Scheduling NUMA-aware workloads

Scheduling NUMA-aware workloads

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

NUMA-aware scheduling is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.

For more information about the support scope of Red Hat Technology Preview features, see https://access.redhat.com/support/offerings/techpreview/.

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.

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.

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.

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.

Additional resources

For more information about running secondary pod schedulers in your cluster and how to deploy pods with a secondary pod scheduler, see Scheduling pods using a secondary scheduler.

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

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
```

Create the operator group for the NUMA Resources Operator:

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

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

Create the subscription for the NUMA Resources Operator:

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: "{product-version}"
  name: numaresources-operator
  source: redhat-operators
  sourceNamespace: openshift-marketplace

Create the Subscription CR by running the following command:
```
$ oc create -f nro-sub.yaml
```

Verification

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.v4.10.0  NUMA Resources Operator      4.10.0               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

Install the NUMA Resources Operator using the OKD web console:
1. In the OKD web console, click Operators → OperatorHub.
2. Choose NUMA Resources Operator from the list of available Operators, and then click Install.
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.
  
  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.

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

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

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: ""

Create the MachineConfigPool CR by running the following command:
```
$ oc create -f nro-machineconfig.yaml
```

Create the NUMAResourcesOperator custom resource:

Save the following YAML in the nrop.yaml file:

apiVersion: nodetopology.openshift.io/v1alpha1
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.

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 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

Create the KubeletConfig custom resource that configures the pod admittance policy for the machine profile:

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"
    cpuManagerReconcilePeriod: "5s"
    reservedSystemCPUs: "0,1"
    memoryManagerPolicy: "Static"
    evictionHard:
      memory.available: "100Mi"
    kubeReserved:
      memory: "512Mi"
    reservedMemory:
      - numaNode: 0
  limits:
    memory: "1124Mi"
    systemReserved:
      memory: "512Mi"
    topologyManagerPolicy: "single-numa-node" (1)
    topologyManagerScope: "pod" (2)

1	`topologyManagerPolicy` must be set to `single-numa-node`.
2	`topologyManagerScope` must be set to pod.

Create the KubeletConfig custom resource (CR) by running the following command:
```
$ oc create -f nro-kubeletconfig.yaml
```

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

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

apiVersion: nodetopology.openshift.io/v1alpha1
kind: NUMAResourcesScheduler
metadata:
  name: numaresourcesscheduler
spec:
  imageSpec: "registry.redhat.io/openshift4/noderesourcetopology-scheduler-container-rhel8:v4.10"

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

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

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

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

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`.

Create the Deployment CR by running the following command:
```
$ oc create -f nro-deployment.yaml
```

Verification

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

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.

Verify that the expected allocated resources are listed for the node. Run the following command:

$ 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.

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 by running the following command:
```
$ oc get pod <pod_name> -n <pod_namespace> -o jsonpath="{ .status.qosClass }"
```
Example output
```
Guaranteed
```

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

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

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

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.

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/v1alpha1
  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/v1alpha1
  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

Delete the currently running NUMAResourcesScheduler resource:

Get the active NUMAResourcesScheduler by running the following command:

$ oc get NUMAResourcesScheduler

Example output

NAME                     AGE
numaresourcesscheduler   90m

Delete the secondary scheduler resource by running the following command:

$ oc delete NUMAResourcesScheduler numaresourcesscheduler

Example output

numaresourcesscheduler.nodetopology.openshift.io "numaresourcesscheduler" deleted

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

apiVersion: nodetopology.openshift.io/v1alpha1
kind: NUMAResourcesScheduler
metadata:
  name: numaresourcesscheduler
spec:
  imageSpec: "registry.redhat.io/openshift4/noderesourcetopology-scheduler-container-rhel8:v4.10"
  logLevel: Debug

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

Check that the NUMA-aware scheduler was successfully deployed:

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

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

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

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

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

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"}

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"}

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

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

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.

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

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