Chapter 6. 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.

6.1. 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 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 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 OpenShift Container Platform pod scheduler. The following diagram provides a high-level overview of NUMA-aware pod scheduling.

Figure 6.1. NUMA-aware scheduling overview

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.

Additional resources

6.2. 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 OpenShift Container Platform CLI or the web console.

6.2.1. 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/v1
kind: Subscription
metadata:
  name: numaresources-operator
  namespace: openshift-numaresources
spec:
  channel: "4.13"
  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.v4.13.2   numaresources-operator   4.13.2               Succeeded

6.2.2. 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. Install the NUMA Resources Operator using the OpenShift Container Platform web console:

    1. In the OpenShift Container Platform web console, click Operators → OperatorHub.
    2. Choose NUMA Resources Operator from the list of available Operators, and then click Install.

  2. 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 default project 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.

6.3. 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.

6.3.1. 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

6.3.2. 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-container-rhel8:v4.13"
  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.
      Note
      • 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

Additional resources

6.3.3. 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: gcr.io/google_containers/pause-amd64:3.0
        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

    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, 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

      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

6.4. 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.

6.4.1. 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:

    Note

    By default, OpenShift Container Platform 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

6.4.2. 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:v4.13"
  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.
      Note
      • 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

6.4.3. 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: <namespace> 1
spec:
  replicas: 1
  selector:
    matchLabels:
      app: test
  template:
    metadata:
      labels:
        app: test
    spec:
      schedulerName: topo-aware-scheduler 2
      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: gcr.io/google_containers/pause-amd64:3.0
        imagePullPolicy: IfNotPresent
        resources:
          limits:
            memory: "100Mi"
            cpu: "8"
          requests:
            memory: "100Mi"
            cpu: "8"
      1
      Replace with the namespace for your deployment.
      2
      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

    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, 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

6.5. 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.

    Note

    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"

      ...

6.6. Troubleshooting NUMA-aware scheduling

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

    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

    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 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.

6.6.1. 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.

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

      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:v4.13"
  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"

6.6.2. Troubleshooting the resource topology exporter

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]}"

    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

6.6.3. 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 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

      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