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. Important 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 Technology Preview Features Support Scope . 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. 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 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 . 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 Create a namespace for the NUMA Resources Operator: Save the following YAML in the nro-namespace.yaml file: apiVersion: v1 kind: Namespace metadata: name: openshift-numaresources Create the Namespace CR by running the following command: USD 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: USD 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: USD 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: USD 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 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 Install the NUMA Resources Operator using the OpenShift Container Platform web console: In the OpenShift Container Platform web console, click Operators OperatorHub . Choose NUMA Resources Operator from the list of available Operators, and then click Install . Optional: Verify that the NUMA Resources Operator installed successfully: Switch to the Operators Installed Operators page. 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. 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: USD 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: USD oc create -f nrop.yaml Verification Verify that the NUMA Resources Operator deployed successfully by running the following command: USD oc get numaresourcesoperators.nodetopology.openshift.io Example output NAME AGE numaresourcesoperator 10m 6.4. 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" 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 . Create the KubeletConfig custom resource (CR) by running the following command: USD 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: USD oc create -f nro-scheduler.yaml Verification Verify that the required resources deployed successfully by running the following command: USD 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 6.5. 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: USD 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: 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 . Create the Deployment CR by running the following command: USD oc create -f nro-deployment.yaml Verification Verify that the deployment was successful: USD 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: USD 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. Verify that the expected allocated resources are listed for the node. Run the following command: USD 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: USD oc get pod <pod_name> -n <pod_namespace> -o jsonpath="{ .status.qosClass }" Example output Guaranteed 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 Verify that the noderesourcetopologies CRD is deployed in the cluster by running the following command: USD 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: USD 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: USD 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. Verify the NUMA zone granularity for all scheduable nodes by running the following command: USD 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. 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 Delete the currently running NUMAResourcesScheduler resource: Get the active NUMAResourcesScheduler by running the following command: USD oc get NUMAResourcesScheduler Example output NAME AGE numaresourcesscheduler 90m Delete the secondary scheduler resource by running the following command: USD 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: USD 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: USD 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: USD 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: USD 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: USD 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 Get the daemonsets managed by the NUMA Resources Operator. Each daemonset has a corresponding nodeGroup in the NUMAResourcesOperator CR. Run the following command: USD 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 step: USD 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: USD 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: USD 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): USD 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 Compare the values for spec.machineConfigPoolSelector.matchLabels in kubeletconfig and metadata.labels in the MachineConfigPool ( mcp ) worker CR using the following commands: Check the kubeletconfig labels by running the following command: USD oc get kubeletconfig -o yaml Example output machineConfigPoolSelector: matchLabels: cnf-worker-tuning: enabled Check the mcp labels by running the following command: USD 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: USD 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: USD 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

Commands:
apiVersion: v1 kind: Namespace metadata: name: openshift-numaresources
oc create -f nro-namespace.yaml
apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: numaresources-operator namespace: openshift-numaresources spec: targetNamespaces: - openshift-numaresources
oc create -f nro-operatorgroup.yaml
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
oc create -f nro-sub.yaml
oc get csv -n openshift-numaresources
NAME DISPLAY VERSION REPLACES PHASE numaresources-operator.v4.10.0 NUMA Resources Operator 4.10.0 Succeeded
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: ""
oc create -f nro-machineconfig.yaml
apiVersion: nodetopology.openshift.io/v1alpha1 kind: NUMAResourcesOperator metadata: name: numaresourcesoperator spec: nodeGroups: - machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: "" 1
oc create -f nrop.yaml
oc get numaresourcesoperators.nodetopology.openshift.io
NAME AGE numaresourcesoperator 10m
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"
oc create -f nro-kubeletconfig.yaml
apiVersion: nodetopology.openshift.io/v1alpha1 kind: NUMAResourcesScheduler metadata: name: numaresourcesscheduler spec: imageSpec: "registry.redhat.io/openshift4/noderesourcetopology-scheduler-container-rhel8:v4.10"
oc create -f nro-scheduler.yaml
oc get all -n openshift-numaresources
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
oc get numaresourcesschedulers.nodetopology.openshift.io numaresourcesscheduler -o json | jq '.status.schedulerName'
topo-aware-scheduler
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"
oc create -f nro-deployment.yaml
oc get pods -n openshift-numaresources
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
oc describe pod numa-deployment-1-56954b7b46-pfgw8 -n openshift-numaresources
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
oc describe noderesourcetopologies.topology.node.k8s.io
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
oc get pod <pod_name> -n <pod_namespace> -o jsonpath="{ .status.qosClass }"
Guaranteed
oc get crd | grep noderesourcetopologies
NAME CREATED AT noderesourcetopologies.topology.node.k8s.io 2022-01-18T08:28:06Z
oc get numaresourcesschedulers.nodetopology.openshift.io numaresourcesscheduler -o json | jq '.status.schedulerName'
topo-aware-scheduler
oc get noderesourcetopologies.topology.node.k8s.io
NAME AGE compute-0.example.com 17h compute-1.example.com 17h
oc get noderesourcetopologies.topology.node.k8s.io -o yaml
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: ""
oc get NUMAResourcesScheduler
NAME AGE numaresourcesscheduler 90m
oc delete NUMAResourcesScheduler numaresourcesscheduler
numaresourcesscheduler.nodetopology.openshift.io "numaresourcesscheduler" deleted
apiVersion: nodetopology.openshift.io/v1alpha1 kind: NUMAResourcesScheduler metadata: name: numaresourcesscheduler spec: imageSpec: "registry.redhat.io/openshift4/noderesourcetopology-scheduler-container-rhel8:v4.10" logLevel: Debug
oc create -f nro-scheduler-debug.yaml
numaresourcesscheduler.nodetopology.openshift.io/numaresourcesscheduler created
oc get crd | grep numaresourcesschedulers
NAME CREATED AT numaresourcesschedulers.nodetopology.openshift.io 2022-02-25T11:57:03Z
oc get numaresourcesschedulers.nodetopology.openshift.io
NAME AGE numaresourcesscheduler 3h26m
oc get pods -n openshift-numaresources
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
oc logs secondary-scheduler-7976c4d466-qm4sc -n openshift-numaresources
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"
oc get numaresourcesoperators.nodetopology.openshift.io numaresourcesoperator -o jsonpath="{.status.daemonsets[0]}"
name: numaresourcesoperator-worker
namespace: openshift-numaresources
oc get ds -n openshift-numaresources numaresourcesoperator-worker -o jsonpath="{.spec.selector.matchLabels}"
name: resource-topology
oc get pods -n openshift-numaresources -l name=resource-topology -o wide
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
oc logs -n openshift-numaresources -c resource-topology-exporter numaresourcesoperator-worker-pb75c
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
Info: couldn't find configuration in "/etc/resource-topology-exporter/config.yaml"
oc get configmap
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
oc get kubeletconfig -o yaml
machineConfigPoolSelector: matchLabels: cnf-worker-tuning: enabled
oc get mcp worker -o yaml
labels: machineconfiguration.openshift.io/mco-built-in: "" pools.operator.machineconfiguration.openshift.io/worker: ""
oc edit mcp worker -o yaml
labels: machineconfiguration.openshift.io/mco-built-in: "" pools.operator.machineconfiguration.openshift.io/worker: "" cnf-worker-tuning: enabled
oc get configmap
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