/posts/implement-gpu-as-a-service-with-kueue-and-nvidia-mig-wtjs3in1t)