Hugo: fix device-plugins (#8567)
Fix misparsed lists: Add empty line before lists so that they are parsed properly.pull/8689/merge
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@ -51,8 +51,9 @@ to advertise 2 `vendor-domain/foo`.
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Then, users can request devices in a
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[Container](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#container-v1-core)
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specification as they request other types of resources, with the following limitations:
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* Extended resources are only supported as integer resources and cannot be overcommitted.
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* Devices cannot be shared among Containers.
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* Extended resources are only supported as integer resources and cannot be overcommitted.
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* Devices cannot be shared among Containers.
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Suppose a Kubernetes cluster is running a device plugin that advertises resource `vendor-domain/resource`
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on certain nodes, here is an example user pod requesting this resource:
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@ -126,8 +127,9 @@ in the plugin's
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Kubernetes device plugin support is still in alpha. As development continues, its API version can
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change in incompatible ways. We recommend that device plugin developers do the following:
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* Watch for changes in future releases.
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* Support multiple versions of the device plugin API for backward/forward compatibility.
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* Watch for changes in future releases.
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* Support multiple versions of the device plugin API for backward/forward compatibility.
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If you enable the DevicePlugins feature and run device plugins on nodes that need to be upgraded to
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a Kubernetes release with a newer device plugin API version, upgrade your device plugins
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@ -137,6 +139,7 @@ ensure the continuous functioning of the device allocations during the upgrade.
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## Examples
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For examples of device plugin implementations, see:
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* The official [NVIDIA GPU device plugin](https://github.com/NVIDIA/k8s-device-plugin)
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* it requires using [nvidia-docker 2.0](https://github.com/NVIDIA/nvidia-docker) which allows you to run GPU enabled docker containers
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* The [NVIDIA GPU device plugin for COS base OS](https://github.com/GoogleCloudPlatform/container-engine-accelerators/tree/master/cmd/nvidia_gpu).
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