cc-device-plugin

Confidential Computing device plugin for Kubernetes

Introduction

This is a Kubernetes device plugin implementation that enables the registration of Confidential Computing devices in a Google Kubernetes Engine (GKE) cluster for compute workloads. With the appropriate GKE setup and this plugin deployed, your Kubernetes cluster will be able to run jobs (e.g., Attestation) that require Confidential Computing devices.

This plugin supports the following technologies on GKE:

• vTPM / AMD SEV: Exposes google.com/cc resource.
• AMD SEV-SNP: Exposes amd.com/sev-snp resource. Requires AMD SNP machines.
• Intel TDX: Exposes intel.com/tdx resource. Requires Intel TDX machines.

Prerequisites

• A GKE cluster with node pools configured to support the desired Confidential Computing technology (SEV, SEV-SNP, or TDX). This includes selecting appropriate machine types and enabling Confidential Nodes in the node pool settings.
• For SEV-SNP, ensure the node pool uses AMD SEV-SNP machine types.
• For TDX, ensure the node pool uses Intel TDX machine types.

Limitations

This plugin targets Kubernetes v1.18+ for AMD SEV. For other Confidential Computing technologies, the minimum required GKE versions (when using Ubuntu node images) are branch-dependent:

• AMD SEV-SNP: v1.33.5-gke.1350000+ or v1.34.1-gke.2037000+
• Intel TDX: v1.33.5-gke.1697000+ or v1.34.1-gke.2909000+
• Refer to Confidential VM Supported Configurations for specific version and region availability.

Deployment

The device plugin needs to be run on all the nodes that are equipped with Confidential Computing devices. The simplest way to do this is to create a Kubernetes DaemonSet, which runs a copy of a pod on all (or some) Nodes in the cluster.

We have a pre-built Docker image on Google Artifact Registry that you can use with your DaemonSet. This repository also has a pre-defined yaml file named cc-device-plugin.yaml. You can create a DaemonSet in your Kubernetes cluster by running this command using a stable version from the release repository:

kubectl create -f manifests/cc-device-plugin.yaml

or directly pull from the web using

kubectl create -f https://raw.githubusercontent.com/google/cc-device-plugin/main/manifests/cc-device-plugin.yaml

Using the Exposed Devices

To use the devices, request them in your Pod's resource limits. This will cause the device plugin to mount the appropriate device node into your container.

Example: Requesting Intel TDX

apiVersion: v1
kind: Pod
metadata:
  name: example-tdx-pod
spec:
  containers:
  - name: test-container
    image: ubuntu # Your application image
    command: ["/bin/sh", "-c", "ls -l /dev/tdx_guest; sleep 3600"]
    resources:
      limits:
        intel.com/tdx: 1 # Request TDX device
  nodeSelector:
    cloud.google.com/gke-confidential-nodes-instance-type: "TDX"
    cloud.google.com/machine-family: "c3"

Inside this container, /dev/tdx_guest will be available for interacting with the Intel Trust Domain.

Example: Requesting AMD SEV-SNP

apiVersion: v1
kind: Pod
metadata:
  name: example-sev-snp-pod
spec:
  containers:
  - name: test-container
    image: ubuntu # Your application image
    command: ["/bin/sh", "-c", "ls -l /dev/sev-guest; sleep 3600"]
    resources:
      limits:
        amd.com/sev-snp: 1 # Request SEV-SNP device
  nodeSelector:
    cloud.google.com/gke-confidential-nodes-instance-type: "SEV_SNP"
    cloud.google.com/machine-family: "n2d"

Inside this container, /dev/sev-guest will be available for interacting with the AMD Secure Processor.

Example: Requesting vTPM / AMD SEV

apiVersion: v1
kind: Pod
metadata:
  name: example-vtpm-pod
spec:
  containers:
  - name: test-container
    image: ubuntu # Your application image
    command: ["/bin/sh", "-c", "ls -l /dev/tpmrm0; sleep 3600"]
    resources:
      limits:
        google.com/cc: 1 # Request vTPM device
  nodeSelector:
    cloud.google.com/gke-confidential-nodes-instance-type: "SEV"

Inside this container, /dev/tpmrm0 will be available.

Monitoring

Applying the Prometheus monitoring manifest allows you to observe the device plugin status:

kubectl apply -f manifests/cc-device-plugin-pod-monitoring.yaml

You can view the metrics in the Cloud Monitoring Metrics Explorer using PromQL, for example to see CPU usage:

rate(process_cpu_seconds_total[5m])