NVIDIA

    NVIDIA/gpu-operator

    NVIDIA GPU Operator creates, configures, and manages GPUs in Kubernetes

    graphics
    kubernetes
    cuda
    gpu
    nvidia
    Go
    Apache-2.0
    2.9K stars
    585 forks
    2.9K GitHub watchers
    Updated Oct 27, 2026
    View on GitHub

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    3 releases in the last 90 days, the latest 13 days ago, with 108 contributors on GitHub.

    Gained 8% fewer stars in the last 90 days than in the 90 days before.

    Use Cases & Benefits

    • Automates the deployment and management of NVIDIA GPU software components in Kubernetes clusters.
    • Simplifies GPU node provisioning by managing drivers, runtimes, and monitoring as containerized components.
    • Use for scaling GPU resources dynamically in cloud or on-prem Kubernetes environments without custom OS images.
    • Use for automating lifecycle management of NVIDIA drivers and device plugins across heterogeneous Kubernetes nodes.
    • Use for enabling GPU monitoring and telemetry integration using NVIDIA DCGM within Kubernetes clusters.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    Apache 2.0

    Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.

    Community files

    • README: present
    • Contributing guide: present
    • Code of conduct: present

    Watch-outs

    No watch-outs from GStars' checks.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    Kubernetes provides access to special hardware resources such as NVIDIA GPUs, NICs, Infiniband adapters and other devices through the device plugin framework. However, configuring and managing nodes with these hardware resources requires configuration of multiple software components such as drivers, container runtimes or other libraries which are difficult and prone to errors. The NVIDIA GPU Operator uses the operator framework within Kubernetes to automate the management of all NVIDIA software components needed to provision GPU. These components include the NVIDIA drivers (to enable CUDA), Kubernetes device plugin for GPUs, the NVIDIA Container Runtime, automatic node labelling, DCGM based monitoring and others.

    The GPU Operator allows administrators of Kubernetes clusters to manage GPU nodes just like CPU nodes in the cluster. Instead of provisioning a special OS image for GPU nodes, administrators can rely on a standard OS image for both CPU and GPU nodes and then rely on the GPU Operator to provision the required software components for GPUs.

    Excerpt from the NVIDIA/gpu-operator README on GitHub (Apache-2.0 license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Forks

    585+59

    Open issues

    123+39

    Compared with peers in Graphics

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth

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