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docs: DRA updates for 26.7.0 - #458

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mikemckiernan merged 5 commits into
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mikemckiernan:mmck-dra
Aug 21, 2026
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docs: DRA updates for 26.7.0#458
mikemckiernan merged 5 commits into
NVIDIA:mainfrom
mikemckiernan:mmck-dra

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@mikemckiernan

@mikemckiernan mikemckiernan commented Aug 10, 2026

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Documentation preview

https://nvidia.github.io/cloud-native-docs/review/pr-458

Comment thread gpu-operator/dra-intro-install.rst Outdated
Comment thread gpu-operator/dra-intro-install.rst Outdated
This functionality replaces the traditional GPU allocation method used by the NVIDIA Kubernetes Device Plugin.
* ComputeDomains: an abstraction for secure `Multi-Node NVLink (MNNVL) <https://docs.nvidia.com/multi-node-nvlink-systems/index.html>`_ for NVIDIA GB200 and similar systems.
GPU Operator management of DRA is available as a technology preview.
Technology preview features are not supported in production environments and are not functionally complete.

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As per our decision, these two lines should be replaced with some version of this:

GPU Operator supports the DRA Driver as a modern alternative to the Device Plugin, but certain features of the DRA Driver are in alpha and not fully supported. As such, the DRA Driver does not currently provide full feature parity with the Device Plugin and it is important that users gain awareness of the features that are not yet implemented or fully supported in the DRA Driver before selecting it for their production needs.

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Changed, but not verbatim. The subject of your text is the software, the subject of my proposal is the reader ("you").

Comment thread gpu-operator/dra-intro-install.rst Outdated

.. _known-issues:
The DRA Driver for NVIDIA GPUs and the NVIDIA Kubernetes Device Plugin provide alternative mechanisms for allocating NVIDIA GPU resources.
The mechanisms do not provide feature parity.

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I put a version of this above under the important note that replaces the previously discussed Tech Preview statement

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I think the about feature parity is duplicated now, in two back to back sections!

Comment thread gpu-operator/dra-intro-install.rst Outdated
Comment thread gpu-operator/dra-intro-install.rst
Comment thread gpu-operator/gpu-driver-upgrades.rst Outdated
Comment thread gpu-operator/install-gpu-operator-air-gapped.rst Outdated
Comment thread gpu-operator/getting-started.rst Outdated
Comment thread gpu-operator/gpu-driver-configuration.rst Outdated
Comment thread gpu-operator/install-gpu-operator-air-gapped.rst Outdated
Comment thread gpu-operator/dra-intro-install.rst Outdated
With the DRA Driver for NVIDIA GPUs, your Kubernetes workloads can allocate and consume the following two types of resources:
GPU Operator supports the DRA Driver as a more recent alternative to the NVIDIA Device Plugin for Kubernetes.
However, some features of the DRA driver are alpha maturity and not fully supported.
The driver does not provide feature parity with the device plugin.

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@mikemckiernan this gives an impression that some key features are missing in the DRA driver. That is actually quite opposite and it has much more advanced and flexible device allocation features. Instead we should just point users to carefully review current limitations {minimum k8s version, feature gate dependencies etc}.

For example:
* - Device Injection and Managed Components
- Requires a Container Device Interface (CDI)-compatible runtime.
``GPUCluster`` manages DRA, ComputeDomains, NVIDIA Data Center GPU Manager (DCGM), DCGM Exporter, and the DRA validator.

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We have to highlight the fact that with GPUCluster the GPU stack is much simpler and manages DRA drivers, DCGM/Exporter and a validation pod.

Comment thread gpu-operator/dra-intro-install.rst Outdated
* ``NVMLDeviceHealthCheck`` is alpha and disabled by default.
The gRPC health probe reports kubelet plugin availability, and DCGM provides telemetry.
Neither provides DRA allocation health status.
* This release does not provide scheduler-accounted capacity sharing among independent ``ResourceClaim`` objects.

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the ConsumableShares feature is supported as an alpha like other feature gates and users can explore that just like other features.

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@mikemckiernan I think a block diagram showing the operand stack managed by both GPUCluster and ClusterPolicy would be good at the high level showcasing the differences clearly. This can be added as a follow up as well.

Signed-off-by: Mike McKiernan <mmckiernan@nvidia.com>
Signed-off-by: Mike McKiernan <mmckiernan@nvidia.com>
Signed-off-by: Mike McKiernan <mmckiernan@nvidia.com>
Signed-off-by: Mike McKiernan <mmckiernan@nvidia.com>
Signed-off-by: Mike McKiernan <mmckiernan@nvidia.com>
@mikemckiernan
mikemckiernan merged commit c1d0dd5 into NVIDIA:main Aug 21, 2026
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3 participants