oc get tuned.tuned.openshift.io/default -o yaml -n openshift-cluster-node-tuning-operator
Learn about the Node Tuning Operator and how you can use it to manage node-level tuning by orchestrating the tuned daemon.
The Node Tuning Operator helps you manage node-level tuning by orchestrating the TuneD daemon and achieves low latency performance by using the Performance Profile controller. The majority of high-performance applications require some level of kernel tuning. The Node Tuning Operator provides a unified management interface to users of node-level sysctls and more flexibility to add custom tuning specified by user needs.
The Operator manages the containerized TuneD daemon for OpenShift Container Platform as a Kubernetes daemon set. It ensures the custom tuning specification is passed to all containerized TuneD daemons running in the cluster in the format that the daemons understand. The daemons run on all nodes in the cluster, one per node.
Node-level settings applied by the containerized TuneD daemon are rolled back on an event that triggers a profile change or when the containerized TuneD daemon is terminated gracefully by receiving and handling a termination signal.
The Node Tuning Operator uses the Performance Profile controller to implement automatic tuning to achieve low latency performance for OpenShift Container Platform applications.
The cluster administrator configures a performance profile to define node-level settings such as the following:
Updating the kernel to kernel-rt.
Choosing CPUs for housekeeping.
Choosing CPUs for running workloads.
Currently, disabling CPU load balancing is not supported by cgroup v2. As a result, you might not get the desired behavior from performance profiles if you have cgroup v2 enabled. Enabling cgroup v2 is not recommended if you are using performance profiles. |
The Node Tuning Operator is part of a standard OpenShift Container Platform installation in version 4.1 and later.
In earlier versions of OpenShift Container Platform, the Performance Addon Operator was used to implement automatic tuning to achieve low latency performance for OpenShift applications. In OpenShift Container Platform 4.11 and later, this functionality is part of the Node Tuning Operator. |
Use this process to access an example Node Tuning Operator specification.
Run the following command to access an example Node Tuning Operator specification:
oc get tuned.tuned.openshift.io/default -o yaml -n openshift-cluster-node-tuning-operator
The default CR is meant for delivering standard node-level tuning for the OpenShift Container Platform platform and it can only be modified to set the Operator Management state. Any other custom changes to the default CR will be overwritten by the Operator. For custom tuning, create your own Tuned CRs. Newly created CRs will be combined with the default CR and custom tuning applied to OpenShift Container Platform nodes based on node or pod labels and profile priorities.
While in certain situations the support for pod labels can be a convenient way of automatically delivering required tuning, this practice is discouraged and strongly advised against, especially in large-scale clusters. The default Tuned CR ships without pod label matching. If a custom profile is created with pod label matching, then the functionality will be enabled at that time. The pod label functionality will be deprecated in future versions of the Node Tuning Operator. |
The following are the default profiles set on a cluster.
apiVersion: tuned.openshift.io/v1
kind: Tuned
metadata:
name: default
namespace: openshift-cluster-node-tuning-operator
spec:
profile:
- data: |
[main]
summary=Optimize systems running OpenShift (provider specific parent profile)
include=-provider-${f:exec:cat:/var/lib/tuned/provider},openshift
name: openshift
recommend:
- profile: openshift-control-plane
priority: 30
match:
- label: node-role.kubernetes.io/master
- label: node-role.kubernetes.io/infra
- profile: openshift-node
priority: 40
Starting with OpenShift Container Platform 4.9, all OpenShift TuneD profiles are shipped with
the TuneD package. You can use the oc exec
command to view the contents of these profiles:
$ oc exec $tuned_pod -n openshift-cluster-node-tuning-operator -- find /usr/lib/tuned/openshift{,-control-plane,-node} -name tuned.conf -exec grep -H ^ {} \;
Verify the TuneD profiles that are applied to your cluster node.
$ oc get profile.tuned.openshift.io -n openshift-cluster-node-tuning-operator
NAME TUNED APPLIED DEGRADED AGE
master-0 openshift-control-plane True False 6h33m
master-1 openshift-control-plane True False 6h33m
master-2 openshift-control-plane True False 6h33m
worker-a openshift-node True False 6h28m
worker-b openshift-node True False 6h28m
NAME
: Name of the Profile object. There is one Profile object per node and their names match.
TUNED
: Name of the desired TuneD profile to apply.
APPLIED
: True
if the TuneD daemon applied the desired profile. (True/False/Unknown
).
DEGRADED
: True
if any errors were reported during application of the TuneD profile (True/False/Unknown
).
AGE
: Time elapsed since the creation of Profile object.
The ClusterOperator/node-tuning
object also contains useful information about the Operator and its node agents' health. For example, Operator misconfiguration is reported by ClusterOperator/node-tuning
status messages.
To get status information about the ClusterOperator/node-tuning
object, run the following command:
$ oc get co/node-tuning -n openshift-cluster-node-tuning-operator
NAME VERSION AVAILABLE PROGRESSING DEGRADED SINCE MESSAGE
node-tuning 4.13.1 True False True 60m 1/5 Profiles with bootcmdline conflict
If either the ClusterOperator/node-tuning
or a profile object’s status is DEGRADED
, additional information is provided in the Operator or operand logs.
The custom resource (CR) for the Operator has two major sections. The first section, profile:
, is a list of TuneD profiles and their names. The second, recommend:
, defines the profile selection logic.
Multiple custom tuning specifications can co-exist as multiple CRs in the Operator’s namespace. The existence of new CRs or the deletion of old CRs is detected by the Operator. All existing custom tuning specifications are merged and appropriate objects for the containerized TuneD daemons are updated.
Management state
The Operator Management state is set by adjusting the default Tuned CR. By default, the Operator is in the Managed state and the spec.managementState
field is not present in the default Tuned CR. Valid values for the Operator Management state are as follows:
Managed: the Operator will update its operands as configuration resources are updated
Unmanaged: the Operator will ignore changes to the configuration resources
Removed: the Operator will remove its operands and resources the Operator provisioned
Profile data
The profile:
section lists TuneD profiles and their names.
profile:
- name: tuned_profile_1
data: |
# TuneD profile specification
[main]
summary=Description of tuned_profile_1 profile
[sysctl]
net.ipv4.ip_forward=1
# ... other sysctl's or other TuneD daemon plugins supported by the containerized TuneD
# ...
- name: tuned_profile_n
data: |
# TuneD profile specification
[main]
summary=Description of tuned_profile_n profile
# tuned_profile_n profile settings
Recommended profiles
The profile:
selection logic is defined by the recommend:
section of the CR. The recommend:
section is a list of items to recommend the profiles based on a selection criteria.
recommend:
<recommend-item-1>
# ...
<recommend-item-n>
The individual items of the list:
- machineConfigLabels: (1)
<mcLabels> (2)
match: (3)
<match> (4)
priority: <priority> (5)
profile: <tuned_profile_name> (6)
operand: (7)
debug: <bool> (8)
tunedConfig:
reapply_sysctl: <bool> (9)
1 | Optional. |
2 | A dictionary of key/value MachineConfig labels. The keys must be unique. |
3 | If omitted, profile match is assumed unless a profile with a higher priority matches first or machineConfigLabels is set. |
4 | An optional list. |
5 | Profile ordering priority. Lower numbers mean higher priority (0 is the highest priority). |
6 | A TuneD profile to apply on a match. For example tuned_profile_1 . |
7 | Optional operand configuration. |
8 | Turn debugging on or off for the TuneD daemon. Options are true for on or false for off. The default is false . |
9 | Turn reapply_sysctl functionality on or off for the TuneD daemon. Options are true for on and false for off. |
<match>
is an optional list recursively defined as follows:
- label: <label_name> (1)
value: <label_value> (2)
type: <label_type> (3)
<match> (4)
1 | Node or pod label name. |
2 | Optional node or pod label value. If omitted, the presence of <label_name> is enough to match. |
3 | Optional object type (node or pod ). If omitted, node is assumed. |
4 | An optional <match> list. |
If <match>
is not omitted, all nested <match>
sections must also evaluate to true
. Otherwise, false
is assumed and the profile with the respective <match>
section will not be applied or recommended. Therefore, the nesting (child <match>
sections) works as logical AND operator. Conversely, if any item of the <match>
list matches, the entire <match>
list evaluates to true
. Therefore, the list acts as logical OR operator.
If machineConfigLabels
is defined, machine config pool based matching is turned on for the given recommend:
list item. <mcLabels>
specifies the labels for a machine config. The machine config is created automatically to apply host settings, such as kernel boot parameters, for the profile <tuned_profile_name>
. This involves finding all machine config pools with machine config selector matching <mcLabels>
and setting the profile <tuned_profile_name>
on all nodes that are assigned the found machine config pools. To target nodes that have both master and worker roles, you must use the master role.
The list items match
and machineConfigLabels
are connected by the logical OR operator. The match
item is evaluated first in a short-circuit manner. Therefore, if it evaluates to true
, the machineConfigLabels
item is not considered.
When using machine config pool based matching, it is advised to group nodes with the same hardware configuration into the same machine config pool. Not following this practice might result in TuneD operands calculating conflicting kernel parameters for two or more nodes sharing the same machine config pool. |
- match:
- label: tuned.openshift.io/elasticsearch
match:
- label: node-role.kubernetes.io/master
- label: node-role.kubernetes.io/infra
type: pod
priority: 10
profile: openshift-control-plane-es
- match:
- label: node-role.kubernetes.io/master
- label: node-role.kubernetes.io/infra
priority: 20
profile: openshift-control-plane
- priority: 30
profile: openshift-node
The CR above is translated for the containerized TuneD daemon into its recommend.conf
file based on the profile priorities. The profile with the highest priority (10
) is openshift-control-plane-es
and, therefore, it is considered first. The containerized TuneD daemon running on a given node looks to see if there is a pod running on the same node with the tuned.openshift.io/elasticsearch
label set. If not, the entire <match>
section evaluates as false
. If there is such a pod with the label, in order for the <match>
section to evaluate to true
, the node label also needs to be node-role.kubernetes.io/master
or node-role.kubernetes.io/infra
.
If the labels for the profile with priority 10
matched, openshift-control-plane-es
profile is applied and no other profile is considered. If the node/pod label combination did not match, the second highest priority profile (openshift-control-plane
) is considered. This profile is applied if the containerized TuneD pod runs on a node with labels node-role.kubernetes.io/master
or node-role.kubernetes.io/infra
.
Finally, the profile openshift-node
has the lowest priority of 30
. It lacks the <match>
section and, therefore, will always match. It acts as a profile catch-all to set openshift-node
profile, if no other profile with higher priority matches on a given node.
apiVersion: tuned.openshift.io/v1
kind: Tuned
metadata:
name: openshift-node-custom
namespace: openshift-cluster-node-tuning-operator
spec:
profile:
- data: |
[main]
summary=Custom OpenShift node profile with an additional kernel parameter
include=openshift-node
[bootloader]
cmdline_openshift_node_custom=+skew_tick=1
name: openshift-node-custom
recommend:
- machineConfigLabels:
machineconfiguration.openshift.io/role: "worker-custom"
priority: 20
profile: openshift-node-custom
To minimize node reboots, label the target nodes with a label the machine config pool’s node selector will match, then create the Tuned CR above and finally create the custom machine config pool itself.
Cloud provider-specific TuneD profiles
With this functionality, all Cloud provider-specific nodes can conveniently be assigned a TuneD profile specifically tailored to a given Cloud provider on a OpenShift Container Platform cluster. This can be accomplished without adding additional node labels or grouping nodes into machine config pools.
This functionality takes advantage of spec.providerID
node object values in the form of <cloud-provider>://<cloud-provider-specific-id>
and writes the file /var/lib/tuned/provider
with the value <cloud-provider>
in NTO operand containers. The content of this file is then used by TuneD to load provider-<cloud-provider>
profile if such profile exists.
The openshift
profile that both openshift-control-plane
and openshift-node
profiles inherit settings from is now updated to use this functionality through the use of conditional profile loading. Neither NTO nor TuneD currently include any Cloud provider-specific profiles. However, it is possible to create a custom profile provider-<cloud-provider>
that will be applied to all Cloud provider-specific cluster nodes.
apiVersion: tuned.openshift.io/v1
kind: Tuned
metadata:
name: provider-gce
namespace: openshift-cluster-node-tuning-operator
spec:
profile:
- data: |
[main]
summary=GCE Cloud provider-specific profile
# Your tuning for GCE Cloud provider goes here.
name: provider-gce
Due to profile inheritance, any setting specified in the |
Using TuneD profiles from the default CR
The following CR applies custom node-level tuning for
OpenShift Container Platform nodes with label
tuned.openshift.io/ingress-node-label
set to any value.
apiVersion: tuned.openshift.io/v1
kind: Tuned
metadata:
name: ingress
namespace: openshift-cluster-node-tuning-operator
spec:
profile:
- data: |
[main]
summary=A custom OpenShift ingress profile
include=openshift-control-plane
[sysctl]
net.ipv4.ip_local_port_range="1024 65535"
net.ipv4.tcp_tw_reuse=1
name: openshift-ingress
recommend:
- match:
- label: tuned.openshift.io/ingress-node-label
priority: 10
profile: openshift-ingress
Custom profile writers are strongly encouraged to include the default TuneD
daemon profiles shipped within the default Tuned CR. The example above uses the
default |
Using built-in TuneD profiles
Given the successful rollout of the NTO-managed daemon set, the TuneD operands all manage the same version of the TuneD daemon. To list the built-in TuneD profiles supported by the daemon, query any TuneD pod in the following way:
$ oc exec $tuned_pod -n openshift-cluster-node-tuning-operator -- find /usr/lib/tuned/ -name tuned.conf -printf '%h\n' | sed 's|^.*/||'
You can use the profile names retrieved by this in your custom tuning specification.
apiVersion: tuned.openshift.io/v1
kind: Tuned
metadata:
name: openshift-node-hpc-compute
namespace: openshift-cluster-node-tuning-operator
spec:
profile:
- data: |
[main]
summary=Custom OpenShift node profile for HPC compute workloads
include=openshift-node,hpc-compute
name: openshift-node-hpc-compute
recommend:
- match:
- label: tuned.openshift.io/openshift-node-hpc-compute
priority: 20
profile: openshift-node-hpc-compute
In addition to the built-in hpc-compute
profile, the example above includes
the openshift-node
TuneD daemon profile shipped within the default
Tuned CR to use OpenShift-specific tuning for compute nodes.
Overriding host-level sysctls
Various kernel parameters can be changed at runtime by using /run/sysctl.d/
, /etc/sysctl.d/
, and /etc/sysctl.conf
host configuration files. OpenShift Container Platform adds several host configuration files which set kernel parameters at runtime; for example, net.ipv[4-6].
, fs.inotify.
, and vm.max_map_count
. These runtime parameters provide basic functional tuning for the system prior to the kubelet and the Operator start.
The Operator does not override these settings unless the reapply_sysctl
option is set to false
. Setting this option to false
results in TuneD
not applying the settings from the host configuration files after it applies its custom profile.
apiVersion: tuned.openshift.io/v1
kind: Tuned
metadata:
name: openshift-no-reapply-sysctl
namespace: openshift-cluster-node-tuning-operator
spec:
profile:
- data: |
[main]
summary=Custom OpenShift profile
include=openshift-node
[sysctl]
vm.max_map_count=>524288
name: openshift-no-reapply-sysctl
recommend:
- match:
- label: tuned.openshift.io/openshift-no-reapply-sysctl
priority: 15
profile: openshift-no-reapply-sysctl
operand:
tunedConfig:
reapply_sysctl: false
Excluding the [main]
section, the following TuneD plugins are supported when
using custom profiles defined in the profile:
section of the Tuned CR:
audio
cpu
disk
eeepc_she
modules
mounts
net
scheduler
scsi_host
selinux
sysctl
sysfs
usb
video
vm
bootloader
There is some dynamic tuning functionality provided by some of these plugins that is not supported. The following TuneD plugins are currently not supported:
script
systemd
The TuneD bootloader plugin only supports Red Hat Enterprise Linux CoreOS (RHCOS) worker nodes. |
Hosted control planes is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process. For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope. |
To set node-level tuning on the nodes in your hosted cluster, you can use the Node Tuning Operator. In hosted control planes, you can configure node tuning by creating config maps that contain Tuned
objects and referencing those config maps in your node pools.
Create a config map that contains a valid tuned manifest, and reference the manifest in a node pool. In the following example, a Tuned
manifest defines a profile that sets vm.dirty_ratio
to 55 on nodes that contain the tuned-1-node-label
node label with any value. Save the following ConfigMap
manifest in a file named tuned-1.yaml
:
apiVersion: v1
kind: ConfigMap
metadata:
name: tuned-1
namespace: clusters
data:
tuning: |
apiVersion: tuned.openshift.io/v1
kind: Tuned
metadata:
name: tuned-1
namespace: openshift-cluster-node-tuning-operator
spec:
profile:
- data: |
[main]
summary=Custom OpenShift profile
include=openshift-node
[sysctl]
vm.dirty_ratio="55"
name: tuned-1-profile
recommend:
- priority: 20
profile: tuned-1-profile
If you do not add any labels to an entry in the |
Create the ConfigMap
object in the management cluster:
$ oc --kubeconfig="$MGMT_KUBECONFIG" create -f tuned-1.yaml
Reference the ConfigMap
object in the spec.tuningConfig
field of the node pool, either by editing a node pool or creating one. In this example, assume that you have only one NodePool
, named nodepool-1
, which contains 2 nodes.
apiVersion: hypershift.openshift.io/v1alpha1
kind: NodePool
metadata:
...
name: nodepool-1
namespace: clusters
...
spec:
...
tuningConfig:
- name: tuned-1
status:
...
You can reference the same config map in multiple node pools. In hosted control planes, the Node Tuning Operator appends a hash of the node pool name and namespace to the name of the Tuned CRs to distinguish them. Outside of this case, do not create multiple TuneD profiles of the same name in different Tuned CRs for the same hosted cluster. |
Now that you have created the ConfigMap
object that contains a Tuned
manifest and referenced it in a NodePool
, the Node Tuning Operator syncs the Tuned
objects into the hosted cluster. You can verify which Tuned
objects are defined and which TuneD profiles are applied to each node.
List the Tuned
objects in the hosted cluster:
$ oc --kubeconfig="$HC_KUBECONFIG" get tuned.tuned.openshift.io -n openshift-cluster-node-tuning-operator
NAME AGE
default 7m36s
rendered 7m36s
tuned-1 65s
List the Profile
objects in the hosted cluster:
$ oc --kubeconfig="$HC_KUBECONFIG" get profile.tuned.openshift.io -n openshift-cluster-node-tuning-operator
NAME TUNED APPLIED DEGRADED AGE
nodepool-1-worker-1 tuned-1-profile True False 7m43s
nodepool-1-worker-2 tuned-1-profile True False 7m14s
If no custom profiles are created, the |
To confirm that the tuning was applied correctly, start a debug shell on a node and check the sysctl values:
$ oc --kubeconfig="$HC_KUBECONFIG" debug node/nodepool-1-worker-1 -- chroot /host sysctl vm.dirty_ratio
vm.dirty_ratio = 55
Hosted control planes is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process. For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope. |
For more advanced tuning in hosted control planes, which requires setting kernel boot parameters, you can also use the Node Tuning Operator. The following example shows how you can create a node pool with huge pages reserved.
Create a ConfigMap
object that contains a Tuned
object manifest for creating 10 huge pages that are 2 MB in size. Save this ConfigMap
manifest in a file named tuned-hugepages.yaml
:
apiVersion: v1
kind: ConfigMap
metadata:
name: tuned-hugepages
namespace: clusters
data:
tuning: |
apiVersion: tuned.openshift.io/v1
kind: Tuned
metadata:
name: hugepages
namespace: openshift-cluster-node-tuning-operator
spec:
profile:
- data: |
[main]
summary=Boot time configuration for hugepages
include=openshift-node
[bootloader]
cmdline_openshift_node_hugepages=hugepagesz=2M hugepages=50
name: openshift-node-hugepages
recommend:
- priority: 20
profile: openshift-node-hugepages
The |
Create the ConfigMap
object in the management cluster:
$ oc --kubeconfig="<management_cluster_kubeconfig>" create -f tuned-hugepages.yaml (1)
1 | Replace <management_cluster_kubeconfig> with the name of your management cluster kubeconfig file. |
Create a NodePool
manifest YAML file, customize the upgrade type of the NodePool
, and reference the ConfigMap
object that you created in the spec.tuningConfig
section. Create the NodePool
manifest and save it in a file named hugepages-nodepool.yaml
by using the hypershift
CLI:
<<<<<<< HEAD
NODEPOOL_NAME=hugepages-example
INSTANCE_TYPE=m5.2xlarge
NODEPOOL_REPLICAS=2
hypershift create nodepool aws \
--cluster-name $CLUSTER_NAME \
--name $NODEPOOL_NAME \
--node-count $NODEPOOL_REPLICAS \
--instance-type $INSTANCE_TYPE \
--render > hugepages-nodepool.yaml
=======
$ hcp create nodepool aws \
--cluster-name <hosted_cluster_name> \(1)
--name <nodepool_name> \(2)
--node-count <nodepool_replicas> \(3)
--instance-type <instance_type> \(4)
--render > hugepages-nodepool.yaml
>>>>>>> e990587823 (OSDOCS#12123: Describe the --render usage)
1 | Replace <hosted_cluster_name> with the name of your hosted cluster. |
2 | Replace <nodepool_name> with the name of your node pool. |
3 | Replace <nodepool_replicas> with the number of your node pool replicas, for example, 2 . |
4 | Replace <instance_type> with the instance type, for example, m5.2xlarge . |
The |
In the hugepages-nodepool.yaml
file, set .spec.management.upgradeType
to InPlace
, and set .spec.tuningConfig
to reference the tuned-hugepages
ConfigMap
object that you created.
apiVersion: hypershift.openshift.io/v1alpha1
kind: NodePool
metadata:
name: hugepages-nodepool
namespace: clusters
...
spec:
management:
...
upgradeType: InPlace
...
tuningConfig:
- name: tuned-hugepages
To avoid the unnecessary re-creation of nodes when you apply the new |
Create the NodePool
in the management cluster:
$ oc --kubeconfig="<management_cluster_kubeconfig>" create -f hugepages-nodepool.yaml
After the nodes are available, the containerized TuneD daemon calculates the required kernel boot parameters based on the applied TuneD profile. After the nodes are ready and reboot once to apply the generated MachineConfig
object, you can verify that the TuneD profile is applied and that the kernel boot parameters are set.
List the Tuned
objects in the hosted cluster:
$ oc --kubeconfig="<hosted_cluster_kubeconfig>" get tuned.tuned.openshift.io -n openshift-cluster-node-tuning-operator
NAME AGE
default 123m
hugepages-8dfb1fed 1m23s
rendered 123m
List the Profile
objects in the hosted cluster:
$ oc --kubeconfig="<hosted_cluster_kubeconfig>" get profile.tuned.openshift.io -n openshift-cluster-node-tuning-operator
NAME TUNED APPLIED DEGRADED AGE
nodepool-1-worker-1 openshift-node True False 132m
nodepool-1-worker-2 openshift-node True False 131m
hugepages-nodepool-worker-1 openshift-node-hugepages True False 4m8s
hugepages-nodepool-worker-2 openshift-node-hugepages True False 3m57s
Both of the worker nodes in the new NodePool
have the openshift-node-hugepages
profile applied.
To confirm that the tuning was applied correctly, start a debug shell on a node and check /proc/cmdline
.
$ oc --kubeconfig="<hosted_cluster_kubeconfig>" debug node/nodepool-1-worker-1 -- chroot /host cat /proc/cmdline
BOOT_IMAGE=(hd0,gpt3)/ostree/rhcos-... hugepagesz=2M hugepages=50
For more information about hosted control planes, see Hosted control planes (Technology Preview).