Red Hat Summit Red Hat SummitSupportConsoleDevelopersStart a trialContact

Chapter 12. Scheduling NUMA-aware workloads

Learn about NUMA-aware scheduling and how you can use it to deploy high performance workloads in an OpenShift Container Platform cluster.

The NUMA Resources Operator allows you to schedule high-performance workloads in the same NUMA zone. It deploys a node resources exporting agent that reports on available cluster node NUMA resources, and a secondary scheduler that manages the workloads.

12.1. About NUMA
Copy link

Non-uniform memory access (NUMA) architecture is a multiprocessor architecture model where CPUs do not access all memory in all locations at the same speed. Instead, CPUs can gain faster access to memory that is in closer proximity to them, or local to them, but slower access to memory that is further away.

A CPU with multiple memory controllers can use any available memory across CPU complexes, regardless of where the memory is located. However, this increased flexibility comes at the expense of performance.

NUMA resource topology refers to the physical locations of CPUs, memory, and PCI devices relative to each other in a NUMA zone. In a NUMA architecture, a NUMA zone is a group of CPUs that has its own processors and memory. Colocated resources are said to be in the same NUMA zone, and CPUs in a zone have faster access to the same local memory than CPUs outside of that zone. A CPU processing a workload using memory that is outside its NUMA zone is slower than a workload processed in a single NUMA zone. For I/O-constrained workloads, the network interface on a distant NUMA zone slows down how quickly information can reach the application.

Applications can achieve better performance by containing data and processing within the same NUMA zone. For high-performance workloads and applications, such as telecommunications workloads, the cluster must process pod workloads in a single NUMA zone so that the workload can operate to specification.

12.2. About NUMA-aware scheduling
Copy link

NUMA-aware scheduling aligns the requested cluster compute resources (CPUs, memory, devices) in the same NUMA zone to process latency-sensitive or high-performance workloads efficiently. NUMA-aware scheduling also improves pod density per compute node for greater resource efficiency.

12.2.1. Integration with Node Tuning Operator
Copy link

By integrating the Node Tuning Operator’s performance profile with NUMA-aware scheduling, you can further configure CPU affinity to optimize performance for latency-sensitive workloads.

12.2.2. Default scheduling logic
Copy link

The default OpenShift Container Platform pod scheduler scheduling logic considers the available resources of the entire compute node, not individual NUMA zones. If the most restrictive resource alignment is requested in the kubelet topology manager, error conditions can occur when admitting the pod to a node. Conversely, if the most restrictive resource alignment is not requested, the pod can be admitted to the node without proper resource alignment, leading to worse or unpredictable performance. For example, runaway pod creation with Topology Affinity Error statuses can occur when the pod scheduler makes suboptimal scheduling decisions for guaranteed pod workloads without knowing if the pod’s requested resources are available. Scheduling mismatch decisions can cause indefinite pod startup delays. Also, depending on the cluster state and resource allocation, poor pod scheduling decisions can cause extra load on the cluster because of failed startup attempts.

12.2.3. NUMA-aware pod scheduling diagram
Copy link

The NUMA Resources Operator deploys a custom NUMA resources secondary scheduler and other resources to mitigate against the shortcomings of the default OpenShift Container Platform pod scheduler. The following diagram provides a high-level overview of NUMA-aware pod scheduling.

Figure 12.1. NUMA-aware scheduling overview

Diagram of NUMA-aware scheduling that shows how the various components interact with each other in the cluster
View larger image
Diagram of NUMA-aware scheduling that shows how the various components interact with each other in the cluster
NodeResourceTopology API
The NodeResourceTopology API describes the available NUMA zone resources in each compute node.
NUMA-aware scheduler
The NUMA-aware secondary scheduler receives information about the available NUMA zones from the NodeResourceTopology API and schedules high-performance workloads on a node where it can be optimally processed.
Node topology exporter
The node topology exporter exposes the available NUMA zone resources for each compute node to the NodeResourceTopology API. The node topology exporter daemon tracks the resource allocation from the kubelet by using the PodResources API.
PodResources API

The PodResources API is local to each node and exposes the resource topology and available resources to the kubelet.

Note

The List endpoint of the PodResources API exposes exclusive CPUs allocated to a particular container. The API does not expose CPUs that belong to a shared pool.

The GetAllocatableResources endpoint exposes allocatable resources available on a node.

12.3. NUMA resource scheduling strategies
Copy link

When scheduling high-performance workloads, the secondary scheduler can employ different strategies to determine which NUMA node within a chosen worker node will handle the workload. The supported strategies in OpenShift Container Platform include LeastAllocated, MostAllocated, and BalancedAllocation. Understanding these strategies helps optimize workload placement for performance and resource utilization.

When a high-performance workload is scheduled in a NUMA-aware cluster, the following steps occur:

  1. The scheduler first selects a suitable worker node based on cluster-wide criteria. For example taints, labels, or resource availability.
  2. After a worker node is selected, the scheduler evaluates its NUMA nodes and applies a scoring strategy to decide which NUMA node will handle the workload.
  3. After a workload is scheduled, the selected NUMA node’s resources are updated to reflect the allocation.

The default strategy applied is the LeastAllocated strategy. This assigns workloads to the NUMA node with the most available resources that is the least utilized NUMA node. The goal of this strategy is to spread workloads across NUMA nodes to reduce contention and avoid hotspots.

The following table summarizes the different strategies and their outcomes:

Scoring strategy summary

Expand
Table 12.1. Scoring strategy summary
StrategyDescriptionOutcome

LeastAllocated

Favors NUMA nodes with the most available resources.

Spreads workloads to reduce contention and ensure headroom for high-priority tasks.

MostAllocated

Favors NUMA nodes with the least available resources.

Consolidates workloads on fewer NUMA nodes, freeing others for energy efficiency.

BalancedAllocation

Favors NUMA nodes with balanced CPU and memory usage.

Ensures even resource utilization, preventing skewed usage patterns.

LeastAllocated strategy example

The LeastAllocated is the default strategy. This strategy assigns workloads to the NUMA node with the most available resources, minimizing resource contention and spreading workloads across NUMA nodes. This reduces hotspots and ensures sufficient headroom for high-priority tasks. Assume a worker node has two NUMA nodes, and the workload requires 4 vCPUs and 8 GB of memory:

Expand
Table 12.2. Example initial NUMA nodes state
NUMA nodeTotal CPUsUsed CPUsTotal memory (GB)Used memory (GB)Available resources

NUMA 1

16

12

64

56

4 CPUs, 8 GB memory

NUMA 2

16

6

64

24

10 CPUs, 40 GB memory

Because NUMA 2 has more available resources compared to NUMA 1, the workload is assigned to NUMA 2.

MostAllocated strategy example

The MostAllocated strategy consolidates workloads by assigning them to the NUMA node with the least available resources, which is the most utilized NUMA node. This approach helps free other NUMA nodes for energy efficiency or critical workloads requiring full isolation. This example uses the "Example initial NUMA nodes state" values listed in the LeastAllocated section.

The workload again requires 4 vCPUs and 8 GB memory. NUMA 1 has fewer available resources compared to NUMA 2, so the scheduler assigns the workload to NUMA 1, further utilizing its resources while leaving NUMA 2 idle or minimally loaded.

BalancedAllocation strategy example

The BalancedAllocation strategy assigns workloads to the NUMA node with the most balanced resource utilization across CPU and memory. The goal is to prevent imbalanced usage, such as high CPU utilization with underutilized memory. Assume a worker node has the following NUMA node states:

Expand
Table 12.3. Example NUMA nodes initial state for BalancedAllocation
NUMA nodeCPU usageMemory usageBalancedAllocation score

NUMA 1

60%

55%

High (more balanced)

NUMA 2

80%

20%

Low (less balanced)

NUMA 1 has a more balanced CPU and memory utilization compared to NUMA 2 and therefore, with the BalancedAllocation strategy in place, the workload is assigned to NUMA 1.

12.4. Installing the NUMA Resources Operator
Copy link

NUMA Resources Operator deploys resources that allow you to schedule NUMA-aware workloads and deployments. You can install the NUMA Resources Operator using the OpenShift Container Platform CLI or the web console.

As a cluster administrator, you can install the Operator using the CLI.

Prerequisites

  • Install the OpenShift CLI (oc).
  • Log in as a user with cluster-admin privileges.

Procedure

  1. Create a namespace for the NUMA Resources Operator:

    1. Save the following YAML in the nro-namespace.yaml file: 

      apiVersion: v1
kind: Namespace
metadata:
  name: openshift-numaresources
      Copy to Clipboard Toggle word wrap

    2. Create the Namespace CR by running the following command: 

      $ oc create -f nro-namespace.yaml
      Copy to Clipboard Toggle word wrap

  2. Create the Operator group for the NUMA Resources Operator:

    1. Save the following YAML in the nro-operatorgroup.yaml file: 

      apiVersion: operators.coreos.com/v1
kind: OperatorGroup
metadata:
  name: numaresources-operator
  namespace: openshift-numaresources
spec:
  targetNamespaces:
  - openshift-numaresources
      Copy to Clipboard Toggle word wrap

    2. Create the OperatorGroup CR by running the following command: 

      $ oc create -f nro-operatorgroup.yaml
      Copy to Clipboard Toggle word wrap

  3. Create the subscription for the NUMA Resources Operator:

    1. Save the following YAML in the nro-sub.yaml file: 

      apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: numaresources-operator
  namespace: openshift-numaresources
spec:
  channel: "4.18"
  name: numaresources-operator
  source: redhat-operators
  sourceNamespace: openshift-marketplace
      Copy to Clipboard Toggle word wrap

    2. Create the Subscription CR by running the following command: 

      $ oc create -f nro-sub.yaml
      Copy to Clipboard Toggle word wrap

Verification

  1. Verify that the installation succeeded by inspecting the CSV resource in the openshift-numaresources namespace. Run the following command: 

    $ oc get csv -n openshift-numaresources
    Copy to Clipboard Toggle word wrap

    Example output

    NAME                             DISPLAY                  VERSION   REPLACES   PHASE
numaresources-operator.v4.18.2   numaresources-operator   4.18.2               Succeeded
    Copy to Clipboard Toggle word wrap

As a cluster administrator, you can install the NUMA Resources Operator using the web console.

Procedure

  1. Create a namespace for the NUMA Resources Operator:

    1. In the OpenShift Container Platform web console, click Administration Namespaces.
    2. Click Create Namespace, enter openshift-numaresources in the Name field, and then click Create.

  2. Install the NUMA Resources Operator:

    1. In the OpenShift Container Platform web console, click Operators OperatorHub.
    2. Choose numaresources-operator from the list of available Operators, and then click Install.
    3. In the Installed Namespaces field, select the openshift-numaresources namespace, and then click Install.

  3. Optional: Verify that the NUMA Resources Operator installed successfully:

    1. Switch to the Operators Installed Operators page.

    2. Ensure that NUMA Resources Operator is listed in the openshift-numaresources namespace with a Status of InstallSucceeded.

      Note

      During installation an Operator might display a Failed status. If the installation later succeeds with an InstallSucceeded message, you can ignore the Failed message.

      If the Operator does not appear as installed, to troubleshoot further:

      • Go to the Operators Installed Operators page and inspect the Operator Subscriptions and Install Plans tabs for any failure or errors under Status.
      • Go to the Workloads Pods page and check the logs for pods in the default project.

12.5. Scheduling NUMA-aware workloads
Copy link

Clusters running latency-sensitive workloads typically feature performance profiles that help to minimize workload latency and optimize performance. The NUMA-aware scheduler deploys workloads based on available node NUMA resources and with respect to any performance profile settings applied to the node. The combination of NUMA-aware deployments, and the performance profile of the workload, ensures that workloads are scheduled in a way that maximizes performance.

For the NUMA Resources Operator to be fully operational, you must deploy the NUMAResourcesOperator custom resource and the NUMA-aware secondary pod scheduler.

When you have installed the NUMA Resources Operator, then create the NUMAResourcesOperator custom resource (CR) that instructs the NUMA Resources Operator to install all the cluster infrastructure needed to support the NUMA-aware scheduler, including daemon sets and APIs.

Prerequisites

  • Install the OpenShift CLI (oc).
  • Log in as a user with cluster-admin privileges.
  • Install the NUMA Resources Operator.

Procedure

  1. Create the NUMAResourcesOperator custom resource:

    1. Save the following minimal required YAML file example as nrop.yaml: 

      apiVersion: nodetopology.openshift.io/v1
kind: NUMAResourcesOperator
metadata:
  name: numaresourcesoperator
spec:
  nodeGroups:
  - machineConfigPoolSelector:
      matchLabels:
        pools.operator.machineconfiguration.openshift.io/worker: ""
      1
      Copy to Clipboard Toggle word wrap
      1
      This must match the MachineConfigPool resource that you want to configure the NUMA Resources Operator on. For example, you might have created a MachineConfigPool resource named worker-cnf that designates a set of nodes expected to run telecommunications workloads. Each NodeGroup must match exactly one MachineConfigPool. Configurations where NodeGroup matches more than one MachineConfigPool are not supported.

    2. Create the NUMAResourcesOperator CR by running the following command: 

      $ oc create -f nrop.yaml
      Copy to Clipboard Toggle word wrap

  2. Optional: To enable NUMA-aware scheduling for multiple machine config pools (MCPs), define a separate NodeGroup for each pool. For example, define three NodeGroups for worker-cnf, worker-ht, and worker-other, in the NUMAResourcesOperator CR as shown in the following example:

    Example YAML definition for a NUMAResourcesOperator CR with multiple NodeGroups

    apiVersion: nodetopology.openshift.io/v1
kind: NUMAResourcesOperator
metadata:
  name: numaresourcesoperator
spec:
  logLevel: Normal
  nodeGroups:
    - machineConfigPoolSelector:
        matchLabels:
          machineconfiguration.openshift.io/role: worker-ht
    - machineConfigPoolSelector:
        matchLabels:
          machineconfiguration.openshift.io/role: worker-cnf
    - machineConfigPoolSelector:
        matchLabels:
          machineconfiguration.openshift.io/role: worker-other
    Copy to Clipboard Toggle word wrap

Verification

  1. Verify that the NUMA Resources Operator deployed successfully by running the following command: 

    $ oc get numaresourcesoperators.nodetopology.openshift.io
    Copy to Clipboard Toggle word wrap

    Example output

    NAME                    AGE
numaresourcesoperator   27s
    Copy to Clipboard Toggle word wrap

  2. After a few minutes, run the following command to verify that the required resources deployed successfully: 

    $ oc get all -n openshift-numaresources
    Copy to Clipboard Toggle word wrap

    Example output

    NAME                                                    READY   STATUS    RESTARTS   AGE
pod/numaresources-controller-manager-7d9d84c58d-qk2mr   1/1     Running   0          12m
pod/numaresourcesoperator-worker-7d96r                  2/2     Running   0          97s
pod/numaresourcesoperator-worker-crsht                  2/2     Running   0          97s
pod/numaresourcesoperator-worker-jp9mw                  2/2     Running   0          97s
    Copy to Clipboard Toggle word wrap

After you install the NUMA Resources Operator, follow this procedure to deploy the NUMA-aware secondary pod scheduler.

Procedure

  1. Create the NUMAResourcesScheduler custom resource that deploys the NUMA-aware custom pod scheduler:

    1. Save the following minimal required YAML in the nro-scheduler.yaml file: 

      apiVersion: nodetopology.openshift.io/v1
kind: NUMAResourcesScheduler
metadata:
  name: numaresourcesscheduler
spec:
  imageSpec: "registry.redhat.io/openshift4/noderesourcetopology-scheduler-rhel9:v4.18"
      1
      Copy to Clipboard Toggle word wrap
      1
      In a disconnected environment, make sure to configure the resolution of this image by either:
      • Creating an ImageTagMirrorSet custom resource (CR). For more information, see "Configuring image registry repository mirroring" in the "Additional resources" section.
      • Setting the URL to the disconnected registry.

    2. Create the NUMAResourcesScheduler CR by running the following command: 

      $ oc create -f nro-scheduler.yaml
      Copy to Clipboard Toggle word wrap

  2. After a few seconds, run the following command to confirm the successful deployment of the required resources: 

    $ oc get all -n openshift-numaresources
    Copy to Clipboard Toggle word wrap

    Example output

    NAME                                                    READY   STATUS    RESTARTS   AGE
pod/numaresources-controller-manager-7d9d84c58d-qk2mr   1/1     Running   0          12m
pod/numaresourcesoperator-worker-7d96r                  2/2     Running   0          97s
pod/numaresourcesoperator-worker-crsht                  2/2     Running   0          97s
pod/numaresourcesoperator-worker-jp9mw                  2/2     Running   0          97s
pod/secondary-scheduler-847cb74f84-9whlm                1/1     Running   0          10m

NAME                                          DESIRED   CURRENT   READY   UP-TO-DATE   AVAILABLE   NODE SELECTOR                     AGE
daemonset.apps/numaresourcesoperator-worker   3         3         3       3            3           node-role.kubernetes.io/worker=   98s

NAME                                               READY   UP-TO-DATE   AVAILABLE   AGE
deployment.apps/numaresources-controller-manager   1/1     1            1           12m
deployment.apps/secondary-scheduler                1/1     1            1           10m

NAME                                                          DESIRED   CURRENT   READY   AGE
replicaset.apps/numaresources-controller-manager-7d9d84c58d   1         1         1       12m
replicaset.apps/secondary-scheduler-847cb74f84                1         1         1       10m
    Copy to Clipboard Toggle word wrap

12.5.3. Configuring a single NUMA node policy
Copy link

The NUMA Resources Operator requires a single NUMA node policy to be configured on the cluster. This can be achieved in two ways: by creating and applying a performance profile, or by configuring a KubeletConfig.

Note

The preferred way to configure a single NUMA node policy is to apply a performance profile. You can use the Performance Profile Creator (PPC) tool to create the performance profile. If a performance profile is created on the cluster, it automatically creates other tuning components like KubeletConfig and the tuned profile.

For more information about creating a performance profile, see "About the Performance Profile Creator" in the "Additional resources" section.

12.5.4. Sample performance profile
Copy link

This example YAML shows a performance profile created by using the performance profile creator (PPC) tool: 

apiVersion: performance.openshift.io/v2
kind: PerformanceProfile
metadata:
  name: performance
spec:
  cpu:
    isolated: "3"
    reserved: 0-2
  machineConfigPoolSelector:
    pools.operator.machineconfiguration.openshift.io/worker: ""
1 

  nodeSelector:
    node-role.kubernetes.io/worker: ""
  numa:
    topologyPolicy: single-numa-node
2 

  realTimeKernel:
    enabled: true
  workloadHints:
    highPowerConsumption: true
    perPodPowerManagement: false
    realTime: true
Copy to Clipboard Toggle word wrap
1
This should match the MachineConfigPool that you want to configure the NUMA Resources Operator on. For example, you might have created a MachineConfigPool named worker-cnf that designates a set of nodes that run telecommunications workloads.
2
The topologyPolicy must be set to single-numa-node. Ensure that this is the case by setting the topology-manager-policy argument to single-numa-node when running the PPC tool.

12.5.5. Creating a KubeletConfig CR
Copy link

The recommended way to configure a single NUMA node policy is to apply a performance profile. Another way is by creating and applying a KubeletConfig custom resource (CR), as shown in the following procedure.

Procedure

  1. Create the KubeletConfig custom resource (CR) that configures the pod admittance policy for the machine profile:

    1. Save the following YAML in the nro-kubeletconfig.yaml file: 

      apiVersion: machineconfiguration.openshift.io/v1
kind: KubeletConfig
metadata:
  name: worker-tuning
spec:
  machineConfigPoolSelector:
    matchLabels:
      pools.operator.machineconfiguration.openshift.io/worker: ""
      1 
      
  kubeletConfig:
    cpuManagerPolicy: "static"
      2 
      
    cpuManagerReconcilePeriod: "5s"
    reservedSystemCPUs: "0,1"
      3 
      
    memoryManagerPolicy: "Static"
      4 
      
    evictionHard:
      memory.available: "100Mi"
    kubeReserved:
      memory: "512Mi"
    reservedMemory:
      - numaNode: 0
        limits:
          memory: "1124Mi"
    systemReserved:
      memory: "512Mi"
    topologyManagerPolicy: "single-numa-node"
      5
      Copy to Clipboard Toggle word wrap
      1
      Adjust this label to match the machineConfigPoolSelector in the NUMAResourcesOperator CR.
      2
      For cpuManagerPolicy, static must use a lowercase s.
      3
      Adjust this based on the CPU on your nodes.
      4
      For memoryManagerPolicy, Static must use an uppercase S.
      5
      topologyManagerPolicy must be set to single-numa-node.

    2. Create the KubeletConfig CR by running the following command: 

      $ oc create -f nro-kubeletconfig.yaml
      Copy to Clipboard Toggle word wrap
      Note

      Applying performance profile or KubeletConfig automatically triggers rebooting of the nodes. If no reboot is triggered, you can troubleshoot the issue by looking at the labels in KubeletConfig that address the node group.

Now that topo-aware-scheduler is installed, the NUMAResourcesOperator and NUMAResourcesScheduler CRs are applied and your cluster has a matching performance profile or kubeletconfig, you can schedule workloads with the NUMA-aware scheduler using deployment CRs that specify the minimum required resources to process the workload.

The following example deployment uses NUMA-aware scheduling for a sample workload.

Prerequisites

  • Install the OpenShift CLI (oc).
  • Log in as a user with cluster-admin privileges.

Procedure

  1. Get the name of the NUMA-aware scheduler that is deployed in the cluster by running the following command: 

    $ oc get numaresourcesschedulers.nodetopology.openshift.io numaresourcesscheduler -o json | jq '.status.schedulerName'
    Copy to Clipboard Toggle word wrap

    Example output

    "topo-aware-scheduler"
    Copy to Clipboard Toggle word wrap

  2. Create a Deployment CR that uses scheduler named topo-aware-scheduler, for example:

    1. Save the following YAML in the nro-deployment.yaml file: 

      apiVersion: apps/v1
kind: Deployment
metadata:
  name: numa-deployment-1
  namespace: openshift-numaresources
spec:
  replicas: 1
  selector:
    matchLabels:
      app: test
  template:
    metadata:
      labels:
        app: test
    spec:
      schedulerName: topo-aware-scheduler
      1 
      
      containers:
      - name: ctnr
        image: quay.io/openshifttest/hello-openshift:openshift
        imagePullPolicy: IfNotPresent
        resources:
          limits:
            memory: "100Mi"
            cpu: "10"
          requests:
            memory: "100Mi"
            cpu: "10"
      - name: ctnr2
        image: registry.access.redhat.com/rhel:latest
        imagePullPolicy: IfNotPresent
        command: ["/bin/sh", "-c"]
        args: [ "while true; do sleep 1h; done;" ]
        resources:
          limits:
            memory: "100Mi"
            cpu: "8"
          requests:
            memory: "100Mi"
            cpu: "8"
      Copy to Clipboard Toggle word wrap
      1
      schedulerName must match the name of the NUMA-aware scheduler that is deployed in your cluster, for example topo-aware-scheduler.

    2. Create the Deployment CR by running the following command: 

      $ oc create -f nro-deployment.yaml
      Copy to Clipboard Toggle word wrap

Verification

  1. Verify that the deployment was successful: 

    $ oc get pods -n openshift-numaresources
    Copy to Clipboard Toggle word wrap

    Example output

    NAME                                                READY   STATUS    RESTARTS   AGE
numa-deployment-1-6c4f5bdb84-wgn6g                  2/2     Running   0          5m2s
numaresources-controller-manager-7d9d84c58d-4v65j   1/1     Running   0          18m
numaresourcesoperator-worker-7d96r                  2/2     Running   4          43m
numaresourcesoperator-worker-crsht                  2/2     Running   2          43m
numaresourcesoperator-worker-jp9mw                  2/2     Running   2          43m
secondary-scheduler-847cb74f84-fpncj                1/1     Running   0          18m
    Copy to Clipboard Toggle word wrap

  2. Verify that the topo-aware-scheduler is scheduling the deployed pod by running the following command: 

    $ oc describe pod numa-deployment-1-6c4f5bdb84-wgn6g -n openshift-numaresources
    Copy to Clipboard Toggle word wrap

    Example output

    Events:
  Type    Reason          Age    From                  Message
  ----    ------          ----   ----                  -------
  Normal  Scheduled       4m45s  topo-aware-scheduler  Successfully assigned openshift-numaresources/numa-deployment-1-6c4f5bdb84-wgn6g to worker-1
    Copy to Clipboard Toggle word wrap

    Note

    Deployments that request more resources than is available for scheduling will fail with a MinimumReplicasUnavailable error. The deployment succeeds when the required resources become available. Pods remain in the Pending state until the required resources are available.

  3. Verify that the expected allocated resources are listed for the node.

    1. Identify the node that is running the deployment pod by running the following command: 

      $ oc get pods -n openshift-numaresources -o wide
      Copy to Clipboard Toggle word wrap

      Example output

      NAME                                 READY   STATUS    RESTARTS   AGE   IP            NODE     NOMINATED NODE   READINESS GATES
numa-deployment-1-6c4f5bdb84-wgn6g   0/2     Running   0          82m   10.128.2.50   worker-1   <none>  <none>
      Copy to Clipboard Toggle word wrap

    2. Run the following command with the name of that node that is running the deployment pod. 

      $ oc describe noderesourcetopologies.topology.node.k8s.io worker-1
      Copy to Clipboard Toggle word wrap

      Example output

      ...

Zones:
  Costs:
    Name:   node-0
    Value:  10
    Name:   node-1
    Value:  21
  Name:     node-0
  Resources:
    Allocatable:  39
    Available:    21
      1 
      
    Capacity:     40
    Name:         cpu
    Allocatable:  6442450944
    Available:    6442450944
    Capacity:     6442450944
    Name:         hugepages-1Gi
    Allocatable:  134217728
    Available:    134217728
    Capacity:     134217728
    Name:         hugepages-2Mi
    Allocatable:  262415904768
    Available:    262206189568
    Capacity:     270146007040
    Name:         memory
  Type:           Node
      Copy to Clipboard Toggle word wrap

      1
      The Available capacity is reduced because of the resources that have been allocated to the guaranteed pod.

      Resources consumed by guaranteed pods are subtracted from the available node resources listed under noderesourcetopologies.topology.node.k8s.io.

  4. Resource allocations for pods with a Best-effort or Burstable quality of service (qosClass) are not reflected in the NUMA node resources under noderesourcetopologies.topology.node.k8s.io. If a pod’s consumed resources are not reflected in the node resource calculation, verify that the pod has qosClass of Guaranteed and the CPU request is an integer value, not a decimal value. You can verify the that the pod has a qosClass of Guaranteed by running the following command: 

    $ oc get pod numa-deployment-1-6c4f5bdb84-wgn6g -n openshift-numaresources -o jsonpath="{ .status.qosClass }"
    Copy to Clipboard Toggle word wrap

    Example output

    Guaranteed
    Copy to Clipboard Toggle word wrap

The daemons controlled by the NUMA Resources Operator in their nodeGroup poll resources to retrieve updates about available NUMA resources. You can fine-tune polling operations for these daemons by configuring the spec.nodeGroups specification in the NUMAResourcesOperator custom resource (CR). This provides advanced control of polling operations. Configure these specifications to improve scheduling behavior and troubleshoot suboptimal scheduling decisions.

The configuration options are the following:

  • infoRefreshMode: Determines the trigger condition for polling the kubelet. The NUMA Resources Operator reports the resulting information to the API server.
  • infoRefreshPeriod: Determines the duration between polling updates.

  • podsFingerprinting: Determines if point-in-time information for the current set of pods running on a node is exposed in polling updates.

    Note

    The default value for podsFingerprinting is EnabledExclusiveResources. To optimize scheduler performance, set podsFingerprinting to either EnabledExclusiveResources or Enabled. Additionally, configure the cacheResyncPeriod in the NUMAResourcesScheduler custom resource (CR) to a value greater than 0. The cacheResyncPeriod specification helps to report more exact resource availability by monitoring pending resources on nodes.

Prerequisites

  • Install the OpenShift CLI (oc).
  • Log in as a user with cluster-admin privileges.
  • Install the NUMA Resources Operator.

Procedure

  • Configure the spec.nodeGroups specification in your NUMAResourcesOperator CR: 

    apiVersion: nodetopology.openshift.io/v1
kind: NUMAResourcesOperator
metadata:
  name: numaresourcesoperator
spec:
  nodeGroups:
  - config:
      infoRefreshMode: Periodic
    1 
    
      infoRefreshPeriod: 10s
    2 
    
      podsFingerprinting: Enabled
    3 
    
    name: worker
    Copy to Clipboard Toggle word wrap
    1
    Valid values are Periodic, Events, PeriodicAndEvents. Use Periodic to poll the kubelet at intervals that you define in infoRefreshPeriod. Use Events to poll the kubelet at every pod lifecycle event. Use PeriodicAndEvents to enable both methods.
    2
    Define the polling interval for Periodic or PeriodicAndEvents refresh modes. The field is ignored if the refresh mode is Events.
    3
    Valid values are Enabled, Disabled, and EnabledExclusiveResources. Setting to Enabled or EnabledExclusiveResources is a requirement for the cacheResyncPeriod specification in the NUMAResourcesScheduler.

Verification

  1. After you deploy the NUMA Resources Operator, verify that the node group configurations were applied by running the following command: 

    $ oc get numaresop numaresourcesoperator -o json | jq '.status'
    Copy to Clipboard Toggle word wrap

    Example output

          ...

        "config": {
        "infoRefreshMode": "Periodic",
        "infoRefreshPeriod": "10s",
        "podsFingerprinting": "Enabled"
      },
      "name": "worker"

      ...
    Copy to Clipboard Toggle word wrap

12.7. Troubleshooting NUMA-aware scheduling
Copy link

To troubleshoot common problems with NUMA-aware pod scheduling, perform the following steps.

Prerequisites

  • Install the OpenShift Container Platform CLI (oc).
  • Log in as a user with cluster-admin privileges.
  • Install the NUMA Resources Operator and deploy the NUMA-aware secondary scheduler.

Procedure

  1. Verify that the noderesourcetopologies CRD is deployed in the cluster by running the following command: 

    $ oc get crd | grep noderesourcetopologies
    Copy to Clipboard Toggle word wrap

    Example output

    NAME                                                              CREATED AT
noderesourcetopologies.topology.node.k8s.io                       2022-01-18T08:28:06Z
    Copy to Clipboard Toggle word wrap

  2. Check that the NUMA-aware scheduler name matches the name specified in your NUMA-aware workloads by running the following command: 

    $ oc get numaresourcesschedulers.nodetopology.openshift.io numaresourcesscheduler -o json | jq '.status.schedulerName'
    Copy to Clipboard Toggle word wrap

    Example output

    topo-aware-scheduler
    Copy to Clipboard Toggle word wrap

  3. Verify that NUMA-aware schedulable nodes have the noderesourcetopologies CR applied to them. Run the following command: 

    $ oc get noderesourcetopologies.topology.node.k8s.io
    Copy to Clipboard Toggle word wrap

    Example output

    NAME                    AGE
compute-0.example.com   17h
compute-1.example.com   17h
    Copy to Clipboard Toggle word wrap

    Note

    The number of nodes should equal the number of worker nodes that are configured by the machine config pool (mcp) worker definition.

  4. Verify the NUMA zone granularity for all schedulable nodes by running the following command: 

    $ oc get noderesourcetopologies.topology.node.k8s.io -o yaml
    Copy to Clipboard Toggle word wrap

    Example output

    apiVersion: v1
items:
- apiVersion: topology.node.k8s.io/v1
  kind: NodeResourceTopology
  metadata:
    annotations:
      k8stopoawareschedwg/rte-update: periodic
    creationTimestamp: "2022-06-16T08:55:38Z"
    generation: 63760
    name: worker-0
    resourceVersion: "8450223"
    uid: 8b77be46-08c0-4074-927b-d49361471590
  topologyPolicies:
  - SingleNUMANodeContainerLevel
  zones:
  - costs:
    - name: node-0
      value: 10
    - name: node-1
      value: 21
    name: node-0
    resources:
    - allocatable: "38"
      available: "38"
      capacity: "40"
      name: cpu
    - allocatable: "134217728"
      available: "134217728"
      capacity: "134217728"
      name: hugepages-2Mi
    - allocatable: "262352048128"
      available: "262352048128"
      capacity: "270107316224"
      name: memory
    - allocatable: "6442450944"
      available: "6442450944"
      capacity: "6442450944"
      name: hugepages-1Gi
    type: Node
  - costs:
    - name: node-0
      value: 21
    - name: node-1
      value: 10
    name: node-1
    resources:
    - allocatable: "268435456"
      available: "268435456"
      capacity: "268435456"
      name: hugepages-2Mi
    - allocatable: "269231067136"
      available: "269231067136"
      capacity: "270573244416"
      name: memory
    - allocatable: "40"
      available: "40"
      capacity: "40"
      name: cpu
    - allocatable: "1073741824"
      available: "1073741824"
      capacity: "1073741824"
      name: hugepages-1Gi
    type: Node
- apiVersion: topology.node.k8s.io/v1
  kind: NodeResourceTopology
  metadata:
    annotations:
      k8stopoawareschedwg/rte-update: periodic
    creationTimestamp: "2022-06-16T08:55:37Z"
    generation: 62061
    name: worker-1
    resourceVersion: "8450129"
    uid: e8659390-6f8d-4e67-9a51-1ea34bba1cc3
  topologyPolicies:
  - SingleNUMANodeContainerLevel
  zones:
    1 
    
  - costs:
    - name: node-0
      value: 10
    - name: node-1
      value: 21
    name: node-0
    resources:
    2 
    
    - allocatable: "38"
      available: "38"
      capacity: "40"
      name: cpu
    - allocatable: "6442450944"
      available: "6442450944"
      capacity: "6442450944"
      name: hugepages-1Gi
    - allocatable: "134217728"
      available: "134217728"
      capacity: "134217728"
      name: hugepages-2Mi
    - allocatable: "262391033856"
      available: "262391033856"
      capacity: "270146301952"
      name: memory
    type: Node
  - costs:
    - name: node-0
      value: 21
    - name: node-1
      value: 10
    name: node-1
    resources:
    - allocatable: "40"
      available: "40"
      capacity: "40"
      name: cpu
    - allocatable: "1073741824"
      available: "1073741824"
      capacity: "1073741824"
      name: hugepages-1Gi
    - allocatable: "268435456"
      available: "268435456"
      capacity: "268435456"
      name: hugepages-2Mi
    - allocatable: "269192085504"
      available: "269192085504"
      capacity: "270534262784"
      name: memory
    type: Node
kind: List
metadata:
  resourceVersion: ""
  selfLink: ""
    Copy to Clipboard Toggle word wrap

    1
    Each stanza under zones describes the resources for a single NUMA zone.
    2
    resources describes the current state of the NUMA zone resources. Check that resources listed under items.zones.resources.available correspond to the exclusive NUMA zone resources allocated to each guaranteed pod.

12.7.1. Reporting more exact resource availability
Copy link

Enable the cacheResyncPeriod specification to help the NUMA Resources Operator report more exact resource availability by monitoring pending resources on nodes and synchronizing this information in the scheduler cache at a defined interval. This also helps to minimize Topology Affinity Error errors because of sub-optimal scheduling decisions. The lower the interval, the greater the network load. The cacheResyncPeriod specification is disabled by default.

Prerequisites

  • Install the OpenShift CLI (oc).
  • Log in as a user with cluster-admin privileges.

Procedure

  1. Delete the currently running NUMAResourcesScheduler resource:

    1. Get the active NUMAResourcesScheduler by running the following command: 

      $ oc get NUMAResourcesScheduler
      Copy to Clipboard Toggle word wrap

      Example output

      NAME                     AGE
numaresourcesscheduler   92m
      Copy to Clipboard Toggle word wrap

    2. Delete the secondary scheduler resource by running the following command: 

      $ oc delete NUMAResourcesScheduler numaresourcesscheduler
      Copy to Clipboard Toggle word wrap

      Example output

      numaresourcesscheduler.nodetopology.openshift.io "numaresourcesscheduler" deleted
      Copy to Clipboard Toggle word wrap

  2. Save the following YAML in the file nro-scheduler-cacheresync.yaml. This example changes the log level to Debug: 

    apiVersion: nodetopology.openshift.io/v1
kind: NUMAResourcesScheduler
metadata:
  name: numaresourcesscheduler
spec:
  imageSpec: "registry.redhat.io/openshift4/noderesourcetopology-scheduler-container-rhel8:v4.18"
  cacheResyncPeriod: "5s"
    1
    Copy to Clipboard Toggle word wrap
    1
    Enter an interval value in seconds for synchronization of the scheduler cache. A value of 5s is typical for most implementations.

  3. Create the updated NUMAResourcesScheduler resource by running the following command: 

    $ oc create -f nro-scheduler-cacheresync.yaml
    Copy to Clipboard Toggle word wrap

    Example output

    numaresourcesscheduler.nodetopology.openshift.io/numaresourcesscheduler created
    Copy to Clipboard Toggle word wrap

Verification steps

  1. Check that the NUMA-aware scheduler was successfully deployed:

    1. Run the following command to check that the CRD is created successfully: 

      $ oc get crd | grep numaresourcesschedulers
      Copy to Clipboard Toggle word wrap

      Example output

      NAME                                                              CREATED AT
numaresourcesschedulers.nodetopology.openshift.io                 2022-02-25T11:57:03Z
      Copy to Clipboard Toggle word wrap

    2. Check that the new custom scheduler is available by running the following command: 

      $ oc get numaresourcesschedulers.nodetopology.openshift.io
      Copy to Clipboard Toggle word wrap

      Example output

      NAME                     AGE
numaresourcesscheduler   3h26m
      Copy to Clipboard Toggle word wrap

  2. Check that the logs for the scheduler show the increased log level:

    1. Get the list of pods running in the openshift-numaresources namespace by running the following command: 

      $ oc get pods -n openshift-numaresources
      Copy to Clipboard Toggle word wrap

      Example output

      NAME                                               READY   STATUS    RESTARTS   AGE
numaresources-controller-manager-d87d79587-76mrm   1/1     Running   0          46h
numaresourcesoperator-worker-5wm2k                 2/2     Running   0          45h
numaresourcesoperator-worker-pb75c                 2/2     Running   0          45h
secondary-scheduler-7976c4d466-qm4sc               1/1     Running   0          21m
      Copy to Clipboard Toggle word wrap

    2. Get the logs for the secondary scheduler pod by running the following command: 

      $ oc logs secondary-scheduler-7976c4d466-qm4sc -n openshift-numaresources
      Copy to Clipboard Toggle word wrap

      Example output

      ...
I0223 11:04:55.614788       1 reflector.go:535] k8s.io/client-go/informers/factory.go:134: Watch close - *v1.Namespace total 11 items received
I0223 11:04:56.609114       1 reflector.go:535] k8s.io/client-go/informers/factory.go:134: Watch close - *v1.ReplicationController total 10 items received
I0223 11:05:22.626818       1 reflector.go:535] k8s.io/client-go/informers/factory.go:134: Watch close - *v1.StorageClass total 7 items received
I0223 11:05:31.610356       1 reflector.go:535] k8s.io/client-go/informers/factory.go:134: Watch close - *v1.PodDisruptionBudget total 7 items received
I0223 11:05:31.713032       1 eventhandlers.go:186] "Add event for scheduled pod" pod="openshift-marketplace/certified-operators-thtvq"
I0223 11:05:53.461016       1 eventhandlers.go:244] "Delete event for scheduled pod" pod="openshift-marketplace/certified-operators-thtvq"
      Copy to Clipboard Toggle word wrap

The NUMA-aware secondary scheduler is responsible for scheduling high-performance workloads on a worker node and within a NUMA node where the workloads can be optimally processed. By default, the secondary scheduler assigns workloads to the NUMA node within the chosen worker node that has the most available resources.

If you want to change where the workloads run, you can add the scoringStrategy setting to the NUMAResourcesScheduler custom resource and set its value to either MostAllocated or BalancedAllocation.

Prerequisites

  • Install the OpenShift CLI (oc).
  • Log in as a user with cluster-admin privileges.

Procedure

  1. Delete the currently running NUMAResourcesScheduler resource by using the following steps:

    1. Get the active NUMAResourcesScheduler by running the following command: 

      $ oc get NUMAResourcesScheduler
      Copy to Clipboard Toggle word wrap

      Example output

      NAME                     AGE
numaresourcesscheduler   92m
      Copy to Clipboard Toggle word wrap

    2. Delete the secondary scheduler resource by running the following command: 

      $ oc delete NUMAResourcesScheduler numaresourcesscheduler
      Copy to Clipboard Toggle word wrap

      Example output

      numaresourcesscheduler.nodetopology.openshift.io "numaresourcesscheduler" deleted
      Copy to Clipboard Toggle word wrap

  2. Save the following YAML in the file nro-scheduler-mostallocated.yaml. This example changes the scoringStrategy to MostAllocated: 

    apiVersion: nodetopology.openshift.io/v1
kind: NUMAResourcesScheduler
metadata:
  name: numaresourcesscheduler
spec:
  imageSpec: "registry.redhat.io/openshift4/noderesourcetopology-scheduler-container-rhel8:v{product-version}"
  scoringStrategy:
        type: "MostAllocated"
    1
    Copy to Clipboard Toggle word wrap
    1
    If the scoringStrategy configuration is omitted, the default of LeastAllocated applies.

  3. Create the updated NUMAResourcesScheduler resource by running the following command: 

    $ oc create -f nro-scheduler-mostallocated.yaml
    Copy to Clipboard Toggle word wrap

    Example output

    numaresourcesscheduler.nodetopology.openshift.io/numaresourcesscheduler created
    Copy to Clipboard Toggle word wrap

Verification

  1. Check that the NUMA-aware scheduler was successfully deployed by using the following steps:

    1. Run the following command to check that the custom resource definition (CRD) is created successfully: 

      $ oc get crd | grep numaresourcesschedulers
      Copy to Clipboard Toggle word wrap

      Example output

      NAME                                                              CREATED AT
numaresourcesschedulers.nodetopology.openshift.io                 2022-02-25T11:57:03Z
      Copy to Clipboard Toggle word wrap

    2. Check that the new custom scheduler is available by running the following command: 

      $ oc get numaresourcesschedulers.nodetopology.openshift.io
      Copy to Clipboard Toggle word wrap

      Example output

      NAME                     AGE
numaresourcesscheduler   3h26m
      Copy to Clipboard Toggle word wrap

  2. Verify that the ScoringStrategy has been applied correctly by running the following command to check the relevant ConfigMap resource for the scheduler: 

    $ oc get -n openshift-numaresources cm topo-aware-scheduler-config -o yaml | grep scoring -A 1
    Copy to Clipboard Toggle word wrap

    Example output

    scoringStrategy:
  type: MostAllocated
    Copy to Clipboard Toggle word wrap

12.7.3. Checking the NUMA-aware scheduler logs
Copy link

Troubleshoot problems with the NUMA-aware scheduler by reviewing the logs. If required, you can increase the scheduler log level by modifying the spec.logLevel field of the NUMAResourcesScheduler resource. Acceptable values are Normal, Debug, and Trace, with Trace being the most verbose option.

Note

To change the log level of the secondary scheduler, delete the running scheduler resource and re-deploy it with the changed log level. The scheduler is unavailable for scheduling new workloads during this downtime.

Prerequisites

  • Install the OpenShift CLI (oc).
  • Log in as a user with cluster-admin privileges.

Procedure

  1. Delete the currently running NUMAResourcesScheduler resource:

    1. Get the active NUMAResourcesScheduler by running the following command: 

      $ oc get NUMAResourcesScheduler
      Copy to Clipboard Toggle word wrap

      Example output

      NAME                     AGE
numaresourcesscheduler   90m
      Copy to Clipboard Toggle word wrap

    2. Delete the secondary scheduler resource by running the following command: 

      $ oc delete NUMAResourcesScheduler numaresourcesscheduler
      Copy to Clipboard Toggle word wrap

      Example output

      numaresourcesscheduler.nodetopology.openshift.io "numaresourcesscheduler" deleted
      Copy to Clipboard Toggle word wrap

  2. Save the following YAML in the file nro-scheduler-debug.yaml. This example changes the log level to Debug: 

    apiVersion: nodetopology.openshift.io/v1
kind: NUMAResourcesScheduler
metadata:
  name: numaresourcesscheduler
spec:
  imageSpec: "registry.redhat.io/openshift4/noderesourcetopology-scheduler-container-rhel8:v4.18"
  logLevel: Debug
    Copy to Clipboard Toggle word wrap

  3. Create the updated Debug logging NUMAResourcesScheduler resource by running the following command: 

    $ oc create -f nro-scheduler-debug.yaml
    Copy to Clipboard Toggle word wrap

    Example output

    numaresourcesscheduler.nodetopology.openshift.io/numaresourcesscheduler created
    Copy to Clipboard Toggle word wrap

Verification steps

  1. Check that the NUMA-aware scheduler was successfully deployed:

    1. Run the following command to check that the CRD is created successfully: 

      $ oc get crd | grep numaresourcesschedulers
      Copy to Clipboard Toggle word wrap

      Example output

      NAME                                                              CREATED AT
numaresourcesschedulers.nodetopology.openshift.io                 2022-02-25T11:57:03Z
      Copy to Clipboard Toggle word wrap

    2. Check that the new custom scheduler is available by running the following command: 

      $ oc get numaresourcesschedulers.nodetopology.openshift.io
      Copy to Clipboard Toggle word wrap

      Example output

      NAME                     AGE
numaresourcesscheduler   3h26m
      Copy to Clipboard Toggle word wrap

  2. Check that the logs for the scheduler shows the increased log level:

    1. Get the list of pods running in the openshift-numaresources namespace by running the following command: 

      $ oc get pods -n openshift-numaresources
      Copy to Clipboard Toggle word wrap

      Example output

      NAME                                               READY   STATUS    RESTARTS   AGE
numaresources-controller-manager-d87d79587-76mrm   1/1     Running   0          46h
numaresourcesoperator-worker-5wm2k                 2/2     Running   0          45h
numaresourcesoperator-worker-pb75c                 2/2     Running   0          45h
secondary-scheduler-7976c4d466-qm4sc               1/1     Running   0          21m
      Copy to Clipboard Toggle word wrap

    2. Get the logs for the secondary scheduler pod by running the following command: 

      $ oc logs secondary-scheduler-7976c4d466-qm4sc -n openshift-numaresources
      Copy to Clipboard Toggle word wrap

      Example output

      ...
I0223 11:04:55.614788       1 reflector.go:535] k8s.io/client-go/informers/factory.go:134: Watch close - *v1.Namespace total 11 items received
I0223 11:04:56.609114       1 reflector.go:535] k8s.io/client-go/informers/factory.go:134: Watch close - *v1.ReplicationController total 10 items received
I0223 11:05:22.626818       1 reflector.go:535] k8s.io/client-go/informers/factory.go:134: Watch close - *v1.StorageClass total 7 items received
I0223 11:05:31.610356       1 reflector.go:535] k8s.io/client-go/informers/factory.go:134: Watch close - *v1.PodDisruptionBudget total 7 items received
I0223 11:05:31.713032       1 eventhandlers.go:186] "Add event for scheduled pod" pod="openshift-marketplace/certified-operators-thtvq"
I0223 11:05:53.461016       1 eventhandlers.go:244] "Delete event for scheduled pod" pod="openshift-marketplace/certified-operators-thtvq"
      Copy to Clipboard Toggle word wrap

Troubleshoot noderesourcetopologies objects where unexpected results are occurring by inspecting the corresponding resource-topology-exporter logs.

Note

It is recommended that NUMA resource topology exporter instances in the cluster are named for nodes they refer to. For example, a worker node with the name worker should have a corresponding noderesourcetopologies object called worker.

Prerequisites

  • Install the OpenShift CLI (oc).
  • Log in as a user with cluster-admin privileges.

Procedure

  1. Get the daemonsets managed by the NUMA Resources Operator. Each daemonset has a corresponding nodeGroup in the NUMAResourcesOperator CR. Run the following command: 

    $ oc get numaresourcesoperators.nodetopology.openshift.io numaresourcesoperator -o jsonpath="{.status.daemonsets[0]}"
    Copy to Clipboard Toggle word wrap

    Example output

    {"name":"numaresourcesoperator-worker","namespace":"openshift-numaresources"}
    Copy to Clipboard Toggle word wrap

  2. Get the label for the daemonset of interest using the value for name from the previous step: 

    $ oc get ds -n openshift-numaresources numaresourcesoperator-worker -o jsonpath="{.spec.selector.matchLabels}"
    Copy to Clipboard Toggle word wrap

    Example output

    {"name":"resource-topology"}
    Copy to Clipboard Toggle word wrap

  3. Get the pods using the resource-topology label by running the following command: 

    $ oc get pods -n openshift-numaresources -l name=resource-topology -o wide
    Copy to Clipboard Toggle word wrap

    Example output

    NAME                                 READY   STATUS    RESTARTS   AGE    IP            NODE
numaresourcesoperator-worker-5wm2k   2/2     Running   0          2d1h   10.135.0.64   compute-0.example.com
numaresourcesoperator-worker-pb75c   2/2     Running   0          2d1h   10.132.2.33   compute-1.example.com
    Copy to Clipboard Toggle word wrap

  4. Examine the logs of the resource-topology-exporter container running on the worker pod that corresponds to the node you are troubleshooting. Run the following command: 

    $ oc logs -n openshift-numaresources -c resource-topology-exporter numaresourcesoperator-worker-pb75c
    Copy to Clipboard Toggle word wrap

    Example output

    I0221 13:38:18.334140       1 main.go:206] using sysinfo:
reservedCpus: 0,1
reservedMemory:
  "0": 1178599424
I0221 13:38:18.334370       1 main.go:67] === System information ===
I0221 13:38:18.334381       1 sysinfo.go:231] cpus: reserved "0-1"
I0221 13:38:18.334493       1 sysinfo.go:237] cpus: online "0-103"
I0221 13:38:18.546750       1 main.go:72]
cpus: allocatable "2-103"
hugepages-1Gi:
  numa cell 0 -> 6
  numa cell 1 -> 1
hugepages-2Mi:
  numa cell 0 -> 64
  numa cell 1 -> 128
memory:
  numa cell 0 -> 45758Mi
  numa cell 1 -> 48372Mi
    Copy to Clipboard Toggle word wrap

If you install the NUMA Resources Operator in a cluster with misconfigured cluster settings, in some circumstances, the Operator is shown as active but the logs of the resource topology exporter (RTE) daemon set pods show that the configuration for the RTE is missing, for example: 

Info: couldn't find configuration in "/etc/resource-topology-exporter/config.yaml"
Copy to Clipboard Toggle word wrap

This log message indicates that the kubeletconfig with the required configuration was not properly applied in the cluster, resulting in a missing RTE configmap. For example, the following cluster is missing a numaresourcesoperator-worker configmap custom resource (CR): 

$ oc get configmap
Copy to Clipboard Toggle word wrap

Example output

NAME                           DATA   AGE
0e2a6bd3.openshift-kni.io      0      6d21h
kube-root-ca.crt               1      6d21h
openshift-service-ca.crt       1      6d21h
topo-aware-scheduler-config    1      6d18h
Copy to Clipboard Toggle word wrap

In a correctly configured cluster, oc get configmap also returns a numaresourcesoperator-worker configmap CR.

Prerequisites

  • Install the OpenShift Container Platform CLI (oc).
  • Log in as a user with cluster-admin privileges.
  • Install the NUMA Resources Operator and deploy the NUMA-aware secondary scheduler.

Procedure

  1. Compare the values for spec.machineConfigPoolSelector.matchLabels in kubeletconfig and metadata.labels in the MachineConfigPool (mcp) worker CR using the following commands:

    1. Check the kubeletconfig labels by running the following command: 

      $ oc get kubeletconfig -o yaml
      Copy to Clipboard Toggle word wrap

      Example output

      machineConfigPoolSelector:
  matchLabels:
    cnf-worker-tuning: enabled
      Copy to Clipboard Toggle word wrap

    2. Check the mcp labels by running the following command: 

      $ oc get mcp worker -o yaml
      Copy to Clipboard Toggle word wrap

      Example output

      labels:
  machineconfiguration.openshift.io/mco-built-in: ""
  pools.operator.machineconfiguration.openshift.io/worker: ""
      Copy to Clipboard Toggle word wrap

      The cnf-worker-tuning: enabled label is not present in the MachineConfigPool object.

  2. Edit the MachineConfigPool CR to include the missing label, for example: 

    $ oc edit mcp worker -o yaml
    Copy to Clipboard Toggle word wrap

    Example output

    labels:
  machineconfiguration.openshift.io/mco-built-in: ""
  pools.operator.machineconfiguration.openshift.io/worker: ""
  cnf-worker-tuning: enabled
    Copy to Clipboard Toggle word wrap

  3. Apply the label changes and wait for the cluster to apply the updated configuration. Run the following command:

Verification

  • Check that the missing numaresourcesoperator-worker configmap CR is applied: 

    $ oc get configmap
    Copy to Clipboard Toggle word wrap

    Example output

    NAME                           DATA   AGE
0e2a6bd3.openshift-kni.io      0      6d21h
kube-root-ca.crt               1      6d21h
numaresourcesoperator-worker   1      5m
openshift-service-ca.crt       1      6d21h
topo-aware-scheduler-config    1      6d18h
    Copy to Clipboard Toggle word wrap

12.7.6. Collecting NUMA Resources Operator data
Copy link

You can use the oc adm must-gather CLI command to collect information about your cluster, including features and objects associated with the NUMA Resources Operator.

Prerequisites

  • You have access to the cluster as a user with the cluster-admin role.
  • You have installed the OpenShift CLI (oc).

Procedure

  • To collect NUMA Resources Operator data with must-gather, you must specify the NUMA Resources Operator must-gather image. 

    $ oc adm must-gather --image=registry.redhat.io/openshift4/numaresources-must-gather-rhel9:v4.18
    Copy to Clipboard Toggle word wrap
Back to top
Red Hat logoGithubredditYoutubeTwitter

Learn

Try, buy, & sell

Communities

About Red Hat Documentation

We help Red Hat users innovate and achieve their goals with our products and services with content they can trust. Explore our recent updates.

Making open source more inclusive

Red Hat is committed to replacing problematic language in our code, documentation, and web properties. For more details, see the Red Hat Blog.

About Red Hat

We deliver hardened solutions that make it easier for enterprises to work across platforms and environments, from the core datacenter to the network edge.

Theme

© 2025 Red Hat