node-feature-discovery/README.md

CPU Feature Discovery for Kubernetes

• Overview
• Getting Started
  • System Requirements
  • Usage
• Building from source
• Targeting Nodes with Specific Features
• License

Overview

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.

Feature sources

The current set of feature sources are the following:

• CPUID for x86 CPU details
• Intel Resource Director Technology
• Intel P-State driver

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

Command line interface

dbi-iafeature-discovery.

	Usage:
	dbi-iafeature-discovery [--no-publish --sources=<sources>]
	dbi-iafeature-discovery -h | --help
	dbi-iafeature-discovery --version

	Options:
	-h --help           Show this screen.
	--version           Output version and exit.
	--sources=<sources> Comma separated list of feature sources. [Default: cpuid,rdt,pstate]
	--no-publish        Do not publish discovered features to the cluster-local Kubernetes API server.

Intel Resource Director Technology (RDT) Features

Feature name	Description
RDTMON	Intel Cache Monitoring Technology (CMT) and Intel Memory Bandwidth Monitoring (MBM)
RDTL3CA	Intel L3 Cache Allocation Technology
RDTL2CA	Intel L2 Cache Allocation Technology

Other 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)

The published node labels encode a few pieces of information:

• A "namespace" to denote vendor-specific information (node.alpha.intel.com).
• The version of this discovery code that wrote the label, for example "node.alpha.intel.com/dbi-iafeature-discovery.version": "v0.1.0". The value of this label corresponds to the output from git describe --tags --dirty --always.
• The relevant information source for each label (e.g. cpuid).
• The name of the discovered feature as it appears in the underlying source, mostly cpuid (e.g. AESNI).

Note: only features that are available on a given node are labeled, so the only label value published for features is the string "true". This feature discovery code will not add a label with the value "false" for features that are not present.

{
  "node.alpha.intel.com/v0.1.0-cpuid-<feature-name>": "true",
  "node.alpha.intel.com/v0.1.0-rdt-<feature-name>": "true",
  "node.alpha.intel.com/v0.1.0-pstate-<feature-name>": "true"
}

System Requirements

At a minimum, you will need:

1. Linux (x86_64)
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)

Usage

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

./label-nodes.sh

The discovery script will launch a job on each 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 and RDT).

Building from source

Download the source code.

git clone https://github.com/intelsdi-x/dbi-iafeature-discovery

Build the Docker image:

cd <project-root>
make

NOTE: To override the DOCKER_REGISTRY_USER use the -e option as follows: DOCKER_REGISTRY_USER=<my-username> make docker -e

Push the Docker Image (optional)

docker push <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 intelsdi/nodelabels image, edit line 40 in the file dbi-iafeature-discovery-job.json.template to the new location (<registry-user>/<image-name>).

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": {
                "node.alpha.intel.com/v0.1.0-pstate-turbo": "true"
        }
    }
}

For more details on targeting nodes, see node selection.

License

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