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About NUMA-aware scheduling

Non-Uniform Memory Access (NUMA) is a compute platform architecture that allows different CPUs to access different regions of memory at different speeds. NUMA resource topology refers to the locations of CPUs, memory, and PCI devices relative to each other in the compute node. Co-located resources are said to be in the same NUMA zone. For high-performance applications, the cluster needs to process pod workloads in a single NUMA zone.

NUMA architecture allows a CPU with multiple memory controllers to use any available memory across CPU complexes, regardless of where the memory is located. This allows for increased flexibility at the expense of performance. A CPU processing a workload using memory that is outside its NUMA zone is slower than a workload processed in a single NUMA zone. Also, for I/O-constrained workloads, the network interface on a distant NUMA zone slows down how quickly information can reach the application. High-performance workloads, such as telecommunications workloads, cannot operate to specification under these conditions. 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.

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.

The default OKD 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 by not 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.

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

Diagram of NUMA-aware scheduling that shows how the various components interact with each other in the cluster
Figure 1. NUMA-aware scheduling overview
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.

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.

Additional resources

Installing the NUMA Resources Operator

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

Installing the NUMA Resources Operator using the CLI

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

      $ oc create -f nro-namespace.yaml
  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
    2. Create the OperatorGroup CR by running the following command:

      $ oc create -f nro-operatorgroup.yaml
  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"
        name: numaresources-operator
        source: redhat-operators
        sourceNamespace: openshift-marketplace
    2. Create the Subscription CR by running the following command:

      $ oc create -f nro-sub.yaml
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
    Example output
    NAME                             DISPLAY                  VERSION   REPLACES   PHASE
    numaresources-operator.v4.2   numaresources-operator   4.2               Succeeded

Installing the NUMA Resources Operator using the web console

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 OKD web console, click AdministrationNamespaces.

    2. Click Create Namespace, enter openshift-numaresources in the Name field, and then click Create.

  2. Install the NUMA Resources Operator:

    1. In the OKD web console, click OperatorsOperatorHub.

    2. Choose NUMA Resources 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 OperatorsInstalled Operators page.

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

      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 OperatorsInstalled Operators page and inspect the Operator Subscriptions and Install Plans tabs for any failure or errors under Status.

      • Go to the WorkloadsPods page and check the logs for pods in the default project.

Scheduling NUMA-aware workloads

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.

Creating the NUMAResourcesOperator custom resource

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 YAML in the nrop.yaml file:

      apiVersion: nodetopology.openshift.io/v1
      kind: NUMAResourcesOperator
      metadata:
        name: numaresourcesoperator
      spec:
        nodeGroups:
        - machineConfigPoolSelector:
            matchLabels:
              pools.operator.machineconfiguration.openshift.io/worker: ""
    2. Create the NUMAResourcesOperator CR by running the following command:

      $ oc create -f nrop.yaml
Verification
  • Verify that the NUMA Resources Operator deployed successfully by running the following command:

    $ oc get numaresourcesoperators.nodetopology.openshift.io
    Example output
    NAME                    AGE
    numaresourcesoperator   10m

Deploying the NUMA-aware secondary pod scheduler

After you install the NUMA Resources Operator, do the following to deploy the NUMA-aware secondary pod scheduler:

  • Configure the performance profile.

  • Deploy the NUMA-aware secondary scheduler.

Prerequisites
  • Install the OpenShift CLI (oc).

  • Log in as a user with cluster-admin privileges.

  • Create the required machine config pool.

  • Install the NUMA Resources Operator.

Procedure
  1. Create the PerformanceProfile custom resource (CR):

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

      apiVersion: performance.openshift.io/v2
      kind: PerformanceProfile
      metadata:
        name: perfprof-nrop
      spec:
        cpu: (1)
          isolated: "4-51,56-103"
          reserved: "0,1,2,3,52,53,54,55"
        nodeSelector:
          node-role.kubernetes.io/worker: ""
        numa:
          topologyPolicy: single-numa-node
      1 The cpu.isolated and cpu.reserved specifications define ranges for isolated and reserved CPUs. Enter valid values for your CPU configuration. See the Additional resources section for more information about configuring a performance profile.
    2. Create the PerformanceProfile CR by running the following command:

      $ oc create -f nro-perfprof.yaml
      Example output
      performanceprofile.performance.openshift.io/perfprof-nrop created
  2. Create the NUMAResourcesScheduler custom resource that deploys the NUMA-aware custom pod scheduler:

    1. Save the following 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"
        cacheResyncPeriod: "5s" (1)
      1 Enter an interval value in seconds for synchronization of the scheduler cache. A value of 5s is typical for most implementations.
      • Enable the cacheResyncPeriod specification to help the NUMA Resource 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.

      • Setting a value of Enabled for the podsFingerprinting specification in the NUMAResourcesOperator CR is a requirement for the implementation of the cacheResyncPeriod specification.

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

      $ oc create -f nro-scheduler.yaml
Verification
  1. Verify that the performance profile was applied by running the following command:

    $ oc describe performanceprofile <performance-profile-name>
  2. Verify that the required resources deployed successfully by running the following command:

    $ oc get all -n openshift-numaresources
    Example output
    NAME                                                    READY   STATUS    RESTARTS   AGE
    pod/numaresources-controller-manager-7575848485-bns4s   1/1     Running   0          13m
    pod/numaresourcesoperator-worker-dvj4n                  2/2     Running   0          16m
    pod/numaresourcesoperator-worker-lcg4t                  2/2     Running   0          16m
    pod/secondary-scheduler-56994cf6cf-7qf4q                1/1     Running   0          16m
    NAME                                          DESIRED   CURRENT   READY   UP-TO-DATE   AVAILABLE   NODE SELECTOR                     AGE
    daemonset.apps/numaresourcesoperator-worker   2         2         2       2            2           node-role.kubernetes.io/worker=   16m
    NAME                                               READY   UP-TO-DATE   AVAILABLE   AGE
    deployment.apps/numaresources-controller-manager   1/1     1            1           13m
    deployment.apps/secondary-scheduler                1/1     1            1           16m
    NAME                                                          DESIRED   CURRENT   READY   AGE
    replicaset.apps/numaresources-controller-manager-7575848485   1         1         1       13m
    replicaset.apps/secondary-scheduler-56994cf6cf                1         1         1       16m

Scheduling workloads with the NUMA-aware scheduler

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.

  • Install the NUMA Resources Operator and deploy the NUMA-aware secondary scheduler.

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'
    Example output
    topo-aware-scheduler
  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"
      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
Verification
  1. Verify that the deployment was successful:

    $ oc get pods -n openshift-numaresources
    Example output
    NAME                                                READY   STATUS    RESTARTS   AGE
    numa-deployment-1-56954b7b46-pfgw8                  2/2     Running   0          129m
    numaresources-controller-manager-7575848485-bns4s   1/1     Running   0          15h
    numaresourcesoperator-worker-dvj4n                  2/2     Running   0          18h
    numaresourcesoperator-worker-lcg4t                  2/2     Running   0          16h
    secondary-scheduler-56994cf6cf-7qf4q                1/1     Running   0          18h
  2. Verify that the topo-aware-scheduler is scheduling the deployed pod by running the following command:

    $ oc describe pod numa-deployment-1-56954b7b46-pfgw8 -n openshift-numaresources
    Example output
    Events:
      Type    Reason          Age   From                  Message
      ----    ------          ----  ----                  -------
      Normal  Scheduled       130m  topo-aware-scheduler  Successfully assigned openshift-numaresources/numa-deployment-1-56954b7b46-pfgw8 to compute-0.example.com

    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, replacing <namespace> with the namespace you specified in the Deployment CR:

      $ oc get pods -n <namespace> -o wide
      Example output
      NAME                                 READY   STATUS    RESTARTS   AGE   IP            NODE     NOMINATED NODE   READINESS GATES
      numa-deployment-1-65684f8fcc-bw4bw   0/2     Running   0          82m   10.128.2.50   worker-0   <none>  <none>
    2. Run the following command, replacing <node_name> with the name of that node that is running the deployment pod.

      $ oc describe noderesourcetopologies.topology.node.k8s.io <node_name>
      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
      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 <pod_name> -n <pod_namespace> -o jsonpath="{ .status.qosClass }"
    Example output
    Guaranteed

Scheduling NUMA-aware workloads with manual performance settings

Clusters running latency-sensitive workloads typically feature performance profiles that help to minimize workload latency and optimize performance. However, you can schedule NUMA-aware workloads in a pristine cluster that does not feature a performance profile. The following workflow features a pristine cluster that you can manually configure for performance by using the KubeletConfig resource. This is not the typical environment for scheduling NUMA-aware workloads.

Creating the NUMAResourcesOperator custom resource with manual performance settings

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. Optional: Create the MachineConfigPool custom resource that enables custom kubelet configurations for worker nodes:

    By default, OKD creates a MachineConfigPool resource for worker nodes in the cluster. You can create a custom MachineConfigPool resource if required.

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

      apiVersion: machineconfiguration.openshift.io/v1
      kind: MachineConfigPool
      metadata:
        labels:
          cnf-worker-tuning: enabled
          machineconfiguration.openshift.io/mco-built-in: ""
          pools.operator.machineconfiguration.openshift.io/worker: ""
        name: worker
      spec:
        machineConfigSelector:
          matchLabels:
            machineconfiguration.openshift.io/role: worker
        nodeSelector:
          matchLabels:
            node-role.kubernetes.io/worker: ""
    2. Create the MachineConfigPool CR by running the following command:

      $ oc create -f nro-machineconfig.yaml
  2. Create the NUMAResourcesOperator custom resource:

    1. Save the following YAML in the nrop.yaml file:

      apiVersion: nodetopology.openshift.io/v1
      kind: NUMAResourcesOperator
      metadata:
        name: numaresourcesoperator
      spec:
        nodeGroups:
        - machineConfigPoolSelector:
            matchLabels:
              pools.operator.machineconfiguration.openshift.io/worker: "" (1)
      1 Should match the label applied to worker nodes in the related MachineConfigPool CR.
    2. Create the NUMAResourcesOperator CR by running the following command:

      $ oc create -f nrop.yaml
Verification
  • Verify that the NUMA Resources Operator deployed successfully by running the following command:

    $ oc get numaresourcesoperators.nodetopology.openshift.io
    Example output
    NAME                    AGE
    numaresourcesoperator   10m

Deploying the NUMA-aware secondary pod scheduler with manual performance settings

After you install the NUMA Resources Operator, do the following to deploy the NUMA-aware secondary pod scheduler:

  • Configure the pod admittance policy for the required machine profile

  • Create the required machine config pool

  • Deploy the NUMA-aware secondary scheduler

Prerequisites
  • Install the OpenShift CLI (oc).

  • Log in as a user with cluster-admin privileges.

  • Install the NUMA Resources Operator.

Procedure
  1. Create the KubeletConfig custom resource 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: cnf-worker-tuning
      spec:
        machineConfigPoolSelector:
          matchLabels:
            cnf-worker-tuning: enabled
        kubeletConfig:
          cpuManagerPolicy: "static" (1)
          cpuManagerReconcilePeriod: "5s"
          reservedSystemCPUs: "0,1"
          memoryManagerPolicy: "Static" (2)
          evictionHard:
            memory.available: "100Mi"
          kubeReserved:
            memory: "512Mi"
          reservedMemory:
            - numaNode: 0
              limits:
                memory: "1124Mi"
          systemReserved:
            memory: "512Mi"
          topologyManagerPolicy: "single-numa-node" (3)
          topologyManagerScope: "pod"
      1 For cpuManagerPolicy, static must use a lowercase s.
      2 For memoryManagerPolicy, Static must use an uppercase S.
      3 topologyManagerPolicy must be set to single-numa-node.
    2. Create the KubeletConfig custom resource (CR) by running the following command:

      $ oc create -f nro-kubeletconfig.yaml
  2. Create the NUMAResourcesScheduler custom resource that deploys the NUMA-aware custom pod scheduler:

    1. Save the following 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-container-rhel8:v4"
        cacheResyncPeriod: "5s" (1)
      1 Enter an interval value in seconds for synchronization of the scheduler cache. A value of 5s is typical for most implementations.
      • Enable the cacheResyncPeriod specification to help the NUMA Resource 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.

      • Setting a value of Enabled for the podsFingerprinting specification in the NUMAResourcesOperator CR is a requirement for the implementation of the cacheResyncPeriod specification.

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

      $ oc create -f nro-scheduler.yaml
Verification
  • Verify that the required resources deployed successfully by running the following command:

    $ oc get all -n openshift-numaresources
    Example output
    NAME                                                    READY   STATUS    RESTARTS   AGE
    pod/numaresources-controller-manager-7575848485-bns4s   1/1     Running   0          13m
    pod/numaresourcesoperator-worker-dvj4n                  2/2     Running   0          16m
    pod/numaresourcesoperator-worker-lcg4t                  2/2     Running   0          16m
    pod/secondary-scheduler-56994cf6cf-7qf4q                1/1     Running   0          16m
    NAME                                          DESIRED   CURRENT   READY   UP-TO-DATE   AVAILABLE   NODE SELECTOR                     AGE
    daemonset.apps/numaresourcesoperator-worker   2         2         2       2            2           node-role.kubernetes.io/worker=   16m
    NAME                                               READY   UP-TO-DATE   AVAILABLE   AGE
    deployment.apps/numaresources-controller-manager   1/1     1            1           13m
    deployment.apps/secondary-scheduler                1/1     1            1           16m
    NAME                                                          DESIRED   CURRENT   READY   AGE
    replicaset.apps/numaresources-controller-manager-7575848485   1         1         1       13m
    replicaset.apps/secondary-scheduler-56994cf6cf                1         1         1       16m

Scheduling workloads with the NUMA-aware scheduler with manual performance settings

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.

  • Install the NUMA Resources Operator and deploy the NUMA-aware secondary scheduler.

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'
    Example output
    topo-aware-scheduler
  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"
      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
Verification
  1. Verify that the deployment was successful:

    $ oc get pods -n openshift-numaresources
    Example output
    NAME                                                READY   STATUS    RESTARTS   AGE
    numa-deployment-1-56954b7b46-pfgw8                  2/2     Running   0          129m
    numaresources-controller-manager-7575848485-bns4s   1/1     Running   0          15h
    numaresourcesoperator-worker-dvj4n                  2/2     Running   0          18h
    numaresourcesoperator-worker-lcg4t                  2/2     Running   0          16h
    secondary-scheduler-56994cf6cf-7qf4q                1/1     Running   0          18h
  2. Verify that the topo-aware-scheduler is scheduling the deployed pod by running the following command:

    $ oc describe pod numa-deployment-1-56954b7b46-pfgw8 -n openshift-numaresources
    Example output
    Events:
      Type    Reason          Age   From                  Message
      ----    ------          ----  ----                  -------
      Normal  Scheduled       130m  topo-aware-scheduler  Successfully assigned openshift-numaresources/numa-deployment-1-56954b7b46-pfgw8 to compute-0.example.com

    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, replacing <namespace> with the namespace you specified in the Deployment CR:

      $ oc get pods -n <namespace> -o wide
      Example output
      NAME                                 READY   STATUS    RESTARTS   AGE   IP            NODE     NOMINATED NODE   READINESS GATES
      numa-deployment-1-65684f8fcc-bw4bw   0/2     Running   0          82m   10.128.2.50   worker-0   <none>  <none>
    2. Run the following command, replacing <node_name> with the name of that node that is running the deployment pod:

      $ oc describe noderesourcetopologies.topology.node.k8s.io <node_name>
      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
      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 <pod_name> -n <pod_namespace> -o jsonpath="{ .status.qosClass }"
    Example output
    Guaranteed

Optional: Configuring polling operations for NUMA resources updates

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 behaviour 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.

    podsFingerprinting is enabled by default. podsFingerprinting is a requirement for the cacheResyncPeriod specification in the NUMAResourcesScheduler CR. 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
    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 or Disabled. Setting to Enabled 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'
    Example output
          ...
    
            "config": {
            "infoRefreshMode": "Periodic",
            "infoRefreshPeriod": "10s",
            "podsFingerprinting": "Enabled"
          },
          "name": "worker"
    
          ...

Troubleshooting NUMA-aware scheduling

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

Prerequisites
  • Install the OKD 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
    Example output
    NAME                                                              CREATED AT
    noderesourcetopologies.topology.node.k8s.io                       2022-01-18T08:28:06Z
  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'
    Example output
    topo-aware-scheduler
  3. Verify that NUMA-aware scheduable nodes have the noderesourcetopologies CR applied to them. Run the following command:

    $ oc get noderesourcetopologies.topology.node.k8s.io
    Example output
    NAME                    AGE
    compute-0.example.com   17h
    compute-1.example.com   17h

    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 scheduable nodes by running the following command:

    $ oc get noderesourcetopologies.topology.node.k8s.io -o yaml
    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: ""
    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.

Checking the NUMA-aware scheduler logs

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.

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
      Example output
      NAME                     AGE
      numaresourcesscheduler   90m
    2. Delete the secondary scheduler resource by running the following command:

      $ oc delete NUMAResourcesScheduler numaresourcesscheduler
      Example output
      numaresourcesscheduler.nodetopology.openshift.io "numaresourcesscheduler" deleted
  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"
      logLevel: Debug
  3. Create the updated Debug logging NUMAResourcesScheduler resource by running the following command:

    $ oc create -f nro-scheduler-debug.yaml
    Example output
    numaresourcesscheduler.nodetopology.openshift.io/numaresourcesscheduler created
Verification steps
  1. Check that the NUMA-aware scheduler was successfully deployed:

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

      $ oc get crd | grep numaresourcesschedulers
      Example output
      NAME                                                              CREATED AT
      numaresourcesschedulers.nodetopology.openshift.io                 2022-02-25T11:57:03Z
    2. Check that the new custom scheduler is available by running the following command:

      $ oc get numaresourcesschedulers.nodetopology.openshift.io
      Example output
      NAME                     AGE
      numaresourcesscheduler   3h26m
  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
      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
    2. Get the logs for the secondary scheduler pod by running the following command:

      $ oc logs secondary-scheduler-7976c4d466-qm4sc -n openshift-numaresources
      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"

Troubleshooting the resource topology exporter

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

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]}"
    Example output
    {"name":"numaresourcesoperator-worker","namespace":"openshift-numaresources"}
  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}"
    Example output
    {"name":"resource-topology"}
  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
    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
  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
    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

Correcting a missing resource topology exporter config map

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"

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
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

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

Prerequisites
  • Install the OKD 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
      Example output
      machineConfigPoolSelector:
        matchLabels:
          cnf-worker-tuning: enabled
    2. Check the mcp labels by running the following command:

      $ oc get mcp worker -o yaml
      Example output
      labels:
        machineconfiguration.openshift.io/mco-built-in: ""
        pools.operator.machineconfiguration.openshift.io/worker: ""

      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
    Example output
    labels:
      machineconfiguration.openshift.io/mco-built-in: ""
      pools.operator.machineconfiguration.openshift.io/worker: ""
      cnf-worker-tuning: enabled
  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
    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

Collecting NUMA Resources Operator data

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/numaresources-must-gather/numaresources-must-gather-rhel9:4