Add docs for 26.3.0 release

Signed-off-by: Abigail McCarthy <20771501+a-mccarthy@users.noreply.github.com>

Co-authored-by: Rajath Agasthya <rajathagasthya@gmail.com>

Author: a-mccarthy

gpu-operator/cdi.rst

@@ -16,13 +16,15 @@
 
 .. headings # #, * *, =, -, ^, "
 
-############################################################
-Container Device Interface (CDI) Support in the GPU Operator
-############################################################
+#################################################################################
+Container Device Interface (CDI) and Node Resource Interface (NRI) Plugin Support
+#################################################################################
 
-************************************
-About the Container Device Interface
-************************************
+This page gives an overview of CDI and NRI Plugin support in the GPU Operator.
+
+**************************************
+About Container Device Interface (CDI)
+**************************************
 
 The `Container Device Interface (CDI) <https://github.com/cncf-tags/container-device-interface/blob/main/SPEC.md>`_
 is an open specification for container runtimes that abstracts what access to a device, such as an NVIDIA GPU, means,
@@ -31,23 +33,22 @@ ensure that a device is available in a container. CDI simplifies adding support
 the specification is applicable to all container runtimes that support CDI.
 
 Starting with GPU Operator v25.10.0, CDI is used by default for enabling GPU support in containers running on Kubernetes.
-Specifically, CDI support in container runtimes, e.g. containerd and cri-o, is used to inject GPU(s) into workload
+Specifically, CDI support in container runtimes, like containerd and cri-o, is used to inject GPU(s) into workload
 containers. This differs from prior GPU Operator releases where CDI was used via a CDI-enabled ``nvidia`` runtime class.
 
 Use of CDI is transparent to cluster administrators and application developers.
 The benefits of CDI are largely to reduce development and support for runtime-specific
 plugins.
 
-********************************
-Enabling CDI During Installation
-********************************
+************
+Enabling CDI 
+************
 
 CDI is enabled by default during installation in GPU Operator v25.10.0 and later.
 Follow the instructions for installing the Operator with Helm on the :doc:`getting-started` page.
 
 CDI is also enabled by default during a Helm upgrade to GPU Operator v25.10.0 and later.
 
-*******************************
 Enabling CDI After Installation
 *******************************
 
@@ -125,3 +126,79 @@ disable CDI and use the legacy NVIDIA Container Toolkit stack instead with the f
           nvidia.com/gpu.deploy.operator-validator=true \
           nvidia.com/gpu.present=true \
           --overwrite
+
+
+.. _nri-plugin:
+
+**********************************************
+About the Node Resource Interface (NRI) Plugin
+**********************************************
+
+Node Resource Interface (NRI) is a standardized interface for plugging in extensions, called NRI Plugins, to OCI-compatible container runtimes like CRI-O and containerd. 
+NRI Plugins serve as hooks which intercept pod and container lifecycle events and perform functions including inject devices to a container, topology aware placement strategies, and more.
+For more details on NRI, refer to the `NRI overview <https://github.com/containerd/nri/tree/main?tab=readme-ov-file#background>`_ in the containerd repository.
+
+When enabled in the GPU Operator, the NRI Plugin is managed by the NVIDIA Container Toolkit andprovides an alternative to the ``nvidia`` runtime class to provision GPU workload pods. 
+It allows the GPU Operator to extend the container runtime behaviour without modifying the container runtime itself.
+This feature also simplifies deployments on platforms like k3s, k0s, or RKE, because the GPU Operator no longer needs you to set  values like ``CONTAINERD_CONFIG``, ``CONTAINERD_SOCKET``, or ``RUNTIME_CONFIG_SOURCE`` for the Container Toolkit.
+
+***********************
+Enabling the NRI Plugin
+***********************
+
+The NRI Plugin requires the following:
+
+- CDI to be enabled in the GPU Operator.
+
+- CRI-O v1.34.0 or later or containerd v1.7.30, v2.1.x, or v2.2.x.
+  If you are not using the latest containerd version, check that both CDI and NRI are enabled in the containerd configuration file before deploying GPU Operator.
+
+To enable the NRI Plugin during installation, follow the instructions for installing the Operator with Helm on the :doc:`getting-started` page and include the ``--set  cdi.nriPluginEnabled=true`` argument in you Helm command. 
+
+Enabling the NRI Plugin After Installation
+******************************************
+
+#. Enable NRI Plugin by modifying the cluster policy:
+
+   .. code-block:: console
+
+     $ kubectl patch clusterpolicies.nvidia.com/cluster-policy --type='json' \
+         -p='[{"op": "replace", "path": "/spec/cdi/nriPluginEnabled", "value":true}]'
+
+   *Example Output*
+
+   .. code-block:: output
+
+    clusterpolicy.nvidia.com/cluster-policy patched
+
+#. (Optional) Confirm that the container toolkit and device plugin pods restart:
+
+   .. code-block:: console
+
+     $ kubectl get pods -n gpu-operator
+
+   *Example Output*
+
+   .. literalinclude:: ./manifests/output/nri-get-pods-restart.txt
+      :language: output
+      :emphasize-lines: 6,9
+
+
+************************
+Disabling the NRI Plugin
+************************
+
+Disable the NRI Plugin and use the ``nvidia`` runtime class instead with the following procedure:
+
+Disable the NRI Plugin by modifying the cluster policy:
+
+.. code-block:: console
+
+   $ kubectl patch clusterpolicies.nvidia.com/cluster-policy --type='json' \
+         -p='[{"op": "replace", "path": "/spec/cdi/nriPluginEnabled", "value":false}]'
+
+*Example Output*
+
+.. code-block:: output
+
+   clusterpolicy.nvidia.com/cluster-policy patched