Table of Contents
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.
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.
The following sections cover how to use the necessary Kubernetes SGX specific components.
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 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.
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
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/
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
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.
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.
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
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.