42 KiB
Node feature discovery for Kubernetes
- Overview
- Command line interface
- Feature discovery
- Extended resources (experimental)
- Getting started
- Building from source
- Targeting nodes with specific features
- References
- License
- Demo
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.
NFD consists of two software components:
- nfd-master is responsible for labeling Kubernetes node objects
- nfd-worker is detects features and communicates them to nfd-master. One instance of nfd-worker is supposed to be run on each node of the cluster
Command line interface
You can run NFD in stand-alone Docker containers e.g. for testing purposes. This is useful for checking features-detection.
NFD-Master
When running as a standalone container labeling is expected to fail because
Kubernetes API is not available. Thus, it is recommended to use --no-publish
command line flag. E.g.
$ docker run --rm --name=nfd-test <NFD_CONTAINER_IMAGE> nfd-master --no-publish
2019/02/01 14:48:21 Node Feature Discovery Master <NFD_VERSION>
2019/02/01 14:48:21 gRPC server serving on port: 8080
Command line flags of nfd-master:
$ docker run --rm <NFD_CONTAINER_IMAGE> nfd-master --help
...
nfd-master.
Usage:
nfd-master [--no-publish] [--label-whitelist=<pattern>] [--port=<port>]
[--ca-file=<path>] [--cert-file=<path>] [--key-file=<path>]
[--verify-node-name] [--extra-label-ns=<list>] [--resource-labels=<list>]
nfd-master -h | --help
nfd-master --version
Options:
-h --help Show this screen.
--version Output version and exit.
--port=<port> Port on which to listen for connections.
[Default: 8080]
--ca-file=<path> Root certificate for verifying connections
[Default: ]
--cert-file=<path> Certificate used for authenticating connections
[Default: ]
--key-file=<path> Private key matching --cert-file
[Default: ]
--verify-node-name Verify worker node name against CN from the TLS
certificate. Only has effect when TLS authentication
has been enabled.
--no-publish Do not publish feature labels
--label-whitelist=<pattern> Regular expression to filter label names to
publish to the Kubernetes API server.
NB: the label namespace is omitted i.e. the filter
is only applied to the name part after '/'.
[Default: ]
--extra-label-ns=<list> Comma separated list of allowed extra label namespaces
[Default: ]
--resource-labels=<list> Comma separated list of labels to be exposed as extended resources.
[Default: ]
NFD-Worker
In order to run nfd-worker as a "stand-alone" container against your standalone nfd-master you need to run them in the same network namespace:
$ docker run --rm --network=container:nfd-test <NFD_CONTAINER_IMAGE> nfd-worker
2019/02/01 14:48:56 Node Feature Discovery Worker <NFD_VERSION>
...
If you just want to try out feature discovery without connecting to nfd-master,
pass the --no-publish
flag to nfd-worker.
Command line flags of nfd-worker:
$ docker run --rm <CONTAINER_IMAGE_ID> nfd-worker --help
...
nfd-worker.
Usage:
nfd-worker [--no-publish] [--sources=<sources>] [--label-whitelist=<pattern>]
[--oneshot | --sleep-interval=<seconds>] [--config=<path>]
[--options=<config>] [--server=<server>] [--server-name-override=<name>]
[--ca-file=<path>] [--cert-file=<path>] [--key-file=<path>]
nfd-worker -h | --help
nfd-worker --version
Options:
-h --help Show this screen.
--version Output version and exit.
--config=<path> Config file to use.
[Default: /etc/kubernetes/node-feature-discovery/nfd-worker.conf]
--options=<config> Specify config options from command line. Config
options are specified in the same format as in the
config file (i.e. json or yaml). These options
will override settings read from the config file.
[Default: ]
--ca-file=<path> Root certificate for verifying connections
[Default: ]
--cert-file=<path> Certificate used for authenticating connections
[Default: ]
--key-file=<path> Private key matching --cert-file
[Default: ]
--server=<server> NFD server address to connecto to.
[Default: localhost:8080]
--server-name-override=<name> Name (CN) expect from server certificate, useful
in testing
[Default: ]
--sources=<sources> Comma separated list of feature sources.
[Default: cpu,custom,iommu,kernel,local,memory,network,pci,storage,system,usb]
--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.
NB: the label namespace is omitted i.e. the filter
is only applied to the name part after '/'.
[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]
NOTE Some feature sources need certain directories and/or files from the
host mounted inside the NFD container. Thus, you need to provide Docker with the
correct --volume
options in order for them to work correctly when run
stand-alone directly with docker run
. See the
template spec
for up-to-date information about the required volume mounts.
Feature discovery
Feature sources
The current set of feature sources are the following:
- CPU
- Custom
- IOMMU
- Kernel
- Memory
- Network
- PCI
- Storage
- System
- USB
- Local (hooks for user-specific features)
Feature labels
The published node labels encode a few pieces of information:
- Namespace, i.e.
feature.node.kubernetes.io
- The source for each label (e.g.
cpu
). - The name of the discovered feature as it appears in the underlying
source, (e.g.
cpuid.AESNI
from cpu). - The value of the discovered feature.
Feature label names adhere to the following pattern:
<namespace>/<source name>-<feature name>[.<attribute name>]
The last component (i.e. attribute-name
) is optional, and only used if a
feature logically has sub-hierarchy, e.g. sriov.capable
and
sriov.configure
from the network
source.
{
"feature.node.kubernetes.io/cpu-<feature-name>": "true",
"feature.node.kubernetes.io/custom-<feature-name>": "true",
"feature.node.kubernetes.io/iommu-<feature-name>": "true",
"feature.node.kubernetes.io/kernel-<feature name>": "<feature value>",
"feature.node.kubernetes.io/memory-<feature-name>": "true",
"feature.node.kubernetes.io/network-<feature-name>": "true",
"feature.node.kubernetes.io/pci-<device label>.present": "true",
"feature.node.kubernetes.io/storage-<feature-name>": "true",
"feature.node.kubernetes.io/system-<feature name>": "<feature value>",
"feature.node.kubernetes.io/usb-<device label>.present": "<feature value>",
"feature.node.kubernetes.io/<file name>-<feature name>": "<feature value>"
}
The --sources
flag controls which sources to use for discovery.
Note: Consecutive runs of nfd-worker 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.
CPU Features
Feature name | Attribute | Description |
---|---|---|
cpuid | <cpuid flag> | CPU capability is supported |
hardware_multithreading | Hardware multithreading, such as Intel HTT, enabled (number of logical CPUs is greater than physical CPUs) | |
power | sst_bf.enabled | Intel SST-BF (Intel Speed Select Technology - Base frequency) enabled |
pstate | turbo | Set to 'true' if turbo frequencies are enabled in Intel pstate driver, set to 'false' if they have been disabled. |
rdt | 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 |
The (sub-)set of CPUID attributes to publish is configurable via the
attributeBlacklist
and attributeWhitelist
cpuid options of the cpu source.
If whitelist is specified, only whitelisted attributes will be published. With
blacklist, only blacklisted attributes are filtered out. attributeWhitelist
has priority over attributeBlacklist
. For examples and more information
about configurability, see Configuration Options.
By default, the following CPUID flags have been blacklisted:
BMI1, BMI2, CLMUL, CMOV, CX16, ERMS, F16C, HTT, LZCNT, MMX, MMXEXT, NX, POPCNT,
RDRAND, RDSEED, RDTSCP, SGX, SSE, SSE2, SSE3, SSE4.1, SSE4.2 and SSSE3.
NOTE The cpuid features advertise supported CPU capabilities, that is, a capability might be supported but not enabled.
X86 CPUID Attributes (Partial List)
Attribute | 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) |
Arm CPUID Attribute (Partial List)
Attribute | Description |
---|---|
IDIVA | Integer divide instructions available in ARM mode |
IDIVT | Integer divide instructions available in Thumb mode |
THUMB | Thumb instructions |
FASTMUL | Fast multiplication |
VFP | Vector floating point instruction extension (VFP) |
VFPv3 | Vector floating point extension v3 |
VFPv4 | Vector floating point extension v4 |
VFPD32 | VFP with 32 D-registers |
HALF | Half-word loads and stores |
EDSP | DSP extensions |
NEON | NEON SIMD instructions |
LPAE | Large Physical Address Extensions |
Arm64 CPUID Attribute (Partial List)
Attribute | 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 |
Custom Features
The Custom feature source allows the user to define features based on a mix of predefined rules. A rule is provided input witch affects its process of matching for a defined feature.
To aid in making Custom Features clearer, we define a general and a per rule nomenclature, keeping things as consistent as possible.
General Nomenclature & Definitions
Rule :Represents a matching logic that is used to match on a feature.
Rule Input :The input a Rule is provided. This determines how a Rule performs the match operation.
Matcher :A composition of Rules, each Matcher may be composed of at most one instance of each Rule.
Custom Features Format (using the Nomenclature defined above)
- name: <feature name>
matchOn:
- <Rule-1>: <Rule-1 Input>
[<Rule-2>: <Rule-2 Input>]
- <Matcher-2>
- ...
- ...
- <Matcher-N>
- <custom feature 2>
- ...
- ...
- <custom feature M>
Matching process
Specifying Rules to match on a feature is done by providing a list of Matchers. Each Matcher contains one or more Rules.
Logical OR is performed between Matchers and logical AND is performed between Rules of a given Matcher.
Rules
PciId Rule
Nomenclature
Attribute :A PCI attribute.
Element :An identifier of the PCI attribute.
The PciId Rule allows matching the PCI devices in the system on the following Attributes: class
,vendor
and
device
. A list of Elements is provided for each Attribute.
Format
pciId :
class: [<class id>, ...]
vendor: [<vendor id>, ...]
device: [<device id>, ...]
Matching is done by performing a logical OR between Elements of an Attribute and logical AND between the specified Attributes for each PCI device in the system. At least one Attribute must be specified. Missing attributes will not partake in the matching process.
UsbId Rule
Nomenclature
Attribute :A USB attribute.
Element :An identifier of the USB attribute.
The UsbId Rule allows matching the USB devices in the system on the following Attributes: class
,vendor
and
device
. A list of Elements is provided for each Attribute.
Format
usbId :
class: [<class id>, ...]
vendor: [<vendor id>, ...]
device: [<device id>, ...]
Matching is done by performing a logical OR between Elements of an Attribute and logical AND between the specified Attributes for each USB device in the system. At least one Attribute must be specified. Missing attributes will not partake in the matching process.
LoadedKMod Rule
Nomenclature
Element :A kernel module
The LoadedKMod Rule allows matching the loaded kernel modules in the system against a provided list of Elements.
Format
loadedKMod : [<kernel module>, ...]
Matching is done by performing logical AND for each provided Element, i.e the Rule will match if all provided Elements (kernel modules) are loaded in the system.
Example
custom:
- name: "my.kernel.feature"
matchOn:
- loadedKMod: ["kmod1", "kmod2"]
- name: "my.pci.feature"
matchOn:
- pciId:
vendor: ["15b3"]
device: ["1014", "1017"]
- name: "my.usb.feature"
matchOn:
- usbId:
vendor: ["1d6b"]
device: ["0003"]
- name: "my.combined.feature"
matchOn:
- loadedKMod : ["vendor_kmod1", "vendor_kmod2"]
pciId:
vendor: ["15b3"]
device: ["1014", "1017"]
- name: "my.accumulated.feature"
matchOn:
- loadedKMod : ["some_kmod1", "some_kmod2"]
- pciId:
vendor: ["15b3"]
device: ["1014", "1017"]
In the example above:
- A node would contain the label:
feature.node.kubernetes.io/custom-my.kernel.feature=true
if the node haskmod1
ANDkmod2
kernel modules loaded. - A node would contain the label:
feature.node.kubernetes.io/custom-my.pci.feature=true
if the node contains a PCI device with a PCI vendor ID of15b3
AND PCI device ID of1014
OR1017
. - A node would contain the label:
feature.node.kubernetes.io/custom-my.usb.feature=true
if the node contains a USB device with a USB vendor ID of1d6b
AND USB device ID of0003
. - A node would contain the label:
feature.node.kubernetes.io/custom-my.combined.feature=true
ifvendor_kmod1
ANDvendor_kmod2
kernel modules are loaded AND the node contains a PCI device with a PCI vendor ID of15b3
AND PCI device ID of1014
or1017
. - A node would contain the label:
feature.node.kubernetes.io/custom-my.accumulated.feature=true
ifsome_kmod1
ANDsome_kmod2
kernel modules are loaded OR the node contains a PCI device with a PCI vendor ID of15b3
AND PCI device ID of1014
OR1017
.
Statically defined features
Some feature labels which are common and generic are defined statically in the custom
feature source.
A user may add additional Matchers to these feature labels by defining them in the nfd-worker
configuration file.
Feature | Attribute | Description |
---|---|---|
rdma | capable | The node has an RDMA capable Network adapter |
rdma | enabled | The node has the needed RDMA modules loaded to run RDMA traffic |
IOMMU Features
Feature name | Description |
---|---|
enabled | IOMMU is present and enabled in the kernel |
Kernel Features
Feature | Attribute | Description |
---|---|---|
config | <option name> | Kernel config option is enabled (set 'y' or 'm'). Default options are NO_HZ , NO_HZ_IDLE , NO_HZ_FULL and PREEMPT |
selinux | enabled | Selinux is enabled on the node |
version | full | Full kernel version as reported by /proc/sys/kernel/osrelease (e.g. '4.5.6-7-g123abcde') |
major | First component of the kernel version (e.g. '4') | |
minor | Second component of the kernel version (e.g. '5') | |
revision | Third component of the kernel version (e.g. '6') |
Kernel config file to use, and, the set of config options to be detected are configurable. See configuration options for more information.
Memory Features
Feature | Attribute | Description |
---|---|---|
numa | Multiple memory nodes i.e. NUMA architecture detected | |
nv | present | NVDIMM device(s) are present |
nv | dax | NVDIMM region(s) configured in DAX mode are present |
Network Features
Feature | Attribute | Description |
---|---|---|
sriov | capable | Single Root Input/Output Virtualization (SR-IOV) enabled Network Interface Card(s) present |
configured | SR-IOV virtual functions have been configured |
PCI Features
Feature | Attribute | Description |
---|---|---|
<device label> | present | PCI device is detected |
<device label> | sriov.capable | Single Root Input/Output Virtualization (SR-IOV) enabled PCI device present |
<device label>
is composed of raw PCI IDs, separated by underscores.
The set of fields used in <device label>
is configurable, valid fields being
class
, vendor
, device
, subsystem_vendor
and subsystem_device
.
Defaults are class
and vendor
. An example label using the default
label fields:
feature.node.kubernetes.io/pci-1200_8086.present=true
Also the set of PCI device classes that the feature source detects is configurable. By default, device classes (0x)03, (0x)0b40 and (0x)12, i.e. GPUs, co-processors and accelerator cards are detected.
USB Features
Feature | Attribute | Description |
---|---|---|
<device label> | present | USB device is detected |
<device label>
is composed of raw USB IDs, separated by underscores.
The set of fields used in <device label>
is configurable, valid fields being
class
, vendor
, and device
.
Defaults are class
, vendor
and device
. An example label using the default
label fields:
feature.node.kubernetes.io/usb-fe_1a6e_089a.present=true
See configuration options for more information on NFD config.
Storage Features
Feature name | Description |
---|---|
nonrotationaldisk | Non-rotational disk, like SSD, is present in the node |
System Features
Feature | Attribute | Description |
---|---|---|
os_release | ID | Operating system identifier |
VERSION_ID | Operating system version identifier (e.g. '6.7') | |
VERSION_ID.major | First component of the OS version id (e.g. '6') | |
VERSION_ID.minor | Second component of the OS version id (e.g. '7') |
Feature Detector Hooks (User-specific Features)
NFD has a special feature source named local which is designed for getting the labels from user-specific feature detector. It provides a mechanism for users to implement custom feature sources in a pluggable way, without modifying nfd source code or Docker images. The local feature source can be used to advertise new user-specific features, and, for overriding labels created by the other feature sources.
The local feature source gets its labels by two different ways:
- It tries to execute files found under
/etc/kubernetes/node-feature-discovery/source.d/
directory. The hook files must be executable and they are supposed to print all discovered features instdout
, one per line. With ELF binaries static linking is recommended as the selection of system libraries available in the NFD release image is very limited. Other runtimes currently supported by the NFD stock image are bash and perl. - It reads files found under
/etc/kubernetes/node-feature-discovery/features.d/
directory. The file content is expected to be similar to the hook output (described above).
These directories must be available inside the Docker image so Volumes and
VolumeMounts must be used if standard NFD images are used. The given template
files mount by default the source.d
and the features.d
directories
respectively from /etc/kubernetes/node-feature-discovery/source.d/
and
/etc/kubernetes/node-feature-discovery/features.d/
from the host. You should
update them to match your needs.
In both cases, the labels can be binary or non binary, using either <name>
or
<name>=<value>
format.
Unlike the other feature sources, the name of the file, instead of the name of
the feature source (that would be local
in this case), is used as a prefix in
the label name, normally. However, if the <name>
of the label starts with a
slash (/
) it is used as the label name as is, without any additional prefix.
This makes it possible for the user to fully control the feature label names,
e.g. for overriding labels created by other feature sources.
You can also override the default namespace of your labels using this format:
<namespace>/<name>[=<value>]
. You must whitelist your namespace using the
--extra-label-ns
option on the master. In this case, the name of the
file will not be added to the label name. For example, if you want to add the
label my.namespace.org/my-label=value
, your hook output or file must contains
my.namespace.org/my-label=value
and you must add
--extra-label-ns=my.namespace.org
on the master command line.
stderr
output of the hooks is propagated to NFD log so it can be used for
debugging and logging.
Injecting Labels from Other Pods
One use case for the hooks and/or feature files is detecting features in other
Pods outside NFD, e.g. in Kubernetes device plugins. It is possible to mount
the source.d
and/or features.d
directories common with the NFD Pod and
deploy the custom hooks/features there. NFD will periodically scan the
directories and run any hooks and read any feature files it finds. The
example nfd-worker deployment template
contains hostPath
mounts for sources.d
and features.d
directories. By
using the same mounts in the secondary Pod (e.g. device plugin) you have
created a shared area for delivering hooks and feature files to NFD.
A Hook Example
User has a shell script
/etc/kubernetes/node-feature-discovery/source.d/my-source
which has the
following stdout
output:
MY_FEATURE_1
MY_FEATURE_2=myvalue
/override_source-OVERRIDE_BOOL
/override_source-OVERRIDE_VALUE=123
override.namespace/value=456
which, in turn, will translate into the following node labels:
feature.node.kubernetes.io/my-source-MY_FEATURE_1=true
feature.node.kubernetes.io/my-source-MY_FEATURE_2=myvalue
feature.node.kubernetes.io/override_source-OVERRIDE_BOOL=true
feature.node.kubernetes.io/override_source-OVERRIDE_VALUE=123
override.namespace/value=456
A File Example
User has a file
/etc/kubernetes/node-feature-discovery/features.d/my-source
which contains the
following lines:
MY_FEATURE_1
MY_FEATURE_2=myvalue
/override_source-OVERRIDE_BOOL
/override_source-OVERRIDE_VALUE=123
override.namespace/value=456
which, in turn, will translate into the following node labels:
feature.node.kubernetes.io/my-source-MY_FEATURE_1=true
feature.node.kubernetes.io/my-source-MY_FEATURE_2=myvalue
feature.node.kubernetes.io/override_source-OVERRIDE_BOOL=true
feature.node.kubernetes.io/override_source-OVERRIDE_VALUE=123
override.namespace/value=456
NFD tries to run any regular files found from the hooks directory. Any
additional data files your hook might need (e.g. a configuration file) should
be placed in a separate directory in order to avoid NFD unnecessarily trying to
execute these. You can use a subdirectory under the hooks directory, for
example /etc/kubernetes/node-feature-discovery/source.d/conf/
.
NOTE! NFD will blindly run any executables placed/mounted in the hooks directory. It is the user's responsibility to review the hooks for e.g. possible security implications.
NOTE! Be careful when creating and/or updating hook or feature files while
NFD is running. In order to avoid race conditions you should write into a
temporary file (outside the source.d
and features.d
directories), and,
atomically create/update the original file by doing a filesystem move
operation.
Extended resources (experimental)
This feature is experimental and by no means a replacement for the usage of device plugins.
Labels which have integer values, can be promoted to Kubernetes extended
resources by listing them to the master --resource-labels
command line flag.
These labels won't then show in the node label section, they will appear only
as extended resources.
An example use-case for the extended resources could be based on a hook which
creates a label for the node SGX EPC memory section size. By giving the name of
that label in the --resource-labels
flag, that value will then turn into an
extended resource of the node, allowing PODs to request that resource and the
Kubernetes scheduler to schedule such PODs to only those nodes which have a
sufficient capacity of said resource left.
Similar to labels, the default namespace feature.node.kubernetes.io
is
automatically prefixed to the extended resource, if the promoted label doesn't
have a namespace.
Example usage of the command line arguments, using a new namespace:
nfd-master --resource-labels=my_source-my.feature,sgx.some.ns/epc --extra-label-ns=sgx.some.ns
The above would result in following extended resources provided that related labels exist:
sgx.some.ns/epc: <label value>
feature.node.kubernetes.io/my_source-my.feature: <label value>
Getting started
For a stable version with ready-built images see the latest released version (release notes).
If you want to use the latest development version (master branch) you need to build your own custom image.
System requirements
- Linux (x86_64/Arm64/Arm)
- kubectl (properly set up and configured to work with your Kubernetes cluster)
- Docker (only required to build and push docker images)
Usage
nfd-master
Nfd-master runs as a deployment (with a replica count of 1), by default it prefers running on the cluster's master nodes but will run on worker nodes if no master nodes are found.
For High Availability, you should simply increase the replica count of the deployment object. You should also look into adding inter-pod affinity to prevent masters from running on the same node. However note that inter-pod affinity is costly and is not recommended in bigger clusters.
You can use the template spec provided to deploy nfd-master, or
use nfd-master.yaml
generated by Makefile
. The latter includes
image:
and namespace:
definitions that match the latest built
image. Example:
make IMAGE_TAG=<IMAGE_TAG>
docker push <IMAGE_TAG>
kubectl create -f nfd-master.yaml
Nfd-master listens for connections from nfd-worker(s) and connects to the Kubernetes API server to add node labels advertised by them.
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 template will configure these for you.
nfd-worker
Nfd-worker is preferably run as a Kubernetes DaemonSet. There is an
example spec (nfd-worker-daemonset.yaml.template
) that can be used
as a template, or, as is when just trying out the service. Similarly
to nfd-master above, the Makefile
also generates
nfd-worker-daemonset.yaml
from the template that you can use to
deploy the latest image. Example:
make IMAGE_TAG=<IMAGE_TAG>
docker push <IMAGE_TAG>
kubectl create -f nfd-worker-daemonset.yaml
Nfd-worker connects to the nfd-master service to advertise hardware features.
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. Also, the configuration file is re-read on
each iteration providing a simple mechanism of run-time reconfiguration.
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 in the cluster.
./label-nodes.sh [<IMAGE_TAG>]
The label-nodes.sh script tries to launch as many jobs as there are Ready nodes. Note that this approach does not guarantee running once on every node. For example, if some node is tainted NoSchedule or fails to start a job for some other reason, then some other node will run extra job instance(s) to satisfy the request and the tainted/failed node does not get labeled.
nfd-master and nfd-worker in the same Pod
You can also run nfd-master and nfd-worker inside a single pod (skip the sed
part if running the latest released version):
sed -E s',^(\s*)image:.+$,\1image: <YOUR_IMAGE_REPO>:<YOUR_IMAGE_TAG>,' nfd-daemonset-combined.yaml.template > nfd-daemonset-combined.yaml
kubectl apply -f nfd-daemonset-combined.yaml
Similar to the nfd-worker setup above, this creates a DaemonSet that schedules an NFD Pod an all worker nodes, with the difference that the Pod also also contains an nfd-master instance. In this case no nfd-master service is run on the master node(s), but, the worker nodes are able to label themselves.
This may be desirable e.g. in single-node setups.
TLS authentication
NFD supports mutual TLS authentication between the nfd-master and nfd-worker instances. That is, nfd-worker and nfd-master both verify that the other end presents a valid certificate.
TLS authentication is enabled by specifying --ca-file
, --key-file
and
--cert-file
args, on both the nfd-master and nfd-worker instances.
The template specs provided with NFD contain (commented out) example
configuration for enabling TLS authentication.
The Common Name (CN) of the nfd-master certificate must match the DNS name of the nfd-master Service of the cluster. By default, nfd-master only check that the nfd-worker has been signed by the specified root certificate (--ca-file). Additional hardening can be enabled by specifying --verify-node-name in nfd-master args, in which case nfd-master verifies that the NodeName presented by nfd-worker matches the Common Name (CN) of its certificate. This means that each nfd-worker requires a individual node-specific TLS certificate.
Usage demo
Configuration options
Nfd-worker supports a configuration file. The default location is
/etc/kubernetes/node-feature-discovery/nfd-worker.conf
, but,
this can be changed by specifying the--config
command line flag.
Configuration file is re-read on each labeling pass (determined by
--sleep-interval
) which makes run-time re-configuration of nfd-worker
possible.
Worker configuration file is read inside the container, and thus, Volumes and VolumeMounts are needed to make your configuration available for NFD. The preferred method is to use a ConfigMap which provides easy deployment and re-configurability. For example, create a config map using the example config as a template:
cp nfd-worker.conf.example nfd-worker.conf
vim nfd-worker.conf # edit the configuration
kubectl create configmap nfd-worker-config --from-file=nfd-worker.conf
Then, configure Volumes and VolumeMounts in the Pod spec (just the relevant snippets shown below):
...
containers:
volumeMounts:
- name: nfd-worker-config
mountPath: "/etc/kubernetes/node-feature-discovery/"
...
volumes:
- name: nfd-worker-config
configMap:
name: nfd-worker-config
...
You could also use other types of volumes, of course. That is, hostPath if different config for different nodes would be required, for example.
The (empty-by-default) example config is used as a config in the NFD Docker image. Thus, this can be used as a default configuration in custom-built images.
Configuration options can also be specified via the --options
command line
flag, in which case no mounts need to be used. The same format as in the config
file must be used, i.e. JSON (or YAML). For example:
--options='{"sources": { "pci": { "deviceClassWhitelist": ["12"] } } }'
Configuration options specified from the command line will override those read from the config file.
Currently, the only available configuration options are related to the CPU, PCI and Kernel feature sources.
Building from source
Download the source code:
git clone https://github.com/kubernetes-sigs/node-feature-discovery
Build the container image:
See customizing the build below for altering the
container image registry, for example.
cd <project-root>
make
Push the container image:
Optional, this example with Docker.
docker push <IMAGE_TAG>
Change the job spec to use your custom image (optional):
To use your published image from the step above instead of the
k8s.gcr.io/nfd/node-feature-discovery
image, edit image
attribute in the spec template(s) to the new location
(<registry-name>/<image-name>[:<version>]
).
Customizing the Build
There are several Makefile variables that control the build process and the name of the resulting container image.
Variable | Description | Default value |
---|---|---|
IMAGE_BUILD_CMD | Command to build the image | docker build |
IMAGE_BUILD_EXTRA_OPTS | Extra options to pass to build command | empty |
IMAGE_PUSH_CMD | Command to push the image to remote registry | docker push |
IMAGE_REGISTRY | Container image registry to use | k8s.gcr.io/nfd |
IMAGE_NAME | Container image name | node-feature-discovery |
IMAGE_TAG_NAME | Container image tag name | <nfd version> |
IMAGE_REPO | Container image repository to use | <IMAGE_REGISTRY>/<IMAGE_NAME> |
IMAGE_TAG | Full image:tag to tag the image with | <IMAGE_REPO>/<IMAGE_NAME> |
K8S_NAMESPACE | nfd-master and nfd-worker namespace | kube-system |
KUBECONFIG | Kubeconfig for running e2e-tests | empty |
E2E_TEST_CONFIG | Parameterization file of e2e-tests (see example) | empty |
For example, to use a custom registry:
make IMAGE_REGISTRY=<my custom registry uri>
Or to specify a build tool different from Docker:
make IMAGE_BUILD_CMD="buildah bud"
Testing
Unit tests are automatically run as part of the container image build. You can also run them manually in the source code tree by simply running:
make test
End-to-end tests are built on top of the e2e test framework of Kubernetes, and, they required a cluster to run them on. For running the tests on your test cluster you need to specify the kubeconfig to be used:
make e2e-test KUBECONFIG=$HOME/.kube/config
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:
feature.node.kubernetes.io/cpu-pstate.turbo: 'true'
For more details on targeting nodes, see node selection.
Node Annotations
NFD annotates nodes it is running on:
Annotation | Description |
---|---|
nfd.node.kubernetes.io/master.version | Version of the nfd-master instance running on the node. Informative use only. |
nfd.node.kubernetes.io/worker.version | Version of the nfd-worker instance running on the node. Informative use only. |
nfd.node.kubernetes.io/feature-labels | Comma-separated list of node labels managed by NFD. NFD uses this internally so must not be edited by users. |
nfd.node.kubernetes.io/extended-resources | Comma-separated list of node extended resources managed by NFD. NFD uses this internally so must not be edited by users. |
Unapplicable annotations are not created, i.e. for example master.version is only created on nodes running nfd-master.
References
Github issues
Governance
This is a SIG-node subproject, hosted under the Kubernetes SIGs organization in Github. The project was established in 2016 as a Kubernetes Incubator project and migrated to Kubernetes SIGs in 2018.
License
This is open source software released under the Apache 2.0 License.
Demo
A demo on the benefits of using node feature discovery can be found in demo.