# Overview [![Build Status](https://github.com/intel/intel-device-plugins-for-kubernetes/workflows/CI/badge.svg?branch=main)](https://github.com/intel/intel-device-plugins-for-kubernetes/actions?query=workflow%3ACI) [![Go Report Card](https://goreportcard.com/badge/github.com/intel/intel-device-plugins-for-kubernetes)](https://goreportcard.com/report/github.com/intel/intel-device-plugins-for-kubernetes) [![GoDoc](https://godoc.org/github.com/intel/intel-device-plugins-for-kubernetes/pkg/deviceplugin?status.svg)](https://godoc.org/github.com/intel/intel-device-plugins-for-kubernetes/pkg/deviceplugin) This repository contains a framework for developing plugins for the Kubernetes [device plugins framework](https://kubernetes.io/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins/), along with a number of device plugin implementations utilizing that framework. The [v0.24 release](https://github.com/intel/intel-device-plugins-for-kubernetes/releases/latest) is the latest feature release with its documentation available [here](https://intel.github.io/intel-device-plugins-for-kubernetes/0.24/). Table of Contents * [Prerequisites](#prerequisites) * [Plugins](#plugins) * [GPU device plugin](#gpu-device-plugin) * [FPGA device plugin](#fpga-device-plugin) * [QAT device plugin](#qat-device-plugin) * [VPU device plugin](#vpu-device-plugin) * [SGX device plugin](#sgx-device-plugin) * [DSA device plugin](#dsa-device-plugin) * [DLB device plugin](#dlb-device-plugin) * [IAA device plugin](#iaa-device-plugin) * [Device Plugins Operator](#device-plugins-operator) * [Demos](#demos) * [Workload Authors](#workload-authors) * [Developers](#developers) * [Supported Kubernetes versions](#supported-kubernetes-versions) * [Pre-built plugin images](#pre-built-plugin-images) * [License](#license) * [Security](#security) * [Related code](#related-code) * [Helm charts](#helm-charts) ## Prerequisites Prerequisites for building and running these device plugins include: - Appropriate hardware and drivers - A fully configured [Kubernetes cluster] - A working [Go environment], of at least version v1.16. ## Plugins The below sections detail existing plugins developed using the framework. ### GPU Device Plugin The [GPU device plugin](cmd/gpu_plugin/README.md) provides access to discrete (Intel® Iris® Xe MAX) and integrated GPU HW device files. The demo subdirectory contains both a [GPU plugin demo video](demo/readme.md#intel-gpu-device-plugin-demo-video) and an OpenCL sample deployment (`intelgpu-job.yaml`). ### FPGA Device Plugin The [FPGA device plugin](cmd/fpga_plugin/README.md) supports FPGA passthrough for the following hardware: - Intel® Arria® 10 devices - Intel® Stratix® 10 devices The FPGA plugin comes as three parts. - the [device plugin](#device-plugin) - the [admission controller](#admission-controller) - the [CRIO-O prestart hook](#cri-o-prestart-hook) Refer to each individual sub-components documentation for more details. Brief overviews of the sub-components are below. The demo subdirectory contains a [video](demo/readme.md#intel-fpga-device-plugin-demo-video) showing deployment and use of the FPGA plugin. Sources relating to the demo can be found in the [opae-nlb-demo](demo/opae-nlb-demo) subdirectory. #### Device Plugin The [FPGA device plugin](cmd/fpga_plugin/README.md) is responsible for discovering and reporting FPGA devices to `kubelet`. #### Admission Controller The [FPGA admission controller webhook](cmd/fpga_admissionwebhook/README.md) is responsible for performing mapping from user-friendly function IDs to the Interface ID and Bitstream ID that are required for FPGA programming. It also implements access control by namespacing FPGA configuration information. #### CRI-O Prestart Hook The [FPGA prestart CRI-O hook](cmd/fpga_crihook/README.md) performs discovery of the requested FPGA function bitstream and programs FPGA devices based on the environment variables in the workload description. ### [QAT](https://01.org/intel-quick-assist-technology) Device Plugin The [QAT plugin](cmd/qat_plugin/README.md) supports device plugin for Intel QAT adapters, and includes code [showing deployment](cmd/qat_plugin/dpdkdrv) via [DPDK](https://doc.dpdk.org/guides/cryptodevs/qat.html). The demo subdirectory includes details of both a [QAT DPDK demo](demo/readme.md#intel-quickassist-technology-device-plugin-with-dpdk-demo-video) and a [QAT OpenSSL demo](demo/readme.md#intel-quickassist-technology-device-plugin-openssl-demo-video). Source for the OpenSSL demo can be found in the [relevant subdirectory](demo/openssl-qat-engine). Details for integrating the QAT device plugin into [Kata Containers](https://katacontainers.io/) can be found in the [Kata Containers documentation repository](https://github.com/kata-containers/kata-containers/blob/main/docs/use-cases/using-Intel-QAT-and-kata.md). ### VPU Device Plugin The [VPU device plugin](cmd/vpu_plugin/README.md) supports Intel VCAC-A card (https://www.intel.com/content/dam/www/public/us/en/documents/datasheets/media-analytics-vcac-a-accelerator-card-by-celestica-datasheet.pdf) the card has: - 1 Intel Core i3-7100U processor - 12 MyriadX VPUs - 8GB DDR4 memory The demo subdirectory includes details of a OpenVINO deployment and use of the VPU plugin. Sources can be found in [openvino-demo](demo/ubuntu-demo-openvino). ### SGX Device Plugin The [SGX device plugin](cmd/sgx_plugin/README.md) allows workloads to use Intel® Software Guard Extensions (Intel® SGX) on platforms with SGX Flexible Launch Control enabled, e.g.,: - 3rd Generation Intel® Xeon® Scalable processor family, code-named “Ice Lake” - Intel® Xeon® E3 processor - Intel® NUC Kit NUC7CJYH The Intel SGX plugin comes in three parts. - the [device plugin](#sgx-plugin) - the [admission webhook](#sgx-admission-webhook) - the [SGX EPC memory registration](#sgx-epc-memory-registration) The demo subdirectory contains a [video](demo/readme.md#intel-sgx-device-plugin-demo-video) showing the deployment and use of the Intel SGX device plugin. Sources relating to the demo can be found in the [sgx-sdk-demo](demo/sgx-sdk-demo) and [sgx-aesmd-demo](demo/sgx-aesmd-demo) subdirectories. Brief overviews of the Intel SGX sub-components are given below. #### device plugin The [SGX device plugin](cmd/sgx_plugin/README.md) is responsible for discovering and reporting Intel SGX device nodes to `kubelet`. Containers requesting Intel SGX resources in the cluster should not use the device plugins resources directly. #### Intel SGX Admission Webhook The Intel SGX admission webhook is responsible for performing Pod mutations based on the `sgx.intel.com/quote-provider` pod annotation set by the user. The purpose of the webhook is to hide the details of setting the necessary device resources and volume mounts for using Intel SGX remote attestation in the cluster. Furthermore, the Intel SGX admission webhook is responsible for writing a pod/sandbox `sgx.intel.com/epc` annotation that is used by Kata Containers to dynamically adjust its virtualized Intel SGX encrypted page cache (EPC) bank(s) size. The Intel SGX admission webhook is available as part of [Intel Device Plugin Operator](cmd/operator/README.md) or as a standalone [SGX Admission webhook image](cmd/sgx_admissionwebhook/README.md). #### Intel SGX EPC memory registration The Intel SGX EPC memory available on each node is registered as a Kubernetes extended resource using node-feature-discovery (NFD). A custom NFD source hook is installed as part of [SGX device plugin](cmd/sgx_plugin/README.md) operator deployment and NFD is configured to register the Intel SGX EPC memory extended resource reported by the hook. Containers requesting Intel SGX EPC resources in the cluster use `sgx.intel.com/epc` resource which is of type [memory](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/#meaning-of-memory). ### DSA Device Plugin The [DSA device plugin](cmd/dsa_plugin/README.md) supports acceleration using the Intel Data Streaming accelerator(DSA). ### DLB Device Plugin The [DLB device plugin](cmd/dlb_plugin/README.md) supports Intel Dynamic Load Balancer accelerator(DLB). ### IAA Device Plugin The [IAA device plugin](cmd/iaa_plugin/README.md) supports acceleration using the Intel Analytics accelerator(IAA). ## Device Plugins Operator To simplify the deployment of the device plugins, a unified device plugins operator is implemented. Currently the operator has support for the DSA, DLB, FPGA, GPU, IAA, QAT, and Intel SGX device plugins. Each device plugin has its own custom resource definition (CRD) and the corresponding controller that watches CRUD operations to those custom resources. The [Device plugins operator README](cmd/operator/README.md) gives the installation and usage details. The operator is also available via [operatorhub.io](https://operatorhub.io/operator/intel-device-plugins-operator) and on Red Hat OpenShift Container Platform. ## Demos The [demo subdirectory](demo/readme.md) contains a number of demonstrations for a variety of the available plugins. ## Workload Authors For workloads to get accesss to devices managed by the plugins, the `Pod` spec must specify the hardware resources needed: ``` spec: containers: - name: demo-container image: /: resources: limits: /: X ``` The summary of resources available via plugins in this repository is given in the list below. **Device Namespace : Registered Resource(s)** * `dlb.intel.com` : `pf` or `vf` * [dlb-libdlb-demo-pod.yaml](demo/dlb-libdlb-demo-pod.yaml) * `dsa.intel.com` : `wq-user-[shared or dedicated]` * [dsa-accel-config-demo-pod.yaml](demo/dsa-accel-config-demo-pod.yaml) * `fpga.intel.com` : custom, see [mappings](cmd/fpga_admissionwebhook/README.md#mappings) * [intelfpga-job.yaml](demo/intelfpga-job.yaml) * `gpu.intel.com` : `i915` * [intelgpu-job.yaml](demo/intelgpu-job.yaml) * `iaa.intel.com` : `wq-user-[shared or dedicated]` * [iaa-qpl-demo-pod.yaml](demo/iaa-qpl-demo-pod.yaml) * `qat.intel.com` : `generic` or `cy`/`dc`/`sym`/`asym` * [crypto-perf-dpdk-pod-requesting-qat.yaml](deployments/qat_dpdk_app/base/crypto-perf-dpdk-pod-requesting-qat.yaml) * `sgx.intel.com` : `epc` * [intelsgx-job.yaml](deployments/sgx_enclave_apps/base/intelsgx-job.yaml) * `vpu.intel.com` : `hddl` * [intelvpu-job.yaml](demo/intelvpu-job.yaml) ## Developers For information on how to develop a new plugin using the framework or work on development task in this repository, see the [Developers Guide](DEVEL.md). ## Supported Kubernetes Versions Releases are made under the github [releases area](https://github.com/intel/intel-device-plugins-for-kubernetes/releases). Supported releases and matching Kubernetes versions are listed below: | Branch | Kubernetes branch/version | Status | |:------------------|:-------------------------------|:------------| | release-0.24 | Kubernetes 1.24 branch v1.24.x | supported | | release-0.23 | Kubernetes 1.23 branch v1.23.x | supported | | release-0.22 | Kubernetes 1.22 branch v1.22.x | supported | | release-0.21 | Kubernetes 1.21 branch v1.21.x | unsupported | | release-0.20 | Kubernetes 1.20 branch v1.20.x | unsupported | | release-0.19 | Kubernetes 1.19 branch v1.19.x | unsupported | | release-0.18 | Kubernetes 1.18 branch v1.18.x | unsupported | | release-0.17 | Kubernetes 1.17 branch v1.17.x | unsupported | | release-0.15 | Kubernetes 1.15 branch v1.15.x | unsupported | | release-0.11 | Kubernetes 1.11 branch v1.11.x | unsupported | [Go environment]: https://golang.org/doc/install [Kubernetes cluster]: https://kubernetes.io/docs/setup/independent/create-cluster-kubeadm/ ## Pre-built plugin images Pre-built images of the plugins are available on the 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 the Docker hub, tagged with their release version numbers in the format x.y.z, corresponding to the branches and releases in this repository. **Note:** the default deployment files and operators are configured with [imagePullPolicy](https://kubernetes.io/docs/concepts/containers/images/#updating-images) ```IfNotPresent``` and can be changed with ```scripts/set-image-pull-policy.sh```. ## License All of the source code required to build intel-device-plugins-for-kubernetes is available under Open Source licenses. The source code files identify external Go modules used. Binaries are distributed as container images on DockerHub*. Those images contain license texts and source code under `/licenses`. ## Security **Reporting a Potential Security Vulnerability**: If you have discovered potential security vulnerability in this project, please send an e-mail to secure@intel.com. Encrypt sensitive information using our [PGP public key](https://www.intel.com/content/www/us/en/security-center/pgp-public-key.html). Please provide as much information as possible, including: - The projects and versions affected - Detailed description of the vulnerability - Information on known exploits A member of the Intel Product Security Team will review your e-mail and contact you to collaborate on resolving the issue. For more information on how Intel works to resolve security issues, see [Vulnerability Handling Guidelines](https://www.intel.com/content/www/us/en/security-center/vulnerability-handling-guidelines.html). ## Related Code A related Intel SRIOV network device plugin can be found in [this repository](https://github.com/intel/sriov-network-device-plugin) ### Helm Charts The [helm charts](charts/README.md) is one way of distributing Kubernetes resources of the device plugins framework.