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Intel Software Guard Extensions (SGX) device plugin for Kubernetes

Table of Contents

Introduction

The Intel SGX device plugin and related components allow workloads to use Intel SGX on platforms with SGX Flexible Launch Control enabled, e.g.,:

  • 3rd Generation Intel® Xeon® Scalable Platform, code-named “Ice Lake”
  • Intel® Xeon® E3
  • Intel® NUC Kit NUC7CJYH

The SGX solution comes in three parts:

This README covers setting up all three components.

Modes and Configuration options

The SGX plugin can take a number of command line arguments, summarised in the following table:

Flag Argument Meaning
-enclave-limit int the number of containers per worker node allowed to use /dev/sgx_enclave device node (default: 20)
-provision-limit int the number of containers per worker node allowed to use /dev/sgx_provision device node (default: 20)

The plugin also accepts a number of other arguments related to logging. Please use the -h option to see the complete list of logging related options.

Installation

The following sections cover how to use the necessary Kubernetes SGX specific components.

Prerequisites

The component has the same basic dependencies as the generic plugin framework dependencies.

The SGX device plugin requires Linux Kernel SGX drivers to be available. These drivers are available in Linux since 5.11. The SGX DCAP out-of-tree driver (v1.41 and later) is also known to work.

The hardware platform must support SGX Flexible Launch Control.

The SGX deployment depends on having cert-manager installed. See its installation instructions here.

Pre-built Images

Pre-built images are available on Docker Hub. These images are automatically built and uploaded to the hub from the latest main branch of this repository.

Release tagged images of the components are also available on Docker Hub, tagged with their release version numbers in the format x.y.z, corresponding to the branches and releases in this repository. Thus the easiest way to deploy Intel SGX components in your cluster is to follow the steps below.

The deployment YAML files supplied with the components in this repository use the images with the devel tag by default. If you do not build your own local images, your Kubernetes cluster may pull down the devel images from Docker Hub by default.

Where <RELEASE_VERSION> needs to be substituted with the desired release tag or main to get devel images.

Installation Using the Operator

First, deploy node-feature-discovery:

$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/nfd/overlays/sgx?ref=<RELEASE_VERSION>
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/nfd/overlays/node-feature-rules?ref=<RELEASE_VERSION>

Note: The default configuration assumes that the in-tree driver is used and enabled (CONFIG_X86_SGX=y). If the SGX DCAP out-of-tree driver is used, the kernel.config match expression must be removed.

Next, deploy the Intel Device plugin operator:

$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/operator/default?ref=<RELEASE_VERSION>

Note: See the operator deployment details for its dependencies and for setting it up on systems behind proxies.

Finally, deploy the SGX device plugin with the operator

$ kubectl apply -f https://raw.githubusercontent.com/intel/intel-device-plugins-for-kubernetes/<RELEASE_VERSION>/deployments/operator/samples/deviceplugin_v1_sgxdeviceplugin.yaml

Installation Using kubectl

There are two alternative ways to deploy SGX device plugin using kubectl.

The first approach involves deployment of the SGX DaemonSet YAML and node-feature-discovery with the necessary configuration.

There is a kustomization for deploying everything:

$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/sgx_plugin/overlays/epc-nfd/

The second approach has a lesser deployment footprint. It does not require NFD, but a helper daemonset that creates sgx.intel.com/capable='true' node label and advertises EPC capacity to the API server.

The following kustomization is used for this approach:

$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/sgx_plugin/overlays/epc-register/

Additionally, SGX admission webhook must be deployed

$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/sgx_admissionwebhook/

Verify Plugin Registration

Verification of the plugin deployment and detection of SGX hardware can be confirmed by examining the resource allocations on the nodes:

$ kubectl describe node <node name> | grep sgx.intel.com
                   nfd.node.kubernetes.io/extended-resources: sgx.intel.com/epc
 sgx.intel.com/enclave:    20
 sgx.intel.com/epc:        98566144
 sgx.intel.com/provision:  20
 sgx.intel.com/enclave:    20
 sgx.intel.com/epc:        98566144
 sgx.intel.com/provision:  20
 sgx.intel.com/enclave    1           1
 sgx.intel.com/epc        400         400
 sgx.intel.com/provision  1           1

Testing and Demos

SGX ECDSA Remote Attestation

The SGX remote attestation allows a relying party to verify that the software is running inside an Intel® SGX enclave on a platform that has the trusted computing base up to date.

The demo guides to run an SGX DCAP/ECDSA quote generation in on a single-node kubernetes cluster using Intel® reference SGX PCK Certificate Cache Service (PCCS) that is configured to service localhost connections.

Read more about SGX Remote Attestation.

Remote Attestation Prerequisites

For the SGX ECDSA Remote Attestation demo to work, the platform must be correctly registered and a PCCS running.

For documentation to set up Intel® reference PCCS, refer to: Intel® Software Guard Extensions (Intel® SGX) Services and Intel® Software Guard Extensions SDK for Linux

Furthermore, the Kubernetes cluster must be set up according the instructions above.

Build the image

The demo uses container images build from Intel® SGX SDK and DCAP releases.

To build the demo images:

$ cd ${INTEL_DEVICE_PLUGINS_SRC}
$ make sgx-aesmd-demo
...
Successfully tagged intel/sgx-aesmd-demo:devel
$ make sgx-sdk-demo
...
Successfully tagged intel/sgx-sdk-demo:devel

Deploy the pods

The demo runs Intel aesmd (architectural enclaves service daemon) that is responsible for generating SGX quotes for workloads. It is deployed with hostNetwork: true to allow connections to localhost PCCS.

$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/sgx_aesmd?ref=<RELEASE_VERSION>
$ kubectl get pods
  NAME                     READY     STATUS    RESTARTS   AGE
  intel-sgx-aesmd-mrnm8                1/1     Running   0          3h47m
  sgxdeviceplugin-sample-z5dcq-llwlw   1/1     Running   0          28m

Note: For quick experiments, kind can be used to deploy the cluster. With kind, host path /var/run/aesmd/ must be mounted to the nodes manually using Extra Mounts.
Example:

$ cat kind_config.yaml
kind: Cluster
apiVersion: kind.x-k8s.io/v1alpha4
name: <your_node_name>
nodes:
- role: control-plane
  extraMounts:
  - hostPath: /var/run/aesmd
    containerPath: /var/run/aesmd
    propagation: Bidirectional 

And bootstrap kind with it
$ kind create cluster --config kind_config.yaml

The sample application runs SGX DCAP Quote Generation sample:

$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/sgx_enclave_apps/overlays/sgx_ecdsa_aesmd_quote?ref=<RELEASE_VERSION>
$ kubectl get pods
  NAME                                 READY   STATUS      RESTARTS   AGE
  intel-sgx-aesmd-mrnm8                1/1     Running     0          3h55m
  ecdsa-quote-intelsgx-demo-job-vtq84  0/1     Completed   0          4s
  sgxdeviceplugin-sample-z5dcq-llwlw   1/1     Running     0          35m
$ kubectl logs ecdsa-quote-intelsgx-demo-job-vtq84

  Step1: Call sgx_qe_get_target_info:succeed!
  Step2: Call create_app_report:succeed!
  Step3: Call sgx_qe_get_quote_size:succeed!
  Step4: Call sgx_qe_get_quote:succeed!cert_key_type = 0x5

Note: The deployment example above uses kustomize that is available in kubectl since Kubernetes v1.14 release.