Chapter 7. Using the 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. 7.1. About the Node Tuning Operator 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. The Node Tuning Operator is part of a standard OpenShift Container Platform installation in version 4.1 and later. Note 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. 7.2. Accessing an example Node Tuning Operator specification Use this process to access an example Node Tuning Operator specification. Procedure 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. Warning 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. 7.3. Default profiles set on a cluster 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-USD{f:exec:cat:/var/lib/ocp-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: USD oc exec USDtuned_pod -n openshift-cluster-node-tuning-operator -- find /usr/lib/tuned/openshift{,-control-plane,-node} -name tuned.conf -exec grep -H ^ {} \; 7.4. Verifying that the TuneD profiles are applied Verify the TuneD profiles that are applied to your cluster node. USD oc get profile.tuned.openshift.io -n openshift-cluster-node-tuning-operator Example output 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: USD oc get co/node-tuning -n openshift-cluster-node-tuning-operator Example output NAME VERSION AVAILABLE PROGRESSING DEGRADED SINCE MESSAGE node-tuning 4.16.1 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. 7.5. Custom tuning specification 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. Important 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. Example: Node or pod label based matching - 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. Example: Machine config pool based matching 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/ocp-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. Example GCE Cloud provider profile 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 Note Due to profile inheritance, any setting specified in the provider-<cloud-provider> profile will be overwritten by the openshift profile and its child profiles. 7.6. Custom tuning examples 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. Example: custom tuning using the openshift-control-plane TuneD profile 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 Important 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 openshift-control-plane profile to accomplish this. 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: USD oc exec USDtuned_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. Example: using built-in hpc-compute TuneD profile 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. Example: overriding host-level sysctls 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 7.7. Supported TuneD daemon plugins 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 Note The TuneD bootloader plugin only supports Red Hat Enterprise Linux CoreOS (RHCOS) worker nodes. Additional resources Available TuneD Plugins Getting Started with TuneD 7.8. Configuring node tuning in a hosted cluster 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. Procedure 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 Note If you do not add any labels to an entry in the spec.recommend section of the Tuned spec, node-pool-based matching is assumed, so the highest priority profile in the spec.recommend section is applied to nodes in the pool. Although you can achieve more fine-grained node-label-based matching by setting a label value in the Tuned .spec.recommend.match section, node labels will not persist during an upgrade unless you set the .spec.management.upgradeType value of the node pool to InPlace . Create the ConfigMap object in the management cluster: USD oc --kubeconfig="USDMGMT_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: ... Note 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. Verification 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: USD oc --kubeconfig="USDHC_KUBECONFIG" get tuned.tuned.openshift.io -n openshift-cluster-node-tuning-operator Example output NAME AGE default 7m36s rendered 7m36s tuned-1 65s List the Profile objects in the hosted cluster: USD oc --kubeconfig="USDHC_KUBECONFIG" get profile.tuned.openshift.io -n openshift-cluster-node-tuning-operator Example output 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 Note If no custom profiles are created, the openshift-node profile is applied by default. To confirm that the tuning was applied correctly, start a debug shell on a node and check the sysctl values: USD oc --kubeconfig="USDHC_KUBECONFIG" debug node/nodepool-1-worker-1 -- chroot /host sysctl vm.dirty_ratio Example output vm.dirty_ratio = 55 7.9. Advanced node tuning for hosted clusters by setting kernel boot parameters 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. Procedure 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 Note The .spec.recommend.match field is intentionally left blank. In this case, this Tuned object is applied to all nodes in the node pool where this ConfigMap object is referenced. Group nodes with the same hardware configuration into the same node pool. Otherwise, TuneD operands can calculate conflicting kernel parameters for two or more nodes that share the same node pool. Create the ConfigMap object in the management cluster: USD 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 hcp CLI: USD 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 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 . Note The --render flag in the hcp create command does not render the secrets. To render the secrets, you must use both the --render and the --render-sensitive flags in the hcp create command. 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 Note To avoid the unnecessary re-creation of nodes when you apply the new MachineConfig objects, set .spec.management.upgradeType to InPlace . If you use the Replace upgrade type, nodes are fully deleted and new nodes can replace them when you apply the new kernel boot parameters that the TuneD operand calculated. Create the NodePool in the management cluster: USD oc --kubeconfig="<management_cluster_kubeconfig>" create -f hugepages-nodepool.yaml Verification 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: USD oc --kubeconfig="<hosted_cluster_kubeconfig>" get tuned.tuned.openshift.io -n openshift-cluster-node-tuning-operator Example output NAME AGE default 123m hugepages-8dfb1fed 1m23s rendered 123m List the Profile objects in the hosted cluster: USD oc --kubeconfig="<hosted_cluster_kubeconfig>" get profile.tuned.openshift.io -n openshift-cluster-node-tuning-operator Example output 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 . USD oc --kubeconfig="<hosted_cluster_kubeconfig>" debug node/nodepool-1-worker-1 -- chroot /host cat /proc/cmdline Example output BOOT_IMAGE=(hd0,gpt3)/ostree/rhcos-... hugepagesz=2M hugepages=50 Additional resources For more information about hosted control planes, see Hosted control planes .

Commands:
get tuned.tuned.openshift.io/default -o yaml -n openshift-cluster-node-tuning-operator
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-USD{f:exec:cat:/var/lib/ocp-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
oc exec USDtuned_pod -n openshift-cluster-node-tuning-operator -- find /usr/lib/tuned/openshift{,-control-plane,-node} -name tuned.conf -exec grep -H ^ {} \;
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
oc get co/node-tuning -n openshift-cluster-node-tuning-operator
NAME VERSION AVAILABLE PROGRESSING DEGRADED SINCE MESSAGE node-tuning 4.16.1 True False True 60m 1/5 Profiles with bootcmdline conflict
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
recommend: <recommend-item-1> <recommend-item-n>
- 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
- label: <label_name> 1 value: <label_value> 2 type: <label_type> 3 <match> 4
- 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
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
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
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
oc exec USDtuned_pod -n openshift-cluster-node-tuning-operator -- find /usr/lib/tuned/ -name tuned.conf -printf '%h\n' | sed 's|^.*/||'
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
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
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
oc --kubeconfig="USDMGMT_KUBECONFIG" create -f tuned-1.yaml
apiVersion: hypershift.openshift.io/v1alpha1 kind: NodePool metadata: name: nodepool-1 namespace: clusters spec: tuningConfig: - name: tuned-1 status:
oc --kubeconfig="USDHC_KUBECONFIG" get tuned.tuned.openshift.io -n openshift-cluster-node-tuning-operator
NAME AGE default 7m36s rendered 7m36s tuned-1 65s
oc --kubeconfig="USDHC_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
oc --kubeconfig="USDHC_KUBECONFIG" debug node/nodepool-1-worker-1 -- chroot /host sysctl vm.dirty_ratio
vm.dirty_ratio = 55
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
oc --kubeconfig="<management_cluster_kubeconfig>" create -f tuned-hugepages.yaml 1
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
apiVersion: hypershift.openshift.io/v1alpha1 kind: NodePool metadata: name: hugepages-nodepool namespace: clusters spec: management: upgradeType: InPlace tuningConfig: - name: tuned-hugepages
oc --kubeconfig="<management_cluster_kubeconfig>" create -f hugepages-nodepool.yaml
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
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
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