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Published: Jun 25, 2018 License: Apache-2.0 Imports: 22 Imported by: 0


Node feature discovery for Kubernetes

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NOTE: We are gathering evidence in order to graduate from the Kubernetes incubator. If you are a user of the project, please add yourself to this list with as much detail as you are comfortable providing (name and email optional).


This software enables node feature discovery for Kubernetes. It detects hardware features available on each node in a Kubernetes cluster, and advertises those features using node labels.

This project uses GitHub milestones for release planning.

Command line interface


  node-feature-discovery [--no-publish] [--sources=<sources>] [--label-whitelist=<pattern>]
     [--oneshot | --sleep-interval=<seconds>]
  node-feature-discovery -h | --help
  node-feature-discovery --version

  -h --help                   Show this screen.
  --version                   Output version and exit.
  --sources=<sources>         Comma separated list of feature sources.
                              [Default: cpuid,rdt,pstate,memory,network,storage,selinux]
  --no-publish                Do not publish discovered features to the
                              cluster-local Kubernetes API server.
  --label-whitelist=<pattern> Regular expression to filter label names to
                              publish to the Kubernetes API server. [Default: ]
  --oneshot                   Label once and exit.
  --sleep-interval=<seconds>  Time to sleep between re-labeling. Non-positive
                              value implies no re-labeling (i.e. infinite
                              sleep). [Default: 60s]

Feature discovery

Feature sources

The current set of feature sources are the following:

Feature labels

The published node labels encode a few pieces of information:

  • A "namespace" (e.g.
  • The version of this discovery code that wrote the label, according to git describe --tags --dirty --always.
  • The source for each label (e.g. cpuid).
  • The name of the discovered feature as it appears in the underlying source, (e.g. AESNI from cpuid).

Note: only features that are available on a given node are labeled, so the only label value published for features is the string "true".

  "": "v0.2.0",
  "<feature-name>": "true",
  "<feature-name>": "true",
  "<feature-name>": "true",
  "<feature-name>": "true",
  "<feature-name>": "true",
  "<feature-name>": "true",
  "<feature-name>": "true"

The --sources flag controls which sources to use for discovery.

Note: Consecutive runs of node-feature-discovery will update the labels on a given node. If features are not discovered on a consecutive run, the corresponding label will be removed. This includes any restrictions placed on the consecutive run, such as restricting discovered features with the --label-whitelist option.

Intel Resource Director Technology (RDT) Features
Feature name Description
RDTMON Intel RDT Monitoring Technology
RDTCMT Intel Cache Monitoring (CMT)
RDTMBM Intel Memory Bandwidth Monitoring (MBM)
RDTL3CA Intel L3 Cache Allocation Technology
RDTL2CA Intel L2 Cache Allocation Technology
RDTMBA Intel Memory Bandwidth Allocation (MBA) Technology
X86 CPUID Features (Partial List)
Feature name Description
ADX Multi-Precision Add-Carry Instruction Extensions (ADX)
AESNI Advanced Encryption Standard (AES) New Instructions (AES-NI)
AVX Advanced Vector Extensions (AVX)
AVX2 Advanced Vector Extensions 2 (AVX2)
BMI1 Bit Manipulation Instruction Set 1 (BMI)
BMI2 Bit Manipulation Instruction Set 2 (BMI2)
SSE4.1 Streaming SIMD Extensions 4.1 (SSE4.1)
SSE4.2 Streaming SIMD Extensions 4.2 (SSE4.2)
SGX Software Guard Extensions (SGX)
Memory Features
Feature name Description
numa Multiple memory nodes i.e. NUMA architecture detected
Arm64 CPUID Features (Partial List)
Feature name Description
AES Announcing the Advanced Encryption Standard
EVSTRM Event Stream Frequency Features
FPHP Half Precision(16bit) Floating Point Data Processing Instructions
ASIMDHP Half Precision(16bit) Asimd Data Processing Instructions
ATOMICS Atomic Instructions to the A64
ASIMRDM Support for Rounding Double Multiply Add/Subtract
PMULL Optional Cryptographic and CRC32 Instructions
JSCVT Perform Conversion to Match Javascript
DCPOP Persistent Memory Support
Network Features
Feature name Description
SRIOV Single Root Input/Output Virtualization (SR-IOV) enabled Network Interface Card
Storage Features
Feature name Description
nonrotationaldisk Non-rotational disk, like SSD, is present in the node
Selinux Features
Feature name Description
selinux selinux is enabled on the node

Getting started

System requirements
  1. Linux (x86_64/Arm64)
  2. [kubectl] kubectl-setup (properly set up and configured to work with your Kubernetes cluster)
  3. [Docker] docker-down (only required to build and push docker images)

Feature discovery is preferably run as a Kubernetes DaemonSet. There is an example spec that can be used as a template, or, as is when just trying out the service:

kubectl create -f rbac.yaml
kubectl create -f node-feature-discovery-daemonset.json.template

If you have RBAC authorization enabled (as is the default e.g. with clusters initialized with kubeadm) you need to configure the appropriate ClusterRoles, ClusterRoleBindings and a ServiceAccount in order for NFD to create node labels. The provided templates will configure these for you.

When run as a daemonset, nodes are re-labeled at an interval specified using the --sleep-interval option. In the template the default interval is set to 60s which is also the default when no --sleep-interval is specified.

Feature discovery can alternatively be configured as a one-shot job. There is an example script in this repo that demonstrates how to deploy the job to unlabeled nodes.


The discovery script will launch a job on each unlabeled node in the cluster. When the job runs, it contacts the Kubernetes API server to add labels to the node to advertise hardware features (initially, from cpuid, RDT, p-state and network).


Building from source

Download the source code.

git clone

Build the Docker image:

cd <project-root>

NOTE: Our default docker image is hosted in To override the QUAY_REGISTRY_USER use the -e option as follows: QUAY_REGISTRY_USER=<my-username> make docker -e

Push the Docker Image (optional)

docker push <quay-domain-name>/<registry-user>/<image-name>:<version>

Change the job spec to use your custom image (optional):

To use your published image from the step above instead of the image, edit line 40 in the file node-feature-discovery-job.json.template to the new location (<quay-domain-name>/<registry-user>/<image-name>[:<version>]).

Targeting Nodes with Specific Features

Nodes with specific features can be targeted using the nodeSelector field. The following example shows how to target nodes with Intel TurboBoost enabled.

    "apiVersion": "v1",
    "kind": "Pod",
    "metadata": {
        "labels": {
            "env": "test"
        "name": "golang-test"
    "spec": {
        "containers": [
                "image": "golang",
                "name": "go1",
        "nodeSelector": {
                "": "true"

For more details on targeting nodes, see node selection.


Github issues

Design proposal

Kubernetes Incubator

This is a Kubernetes Incubator project. The project was established 2016-08-29. The incubator team for the project is:

  • Sponsor: Dawn Chen (@dchen1107)
  • Champion: David Oppenheimer (@davidopp)
  • SIG: sig-node


This is open source software released under the Apache 2.0 License.


A demo on the benefits of using node feature discovery can be found in demo.


The Go Gopher

There is no documentation for this package.


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