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Draft Kata update to use kata-deploy #95

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a359540
Draft Kata update to use kata-deploy
mikemckiernan Sep 4, 2024
ef0a90c
Clarify what Kata mgr does
mikemckiernan Sep 10, 2024
8dc1a54
Cosmetic touchups
mikemckiernan Sep 10, 2024
0eb3e6c
Add alias steps
mikemckiernan Oct 24, 2024
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Move alias step after troubleshooting
mikemckiernan Oct 24, 2024
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Show allocatable res instead of capacity
mikemckiernan Oct 24, 2024
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272 changes: 177 additions & 95 deletions gpu-operator/gpu-operator-kata.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -67,59 +67,25 @@ The following diagram shows the software components that Kubernetes uses to run
a[Kubelet] --> b[CRI] --> c[Kata\nRuntime] --> d[Lightweight\nQEMU VM] --> e[Lightweight\nGuest OS] --> f[Pod] --> g[Container]


NVIDIA supports Kata Containers by using the Confidential Containers Operator to install the Kata runtime and QEMU.
Even though the Operator isn't used for confidential computing in this configuration, the Operator
simplifies the installation of the Kata runtime.
NVIDIA supports Kata Containers by using Helm to run a daemon set that installs the Kata runtime and QEMU.

The daemon set runs the ``kata-deploy.sh`` script that performs the following actions on each node htat is labeled to run Kata Containers:

- Downloads an NVIDIA optimized Linux kernel image and initial RAM disk that provides the lightweight operating system for the virtual machines that run in QEMU.
These artifacts are downloaded from the NVIDIA container registry, nvcr.io, on each worker node.
- Configures each worker node with a runtime class, ``kata-qemu-nvidia-gpu``.

About NVIDIA Kata Manager
=========================

When you configure the GPU Operator for Kata Containers, the Operator
deploys NVIDIA Kata Manager as an operand.

The manager downloads an NVIDIA optimized Linux kernel image and initial RAM disk that
provides the lightweight operating system for the virtual machines that run in QEMU.
These artifacts are downloaded from the NVIDIA container registry, nvcr.io, on each worker node.

The manager also configures each worker node with a runtime class, ``kata-qemu-nvidia-gpu``,
and configures containerd for the runtime class.

NVIDIA Kata Manager Configuration
=================================

The following part of the cluster policy shows the fields related to the manager:

.. code-block:: yaml

kataManager:
enabled: true
config:
artifactsDir: /opt/nvidia-gpu-operator/artifacts/runtimeclasses
runtimeClasses:
- artifacts:
pullSecret: ""
url: nvcr.io/nvidia/cloud-native/kata-gpu-artifacts:ubuntu22.04-525
name: kata-qemu-nvidia-gpu
nodeSelector: {}
- artifacts:
pullSecret: ""
url: nvcr.io/nvidia/cloud-native/kata-gpu-artifacts:ubuntu22.04-535-snp
name: kata-qemu-nvidia-gpu-snp
nodeSelector: {}
repository: nvcr.io/nvidia/cloud-native
image: k8s-kata-manager
version: v0.1.0
imagePullPolicy: IfNotPresent
imagePullSecrets: []
env: []
resources: {}

The ``kata-qemu-nvidia-gpu`` runtime class is used with Kata Containers.

The ``kata-qemu-nvidia-gpu-snp`` runtime class is used with Confidential Containers
and is installed by default even though it is not used with this configuration.
The manager performs the following actions on each node that is labeled to run Kata Containers:

- Configures containerd with the ``kata-qemu-nvidia-gpu`` runtime class.
- Creates a CDI specification, ``/var/run/cdi/nvidia.com-pgpu.yaml``, for each GPU on the node.
- Loads the vhost-sock and vhost-net Linux kernel modules.

*********************************
Benefits of Using Kata Containers
Expand All @@ -136,6 +102,7 @@ The primary benefits of Kata Containers are as follows:

* Transparent deployment of unmodified containers.


****************************
Limitations and Restrictions
****************************
Expand All @@ -149,8 +116,8 @@ Limitations and Restrictions
* Support for Kata Containers is limited to the implementation described on this page.
The Operator does not support Red Hat OpenShift sandbox containers.

* Uninstalling the GPU Operator or the NVIDIA Kata Manager does not remove the files
that the manager downloads and installs in the ``/opt/nvidia-gpu-operator/artifacts/runtimeclasses/kata-qemu-nvidia-gpu/``
* Uninstalling the GPU Operator or the NVIDIA Kata Manager does not remove the
``/opt/nvidia-gpu-operator/artifacts/runtimeclasses/``
directory on the worker nodes.

* NVIDIA supports the Operator and Kata Containers with the containerd runtime only.
Expand Down Expand Up @@ -197,7 +164,7 @@ Prerequisites

* Your hosts are configured to support IOMMU.

If the output from running ``ls /sys/kernel/iommu_groups`` includes ``0``, ``1``, and so on,
If the output from running ``ls -1 /sys/kernel/iommu_groups | wc -l`` includes a value greater than ``0``,
then your host is configured for IOMMU.

If a host is not configured or you are unsure, add the ``intel_iommu=on`` Linux kernel command-line argument.
Expand Down Expand Up @@ -228,22 +195,127 @@ Installing and configuring your cluster to support the NVIDIA GPU Operator with
This step ensures that you can continue to run traditional container workloads with GPU or vGPU workloads on some nodes in your cluster.
Alternatively, you can set the default sandbox workload to ``vm-passthrough`` to run confidential containers on all worker nodes.

#. Install the Confidential Containers Operator.
#. Install the Kata Deploy Helm chart.

This step installs the Operator and also the Kata Containers runtime that NVIDIA uses for Kata Containers.
This step runs ``kata-deploy.sh`` on each node and installs the Kata Containers runtime on each node.

#. Install the NVIDIA GPU Operator.

You install the Operator and specify options to deploy the operands that are required for Kata Containers.

After installation, you can run a sample workload.

.. |project-name| replace:: Kata Containers
*************************************
Kata Deploy Helm Chart Customizations
*************************************

The following table shows the configurable values from the Kata Deploy Helm chart.

.. list-table::
:widths: 20 50 30
:header-rows: 1

* - Parameter
- Description
- Default

* - ``kataDeploy.allowedHypervisorAnnotations``
- Specifies the
`hypervisor annotations <https://github.com/kata-containers/kata-containers/blob/main/docs/how-to/how-to-set-sandbox-config-kata.md#hypervisor-options>`__
to enable in the Kata configuration file on each node.
Specify a space-separated string of values such as ``enable_iommu initrd kernel``.
- None

* - ``kataDeploy.createRuntimeClasses``
- When set to ``true``, the ``kata-deploy.sh`` script installs the runtime classes on the nodes.
- ``false``

* - ``kataDeploy.createDefaultRuntimeClass``
- When set to ``true``, the ``kata-deploy.sh`` script sets the runtime class specified in the ``defaultShim`` field as the default Kata runtime class.
- ``false``

* - ``kataDeploy.debug``
- When set to ``true``, the ``kata-deploy.sh`` script enables debugging and a debug console in the Kata configuration file on each node.
- ``false``

* - ``kataDeploy.defaultShim``
- Specifies the shim to set as the default Kata runtime class.
This field is ignored unless you specify ``createDefaultRuntimeClass: true``.
- None

* - ``kataDeploy.imagePullPolicy``
- Specifies the image pull policy for the ``kata-deploy`` container.
- ``Always``

* - ``kataDeploy.k8sDistribution``
- Specifies the Kubernetes platform.
The Helm chart uses the value to set the platform-specific location of the containerd configuration file.

Supported values are ``k8s``, ``k3s``, ``rke2``, and ``k0s``.
- ``k8s``

* - ``kataDeploy.repository``
- Specifies the image repository for the ``kata-deploy`` container.
- ``nvcr.io/nvidia/cloud-native``

* - ``kataDeploy.shims``
- Specifies the shim binaries to install on each node.
Specify a space-separated string of values.
- ``qemu-nvidia-gpu``

* - ``kataDeploy.version``
- Specifies the version of the ``kata-deploy`` container to run.
- ``latest``


**********************************
Install the Kata Deploy Helm Chart
**********************************

Perform the following steps to install the Helm chart:

#. Label the nodes to run virtual machines in containers. Label only the nodes that you want to run with Kata Containers:

.. code-block:: console

$ kubectl label node <node-name> nvidia.com/gpu.workload.config=vm-passthrough

#. Add and update the NVIDIA Helm repository:

.. code-block:: console

$ helm repo add nvidia https://helm.ngc.nvidia.com/nvidia \
&& helm repo update

#. Specify at least the following options when you install the chart:

.. code-block:: console

$ helm install --wait --generate-name \
-n kube-system \
nvidia/kata-deploy \
--set kataDeploy.createRuntimeClasses=true

#. Optional: Verify the installation.

- Confirm the ``kata-deploy`` containers are running:

.. code-block:: console

$ kubectl get pods -n kube-system -l name=kata-deploy

- Confirm the runtime class is installed:

.. code-block:: console

$ kubectl get runtimeclass kata-qemu-nvidia-gpu

*Example Output*

.. include:: gpu-operator-confidential-containers.rst
:start-after: start-install-coco-operator
:end-before: end-install-coco-operator
.. code-block:: output

NAME HANDLER AGE
kata-qemu-nvidia-gpu kata-qemu-nvidia-gpu 23s

*******************************
Install the NVIDIA GPU Operator
Expand All @@ -262,15 +334,16 @@ Perform the following steps to install the Operator for use with Kata Containers
&& helm repo update

#. Specify at least the following options when you install the Operator.
If you want to run |project-name| by default on all worker nodes, also specify ``--set sandboxWorkloads.defaultWorkload=vm-passthough``.
If you want to run Kata Containers by default on all worker nodes, also specify ``--set sandboxWorkloads.defaultWorkload=vm-passthough``.

.. code-block:: console

$ helm install --wait --generate-name \
-n gpu-operator --create-namespace \
nvidia/gpu-operator \
--set sandboxWorkloads.enabled=true \
--set kataManager.enabled=true
--set kataManager.enabled=true \
--set kataManager.config.runtimeClasses=null

*Example Output*

Expand All @@ -296,7 +369,6 @@ Verification
*Example Output*

.. code-block:: output
:emphasize-lines: 5,8

NAME READY STATUS RESTARTS AGE
gpu-operator-57bf5d5769-nb98z 1/1 Running 0 6m21s
Expand All @@ -307,7 +379,7 @@ Verification
nvidia-sandbox-validator-9wjm4 1/1 Running 0 2m37s
nvidia-vfio-manager-vg4wp 1/1 Running 0 3m36s

#. Verify that the ``kata-qemu-nvidia-gpu`` and ``kata-qemu-nvidia-gpu-snp`` runtime classes are available:
#. Verify that the ``kata-qemu-nvidia-gpu`` runtime classes is available:

.. code-block:: console

Expand All @@ -316,53 +388,27 @@ Verification
*Example Output*

.. code-block:: output
:emphasize-lines: 6, 7

NAME HANDLER AGE
kata kata 37m
kata-clh kata-clh 37m
kata-clh-tdx kata-clh-tdx 37m
kata-qemu kata-qemu 37m
kata-qemu-nvidia-gpu kata-qemu-nvidia-gpu 96s
kata-qemu-nvidia-gpu-snp kata-qemu-nvidia-gpu-snp 96s
kata-qemu-sev kata-qemu-sev 37m
kata-qemu-snp kata-qemu-snp 37m
kata-qemu-tdx kata-qemu-tdx 37m
nvidia nvidia 97s


#. Optional: If you have host access to the worker node, you can perform the following steps:
#. Optional: If you have host access to the worker node, confirm that the host uses the ``vfio-pci`` device driver for GPUs:

#. Confirm that the host uses the ``vfio-pci`` device driver for GPUs:

.. code-block:: console

$ lspci -nnk -d 10de:

*Example Output*

.. code-block:: output
:emphasize-lines: 3

65:00.0 3D controller [0302]: NVIDIA Corporation GA102GL [A10] [10de:2236] (rev a1)
Subsystem: NVIDIA Corporation GA102GL [A10] [10de:1482]
Kernel driver in use: vfio-pci
Kernel modules: nvidiafb, nouveau

#. Confirm that NVIDIA Kata Manager installed the ``kata-qemu-nvidia-gpu`` runtime class files:

.. code-block:: console
.. code-block:: console

$ ls -1 /opt/nvidia-gpu-operator/artifacts/runtimeclasses/kata-qemu-nvidia-gpu/
$ lspci -nnk -d 10de:

*Example Output*
*Example Output*

.. code-block:: output
.. code-block:: output
:emphasize-lines: 3

configuration-nvidia-gpu-qemu.toml
kata-ubuntu-jammy-nvidia-gpu.initrd
vmlinuz-5.xx.x-xxx-nvidia-gpu
...
65:00.0 3D controller [0302]: NVIDIA Corporation GA102GL [A10] [10de:2236] (rev a1)
Subsystem: NVIDIA Corporation GA102GL [A10] [10de:1482]
Kernel driver in use: vfio-pci
Kernel modules: nvidiafb, nouveau


*********************
Expand Down Expand Up @@ -395,7 +441,7 @@ A pod specification for a Kata container requires the following:
#. Create a file, such as ``cuda-vectoradd-kata.yaml``, like the following example:

.. code-block:: yaml
:emphasize-lines: 6,8,15
:emphasize-lines: 6,7,9,16

apiVersion: v1
kind: Pod
Expand Down Expand Up @@ -446,7 +492,6 @@ A pod specification for a Kata container requires the following:

$ kubectl delete -f cuda-vectoradd-kata.yaml


Troubleshooting Workloads
=========================

Expand All @@ -466,6 +511,43 @@ If the sample workload does not run, confirm that you labelled nodes to run virt
kata-worker-3 Ready <none> 10d v1.27.3


******************************************
Optional: Configuring a GPU Resource Alias
******************************************

By default, GPU resources are exposed on nodes with a name like ``nvidia.com/GA102GL_A10``.
You can configure the NVIDIA Sandbox Device Plugin so that nodes also expose GPUs with an alias like ``nvidia.com/pgpu``.

#. Patch the cluster policy with a command like the following example:

.. code-block:: console

$ kubectl patch clusterpolicies.nvidia.com/cluster-policy --type=merge \
-p '{"spec": {"sandboxDevicePlugin": {"env":[{"name": "P_GPU_ALIAS", "value":"pgpu"}]}}}'

The sandbox device plugin daemon set pods restart.

#. Optional: Describe a node to confirm the alias:

.. code-block:: console

$ kubectl describe node <node-name>

*Partial Output*

.. code-block:: output

...
Allocatable:
cpu: 16
ephemeral-storage: 1922145660Ki
hugepages-1Gi: 0
hugepages-2Mi: 0
memory: 65488292Ki
nvidia.com/GA102GL_A10: 0
nvidia.com/pgpu: 1


************************
About the Pod Annotation
************************
Expand Down