Chapter 4. Using the Node Tuning Operator

The Node Tuning Operator helps you manage node-level tuning by orchestrating the TuneD daemon. 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 is part of a standard OpenShift Container Platform installation in version 4.1 and later.

Use this process to access an example Node Tuning Operator specification.

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.

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:
  - name: "openshift"
    data: |
      [main]
      summary=Optimize systems running OpenShift (parent profile)
      include=${f:virt_check:virtual-guest:throughput-performance}

      [selinux]
      avc_cache_threshold=8192

      [net]
      nf_conntrack_hashsize=131072

      [sysctl]
      net.ipv4.ip_forward=1
      kernel.pid_max=>4194304
      net.netfilter.nf_conntrack_max=1048576
      net.ipv4.conf.all.arp_announce=2
      net.ipv4.neigh.default.gc_thresh1=8192
      net.ipv4.neigh.default.gc_thresh2=32768
      net.ipv4.neigh.default.gc_thresh3=65536
      net.ipv6.neigh.default.gc_thresh1=8192
      net.ipv6.neigh.default.gc_thresh2=32768
      net.ipv6.neigh.default.gc_thresh3=65536
      vm.max_map_count=262144

      [sysfs]
      /sys/module/nvme_core/parameters/io_timeout=4294967295
      /sys/module/nvme_core/parameters/max_retries=10

  - name: "openshift-control-plane"
    data: |
      [main]
      summary=Optimize systems running OpenShift control plane
      include=openshift

      [sysctl]
      # ktune sysctl settings, maximizing i/o throughput
      #
      # Minimal preemption granularity for CPU-bound tasks:
      # (default: 1 msec#  (1 + ilog(ncpus)), units: nanoseconds)
      kernel.sched_min_granularity_ns=10000000
      # The total time the scheduler will consider a migrated process
      # "cache hot" and thus less likely to be re-migrated
      # (system default is 500000, i.e. 0.5 ms)
      kernel.sched_migration_cost_ns=5000000
      # SCHED_OTHER wake-up granularity.
      #
      # Preemption granularity when tasks wake up.  Lower the value to
      # improve wake-up latency and throughput for latency critical tasks.
      kernel.sched_wakeup_granularity_ns=4000000

  - name: "openshift-node"
    data: |
      [main]
      summary=Optimize systems running OpenShift nodes
      include=openshift

      [sysctl]
      net.ipv4.tcp_fastopen=3
      fs.inotify.max_user_watches=65536
      fs.inotify.max_user_instances=8192

  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

Verify the TuneD profiles that are applied to your cluster node.

$ oc get profile -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

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:

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

<match> is an optional list recursively defined as follows:

- label: <label_name> 1
  value: <label_value> 2
  type: <label_type> 3
    <match> 4

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.

- 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.

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

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.

Excluding the [main] section, the following TuneD plugins are supported when using custom profiles defined in the profile: section of the Tuned CR:

There is some dynamic tuning functionality provided by some of these plugins that is not supported. The following TuneD plugins are currently not supported:

See Available TuneD Plugins and Getting Started with TuneD for more information.