Prerequisites#

Complete the following prerequisites before deploying Confidential Containers. Refer to the Supported Platforms page for validated hardware and software versions.

Hardware and BIOS#

Use a supported platform configured for Confidential Computing. For more information on machine setup, refer to Supported Platforms.
Ensure hosts are configured to enable hardware virtualization and Access Control Services (ACS). With some AMD CPUs and BIOSes, ACS might be grouped under Advanced Error Reporting (AER). Enable these features in the host BIOS.
Configure hosts to support IOMMU. You can check if your host is configured for IOMMU by running the following command:
```
$ ls /sys/kernel/iommu_groups
```
If the output of this command includes 0, 1, and so on, then your host is configured for IOMMU.

If the host is not configured or if you are unsure, add the amd_iommu=on Linux kernel command-line argument. For most Linux distributions, add the argument to the /etc/default/grub file, for instance:
```
...
GRUB_CMDLINE_LINUX_DEFAULT="quiet amd_iommu=on modprobe.blacklist=nouveau"
...
```
After making the change, configure the bootloader
```
$ sudo update-grub
```
Example Output:
```
Sourcing file `/etc/default/grub'
Generating grub configuration file ...
Found linux image: /boot/vmlinuz-5.15.0-generic
Found initrd image: /boot/initrd.img-5.15.0-generic
done
```
Reboot the host after configuring the bootloader.

Note

After configuring IOMMU, you might see QEMU warnings about PCI P2P DMA when running GPU workloads. These are expected and can be safely ignored. Refer to Limitations and Restrictions for details.
Ensure that no NVIDIA GPU drivers are installed on the host. Confidential Containers uses VFIO to pass GPUs directly to the confidential VM, and host-level GPU drivers interfere with VFIO device binding.

To check if NVIDIA GPU drivers are installed, run the following command:
```
$ lsmod | grep nvidia
```
If the output is empty, no NVIDIA GPU drivers are loaded. If modules such as nvidia, nvidia_uvm, or nvidia_modeset are listed, NVIDIA GPU drivers are present and must be removed before proceeding. Refer to Removing the Driver in the NVIDIA Driver Installation Guide.

Kubernetes Cluster#

A Kubernetes cluster with cluster administrator privileges. Refer to the Supported Software Components table for supported Kubernetes versions.
Helm installed on your cluster. Refer to the Helm documentation for installation instructions.
Enable the KubeletPodResourcesGet and RuntimeClassInImageCriApi Kubelet feature gates on your cluster.
- KubeletPodResourcesGet: Enabled by default on Kubernetes v1.34 and later. On older versions, you must enable it explicitly. The Kata runtime uses this feature gate to query the Kubelet Pod Resources API and discover allocated GPU devices during sandbox creation.
- RuntimeClassInImageCriApi: Alpha since Kubernetes v1.29 and is not enabled by default. This feature gate is required to support pod deployments that use multiple snapshotters side-by-side.
Add both feature gates to your Kubelet configuration (typically /var/lib/kubelet/config.yaml):
```
apiVersion: kubelet.config.k8s.io/v1beta1
kind: KubeletConfiguration
featureGates:
  KubeletPodResourcesGet: true
  RuntimeClassInImageCriApi: true
```
If your config.yaml already has a featureGates section, add the gates to the existing section rather than creating a duplicate.

Restart the Kubelet service to apply the changes:
```
$ sudo systemctl restart kubelet
```

Next Steps#

After completing the prerequisites, proceed to Deploy Confidential Containers.