Chapter 14. Logging, events, and monitoring 14.1. Virtualization Overview page The Virtualization Overview page provides a comprehensive view of virtualization resources, details, status, and top consumers: The Overview tab displays Getting started resources, details, inventory, alerts, and other information about your OpenShift Virtualization environment. The Top consumers tab displays high utilization of a specific resource by projects, virtual machines, or nodes. The Migrations tab displays the status of live migrations. The Settings tab displays cluster-wide settings, including live migration settings and user permissions. By gaining an insight into the overall health of OpenShift Virtualization, you can determine if intervention is required to resolve specific issues identified by examining the data. 14.1.1. Reviewing top consumers You can view the top consumers of resources for a selected project, virtual machine, or node on the Top consumers tab of the Virtualization Overview page. Prerequisites You must have access to the cluster as a user with the cluster-admin role. To use the vCPU wait metric on the Top consumers tab, you must apply the schedstats=enable kernel argument to the MachineConfig object. Procedure In the Administrator perspective in the OpenShift Container Platform web console, navigate to Virtualization Overview . Click the Top consumers tab. Optional: You can filter the results by selecting a time period or by selecting the 5 or 10 top consumers. 14.1.2. Additional resources Adding kernel arguments to nodes Monitoring overview Reviewing monitoring dashboards Dashboards 14.2. Viewing OpenShift Virtualization logs You can view logs for OpenShift Virtualization components and virtual machines by using the web console or the oc CLI. You can retrieve virtual machine logs from the virt-launcher pod. To control log verbosity, edit the HyperConverged custom resource. 14.2.1. Viewing OpenShift Virtualization logs with the CLI Configure log verbosity for OpenShift Virtualization components by editing the HyperConverged custom resource (CR). Then, view logs for the component pods by using the oc CLI tool. Procedure To set log verbosity for specific components, open the HyperConverged CR in your default text editor by running the following command: USD oc edit hyperconverged kubevirt-hyperconverged -n openshift-cnv Set the log level for one or more components by editing the spec.logVerbosityConfig stanza. For example: apiVersion: hco.kubevirt.io/v1beta1 kind: HyperConverged metadata: name: kubevirt-hyperconverged spec: logVerbosityConfig: kubevirt: virtAPI: 5 1 virtController: 4 virtHandler: 3 virtLauncher: 2 virtOperator: 6 1 The log verbosity value must be an integer in the range 1-9 , where a higher number indicates a more detailed log. In this example, the virtAPI component logs are exposed if their priority level is 5 or higher. Apply your changes by saving and exiting the editor. View a list of pods in the OpenShift Virtualization namespace by running the following command: USD oc get pods -n openshift-cnv Example 14.1. Example output NAME READY STATUS RESTARTS AGE disks-images-provider-7gqbc 1/1 Running 0 32m disks-images-provider-vg4kx 1/1 Running 0 32m virt-api-57fcc4497b-7qfmc 1/1 Running 0 31m virt-api-57fcc4497b-tx9nc 1/1 Running 0 31m virt-controller-76c784655f-7fp6m 1/1 Running 0 30m virt-controller-76c784655f-f4pbd 1/1 Running 0 30m virt-handler-2m86x 1/1 Running 0 30m virt-handler-9qs6z 1/1 Running 0 30m virt-operator-7ccfdbf65f-q5snk 1/1 Running 0 32m virt-operator-7ccfdbf65f-vllz8 1/1 Running 0 32m To view logs for a component pod, run the following command: USD oc logs -n openshift-cnv <pod_name> For example: USD oc logs -n openshift-cnv virt-handler-2m86x Note If a pod fails to start, you can use the -- option to view logs from the last attempt. To monitor log output in real time, use the -f option. Example 14.2. Example output {"component":"virt-handler","level":"info","msg":"set verbosity to 2","pos":"virt-handler.go:453","timestamp":"2022-04-17T08:58:37.373695Z"} {"component":"virt-handler","level":"info","msg":"set verbosity to 2","pos":"virt-handler.go:453","timestamp":"2022-04-17T08:58:37.373726Z"} {"component":"virt-handler","level":"info","msg":"setting rate limiter to 5 QPS and 10 Burst","pos":"virt-handler.go:462","timestamp":"2022-04-17T08:58:37.373782Z"} {"component":"virt-handler","level":"info","msg":"CPU features of a minimum baseline CPU model: map[apic:true clflush:true cmov:true cx16:true cx8:true de:true fpu:true fxsr:true lahf_lm:true lm:true mca:true mce:true mmx:true msr:true mtrr:true nx:true pae:true pat:true pge:true pni:true pse:true pse36:true sep:true sse:true sse2:true sse4.1:true ssse3:true syscall:true tsc:true]","pos":"cpu_plugin.go:96","timestamp":"2022-04-17T08:58:37.390221Z"} {"component":"virt-handler","level":"warning","msg":"host model mode is expected to contain only one model","pos":"cpu_plugin.go:103","timestamp":"2022-04-17T08:58:37.390263Z"} {"component":"virt-handler","level":"info","msg":"node-labeller is running","pos":"node_labeller.go:94","timestamp":"2022-04-17T08:58:37.391011Z"} 14.2.2. Viewing virtual machine logs in the web console Get virtual machine logs from the associated virtual machine launcher pod. Procedure In the OpenShift Container Platform console, click Virtualization VirtualMachines from the side menu. Select a virtual machine to open the VirtualMachine details page. Click the Details tab. Click the virt-launcher-<name> pod in the Pod section to open the Pod details page. Click the Logs tab to view the pod logs. 14.2.3. Common error messages The following error messages might appear in OpenShift Virtualization logs: ErrImagePull or ImagePullBackOff Indicates an incorrect deployment configuration or problems with the images that are referenced. 14.3. Viewing events 14.3.1. About virtual machine events OpenShift Container Platform events are records of important life-cycle information in a namespace and are useful for monitoring and troubleshooting resource scheduling, creation, and deletion issues. OpenShift Virtualization adds events for virtual machines and virtual machine instances. These can be viewed from either the web console or the CLI. See also: Viewing system event information in an OpenShift Container Platform cluster . 14.3.2. Viewing the events for a virtual machine in the web console You can view streaming events for a running virtual machine on the VirtualMachine details page of the web console. Procedure Click Virtualization VirtualMachines from the side menu. Select a virtual machine to open the VirtualMachine details page. Click the Events tab to view streaming events for the virtual machine. The ▮▮ button pauses the events stream. The ▶ button resumes a paused events stream. 14.3.3. Viewing namespace events in the CLI Use the OpenShift Container Platform client to get the events for a namespace. Procedure In the namespace, use the oc get command: USD oc get events 14.3.4. Viewing resource events in the CLI Events are included in the resource description, which you can get using the OpenShift Container Platform client. Procedure In the namespace, use the oc describe command. The following example shows how to get the events for a virtual machine, a virtual machine instance, and the virt-launcher pod for a virtual machine: USD oc describe vm <vm> USD oc describe vmi <vmi> USD oc describe pod virt-launcher-<name> 14.4. Monitoring live migration You can monitor the progress of live migration from either the web console or the CLI. 14.4.1. Monitoring live migration by using the web console You can monitor the progress of all live migrations on the Overview Migrations tab in the web console. You can view the migration metrics of a virtual machine on the VirtualMachine details Metrics tab in the web console. 14.4.2. Monitoring live migration of a virtual machine instance in the CLI The status of the virtual machine migration is stored in the Status component of the VirtualMachineInstance configuration. Procedure Use the oc describe command on the migrating virtual machine instance: USD oc describe vmi vmi-fedora Example output ... Status: Conditions: Last Probe Time: <nil> Last Transition Time: <nil> Status: True Type: LiveMigratable Migration Method: LiveMigration Migration State: Completed: true End Timestamp: 2018-12-24T06:19:42Z Migration UID: d78c8962-0743-11e9-a540-fa163e0c69f1 Source Node: node2.example.com Start Timestamp: 2018-12-24T06:19:35Z Target Node: node1.example.com Target Node Address: 10.9.0.18:43891 Target Node Domain Detected: true 14.4.3. Metrics You can use Prometheus queries to monitor live migration. 14.4.3.1. Live migration metrics The following metrics can be queried to show live migration status: kubevirt_migrate_vmi_data_processed_bytes The amount of guest operating system (OS) data that has migrated to the new virtual machine (VM). Type: Gauge. kubevirt_migrate_vmi_data_remaining_bytes The amount of guest OS data that remains to be migrated. Type: Gauge. kubevirt_migrate_vmi_dirty_memory_rate_bytes The rate at which memory is becoming dirty in the guest OS. Dirty memory is data that has been changed but not yet written to disk. Type: Gauge. kubevirt_migrate_vmi_pending_count The number of pending migrations. Type: Gauge. kubevirt_migrate_vmi_scheduling_count The number of scheduling migrations. Type: Gauge. kubevirt_migrate_vmi_running_count The number of running migrations. Type: Gauge. kubevirt_migrate_vmi_succeeded The number of successfully completed migrations. Type: Gauge. kubevirt_migrate_vmi_failed The number of failed migrations. Type: Gauge. 14.5. Diagnosing data volumes using events and conditions Use the oc describe command to analyze and help resolve issues with data volumes. 14.5.1. About conditions and events Diagnose data volume issues by examining the output of the Conditions and Events sections generated by the command: USD oc describe dv <DataVolume> There are three Types in the Conditions section that display: Bound Running Ready The Events section provides the following additional information: Type of event Reason for logging Source of the event Message containing additional diagnostic information. The output from oc describe does not always contains Events . An event is generated when either Status , Reason , or Message changes. Both conditions and events react to changes in the state of the data volume. For example, if you misspell the URL during an import operation, the import generates a 404 message. That message change generates an event with a reason. The output in the Conditions section is updated as well. 14.5.2. Analyzing data volumes using conditions and events By inspecting the Conditions and Events sections generated by the describe command, you determine the state of the data volume in relation to persistent volume claims (PVCs), and whether or not an operation is actively running or completed. You might also receive messages that offer specific details about the status of the data volume, and how it came to be in its current state. There are many different combinations of conditions. Each must be evaluated in its unique context. Examples of various combinations follow. Bound - A successfully bound PVC displays in this example. Note that the Type is Bound , so the Status is True . If the PVC is not bound, the Status is False . When the PVC is bound, an event is generated stating that the PVC is bound. In this case, the Reason is Bound and Status is True . The Message indicates which PVC owns the data volume. Message , in the Events section, provides further details including how long the PVC has been bound ( Age ) and by what resource ( From ), in this case datavolume-controller : Example output Status: Conditions: Last Heart Beat Time: 2020-07-15T03:58:24Z Last Transition Time: 2020-07-15T03:58:24Z Message: PVC win10-rootdisk Bound Reason: Bound Status: True Type: Bound Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal Bound 24s datavolume-controller PVC example-dv Bound Running - In this case, note that Type is Running and Status is False , indicating that an event has occurred that caused an attempted operation to fail, changing the Status from True to False . However, note that Reason is Completed and the Message field indicates Import Complete . In the Events section, the Reason and Message contain additional troubleshooting information about the failed operation. In this example, the Message displays an inability to connect due to a 404 , listed in the Events section's first Warning . From this information, you conclude that an import operation was running, creating contention for other operations that are attempting to access the data volume: Example output Status: Conditions: Last Heart Beat Time: 2020-07-15T04:31:39Z Last Transition Time: 2020-07-15T04:31:39Z Message: Import Complete Reason: Completed Status: False Type: Running Events: Type Reason Age From Message ---- ------ ---- ---- ------- Warning Error 12s (x2 over 14s) datavolume-controller Unable to connect to http data source: expected status code 200, got 404. Status: 404 Not Found Ready - If Type is Ready and Status is True , then the data volume is ready to be used, as in the following example. If the data volume is not ready to be used, the Status is False : Example output Status: Conditions: Last Heart Beat Time: 2020-07-15T04:31:39Z Last Transition Time: 2020-07-15T04:31:39Z Status: True Type: Ready 14.6. Viewing information about virtual machine workloads You can view high-level information about your virtual machines by using the Virtual Machines dashboard in the OpenShift Container Platform web console. 14.6.1. The Virtual Machines dashboard Access virtual machines (VMs) from the OpenShift Container Platform web console by navigating to the Virtualization VirtualMachines page and clicking a virtual machine (VM) to view the VirtualMachine details page. The Overview tab displays the following cards: Details provides identifying information about the virtual machine, including: Name Status Date of creation Operating system CPU and memory Hostname Template If the VM is running, there is an active VNC preview window and a link to open the VNC web console. The Options menu on the Details card provides options to stop or pause the VM, and to copy the ssh over nodeport command for SSH tunneling. Alerts lists VM alerts with three severity levels: Critical Warning Info Snapshots provides information about VM snapshots and the ability to take a snapshot. For each snapshot listed, the Snapshots card includes: A visual indicator of the status of the snapshot, if it is successfully created, is still in progress, or has failed. An Options menu with options to restore or delete the snapshot Network interfaces provides information about the network interfaces of the VM, including: Name (Network and Type) IP address, with the ability to copy the IP address to the clipboard Disks lists VM disks details, including: Name Drive Size Utilization includes charts that display usage data for: CPU Memory Storage Network transfer Note Use the drop-down list to choose a duration for the utilization data. The available options are 5 minutes , 1 hour , 6 hours , and 24 hours . Hardware Devices provides information about GPU and host devices, including: Resource name Hardware device name 14.7. Monitoring virtual machine health A virtual machine instance (VMI) can become unhealthy due to transient issues such as connectivity loss, deadlocks, or problems with external dependencies. A health check periodically performs diagnostics on a VMI by using any combination of the readiness and liveness probes. 14.7.1. About readiness and liveness probes Use readiness and liveness probes to detect and handle unhealthy virtual machine instances (VMIs). You can include one or more probes in the specification of the VMI to ensure that traffic does not reach a VMI that is not ready for it and that a new instance is created when a VMI becomes unresponsive. A readiness probe determines whether a VMI is ready to accept service requests. If the probe fails, the VMI is removed from the list of available endpoints until the VMI is ready. A liveness probe determines whether a VMI is responsive. If the probe fails, the VMI is deleted and a new instance is created to restore responsiveness. You can configure readiness and liveness probes by setting the spec.readinessProbe and the spec.livenessProbe fields of the VirtualMachineInstance object. These fields support the following tests: HTTP GET The probe determines the health of the VMI by using a web hook. The test is successful if the HTTP response code is between 200 and 399. You can use an HTTP GET test with applications that return HTTP status codes when they are completely initialized. TCP socket The probe attempts to open a socket to the VMI. The VMI is only considered healthy if the probe can establish a connection. You can use a TCP socket test with applications that do not start listening until initialization is complete. Guest agent ping The probe uses the guest-ping command to determine if the QEMU guest agent is running on the virtual machine. 14.7.2. Defining an HTTP readiness probe Define an HTTP readiness probe by setting the spec.readinessProbe.httpGet field of the virtual machine instance (VMI) configuration. Procedure Include details of the readiness probe in the VMI configuration file. Sample readiness probe with an HTTP GET test # ... spec: readinessProbe: httpGet: 1 port: 1500 2 path: /healthz 3 httpHeaders: - name: Custom-Header value: Awesome initialDelaySeconds: 120 4 periodSeconds: 20 5 timeoutSeconds: 10 6 failureThreshold: 3 7 successThreshold: 3 8 # ... 1 The HTTP GET request to perform to connect to the VMI. 2 The port of the VMI that the probe queries. In the above example, the probe queries port 1500. 3 The path to access on the HTTP server. In the above example, if the handler for the server's /healthz path returns a success code, the VMI is considered to be healthy. If the handler returns a failure code, the VMI is removed from the list of available endpoints. 4 The time, in seconds, after the VMI starts before the readiness probe is initiated. 5 The delay, in seconds, between performing probes. The default delay is 10 seconds. This value must be greater than timeoutSeconds . 6 The number of seconds of inactivity after which the probe times out and the VMI is assumed to have failed. The default value is 1. This value must be lower than periodSeconds . 7 The number of times that the probe is allowed to fail. The default is 3. After the specified number of attempts, the pod is marked Unready . 8 The number of times that the probe must report success, after a failure, to be considered successful. The default is 1. Create the VMI by running the following command: USD oc create -f <file_name>.yaml 14.7.3. Defining a TCP readiness probe Define a TCP readiness probe by setting the spec.readinessProbe.tcpSocket field of the virtual machine instance (VMI) configuration. Procedure Include details of the TCP readiness probe in the VMI configuration file. Sample readiness probe with a TCP socket test ... spec: readinessProbe: initialDelaySeconds: 120 1 periodSeconds: 20 2 tcpSocket: 3 port: 1500 4 timeoutSeconds: 10 5 ... 1 The time, in seconds, after the VMI starts before the readiness probe is initiated. 2 The delay, in seconds, between performing probes. The default delay is 10 seconds. This value must be greater than timeoutSeconds . 3 The TCP action to perform. 4 The port of the VMI that the probe queries. 5 The number of seconds of inactivity after which the probe times out and the VMI is assumed to have failed. The default value is 1. This value must be lower than periodSeconds . Create the VMI by running the following command: USD oc create -f <file_name>.yaml 14.7.4. Defining an HTTP liveness probe Define an HTTP liveness probe by setting the spec.livenessProbe.httpGet field of the virtual machine instance (VMI) configuration. You can define both HTTP and TCP tests for liveness probes in the same way as readiness probes. This procedure configures a sample liveness probe with an HTTP GET test. Procedure Include details of the HTTP liveness probe in the VMI configuration file. Sample liveness probe with an HTTP GET test # ... spec: livenessProbe: initialDelaySeconds: 120 1 periodSeconds: 20 2 httpGet: 3 port: 1500 4 path: /healthz 5 httpHeaders: - name: Custom-Header value: Awesome timeoutSeconds: 10 6 # ... 1 The time, in seconds, after the VMI starts before the liveness probe is initiated. 2 The delay, in seconds, between performing probes. The default delay is 10 seconds. This value must be greater than timeoutSeconds . 3 The HTTP GET request to perform to connect to the VMI. 4 The port of the VMI that the probe queries. In the above example, the probe queries port 1500. The VMI installs and runs a minimal HTTP server on port 1500 via cloud-init. 5 The path to access on the HTTP server. In the above example, if the handler for the server's /healthz path returns a success code, the VMI is considered to be healthy. If the handler returns a failure code, the VMI is deleted and a new instance is created. 6 The number of seconds of inactivity after which the probe times out and the VMI is assumed to have failed. The default value is 1. This value must be lower than periodSeconds . Create the VMI by running the following command: USD oc create -f <file_name>.yaml 14.7.5. Defining a guest agent ping probe Define a guest agent ping probe by setting the spec.readinessProbe.guestAgentPing field of the virtual machine instance (VMI) configuration. Important The guest agent ping probe 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 . Prerequisites The QEMU guest agent must be installed and enabled on the virtual machine. Procedure Include details of the guest agent ping probe in the VMI configuration file. For example: Sample guest agent ping probe # ... spec: readinessProbe: guestAgentPing: {} 1 initialDelaySeconds: 120 2 periodSeconds: 20 3 timeoutSeconds: 10 4 failureThreshold: 3 5 successThreshold: 3 6 # ... 1 The guest agent ping probe to connect to the VMI. 2 Optional: The time, in seconds, after the VMI starts before the guest agent probe is initiated. 3 Optional: The delay, in seconds, between performing probes. The default delay is 10 seconds. This value must be greater than timeoutSeconds . 4 Optional: The number of seconds of inactivity after which the probe times out and the VMI is assumed to have failed. The default value is 1. This value must be lower than periodSeconds . 5 Optional: The number of times that the probe is allowed to fail. The default is 3. After the specified number of attempts, the pod is marked Unready . 6 Optional: The number of times that the probe must report success, after a failure, to be considered successful. The default is 1. Create the VMI by running the following command: USD oc create -f <file_name>.yaml 14.7.6. Template: Virtual machine configuration file for defining health checks apiVersion: kubevirt.io/v1 kind: VirtualMachine metadata: labels: special: vm-fedora name: vm-fedora spec: template: metadata: labels: special: vm-fedora spec: domain: devices: disks: - disk: bus: virtio name: containerdisk - disk: bus: virtio name: cloudinitdisk resources: requests: memory: 1024M readinessProbe: httpGet: port: 1500 initialDelaySeconds: 120 periodSeconds: 20 timeoutSeconds: 10 failureThreshold: 3 successThreshold: 3 terminationGracePeriodSeconds: 180 volumes: - name: containerdisk containerDisk: image: kubevirt/fedora-cloud-registry-disk-demo - cloudInitNoCloud: userData: |- #cloud-config password: fedora chpasswd: { expire: False } bootcmd: - setenforce 0 - dnf install -y nmap-ncat - systemd-run --unit=httpserver nc -klp 1500 -e '/usr/bin/echo -e HTTP/1.1 200 OK\\n\\nHello World!' name: cloudinitdisk 14.7.7. Additional resources Monitoring application health by using health checks 14.8. Using the OpenShift Container Platform dashboard to get cluster information Access the OpenShift Container Platform dashboard, which captures high-level information about the cluster, by clicking Home > Dashboards > Overview from the OpenShift Container Platform web console. The OpenShift Container Platform dashboard provides various cluster information, captured in individual dashboard cards . 14.8.1. About the OpenShift Container Platform dashboards page Access the OpenShift Container Platform dashboard, which captures high-level information about the cluster, by navigating to Home Overview from the OpenShift Container Platform web console. The OpenShift Container Platform dashboard provides various cluster information, captured in individual dashboard cards. The OpenShift Container Platform dashboard consists of the following cards: Details provides a brief overview of informational cluster details. Status include ok , error , warning , in progress , and unknown . Resources can add custom status names. Cluster ID Provider Version Cluster Inventory details number of resources and associated statuses. It is helpful when intervention is required to resolve problems, including information about: Number of nodes Number of pods Persistent storage volume claims Virtual machines (available if OpenShift Virtualization is installed) Bare metal hosts in the cluster, listed according to their state (only available in metal3 environment). Cluster Health summarizes the current health of the cluster as a whole, including relevant alerts and descriptions. If OpenShift Virtualization is installed, the overall health of OpenShift Virtualization is diagnosed as well. If more than one subsystem is present, click See All to view the status of each subsystem. Bare metal hosts in the cluster, listed according to their state (only available in metal3 environment) Status helps administrators understand how cluster resources are consumed. Click on a resource to jump to a detailed page listing pods and nodes that consume the largest amount of the specified cluster resource (CPU, memory, or storage). Cluster Utilization shows the capacity of various resources over a specified period of time, to help administrators understand the scale and frequency of high resource consumption, including information about: CPU time Memory allocation Storage consumed Network resources consumed Pod count Activity lists messages related to recent activity in the cluster, such as pod creation or virtual machine migration to another host. 14.9. Reviewing resource usage by virtual machines Dashboards in the OpenShift Container Platform web console provide visual representations of cluster metrics to help you to quickly understand the state of your cluster. Dashboards belong to the Monitoring overview that provides monitoring for core platform components. The OpenShift Virtualization dashboard provides data on resource consumption for virtual machines and associated pods. The visualization metrics displayed in the OpenShift Virtualization dashboard are based on Prometheus Query Language (PromQL) queries . A monitoring role is required to monitor user-defined namespaces in the OpenShift Virtualization dashboard. You can view resource usage for a specific virtual machine on the VirtualMachine details page Metrics tab in the web console. 14.9.1. About reviewing top consumers In the OpenShift Virtualization dashboard, you can select a specific time period and view the top consumers of resources within that time period. Top consumers are virtual machines or virt-launcher pods that are consuming the highest amount of resources. The following table shows resources monitored in the dashboard and describes the metrics associated with each resource for top consumers. Monitored resources Description Memory swap traffic Virtual machines consuming the most memory pressure when swapping memory. vCPU wait Virtual machines experiencing the maximum wait time (in seconds) for their vCPUs. CPU usage by pod The virt-launcher pods that are using the most CPU. Network traffic Virtual machines that are saturating the network by receiving the most amount of network traffic (in bytes). Storage traffic Virtual machines with the highest amount (in bytes) of storage-related traffic. Storage IOPS Virtual machines with the highest amount of I/O operations per second over a time period. Memory usage The virt-launcher pods that are using the most memory (in bytes). Note Viewing the maximum resource consumption is limited to the top five consumers. 14.9.2. Reviewing top consumers In the Administrator perspective, you can view the OpenShift Virtualization dashboard where top consumers of resources are displayed. Prerequisites You have access to the cluster as a user with the cluster-admin role. Procedure In the Administrator perspective in the OpenShift Virtualization web console, navigate to Observe Dashboards . Select the KubeVirt/Infrastructure Resources/Top Consumers dashboard from the Dashboard list. Select a predefined time period from the drop-down menu for Period. You can review the data for top consumers in the tables. Optional: Click Inspect to view or edit the Prometheus Query Language (PromQL) query associated with the top consumers for a table. 14.9.3. Additional resources Monitoring overview Reviewing monitoring dashboards 14.10. OpenShift Container Platform cluster monitoring, logging, and Telemetry OpenShift Container Platform provides various resources for monitoring at the cluster level. 14.10.1. About OpenShift Container Platform monitoring OpenShift Container Platform includes a preconfigured, preinstalled, and self-updating monitoring stack that provides monitoring for core platform components . OpenShift Container Platform delivers monitoring best practices out of the box. A set of alerts are included by default that immediately notify cluster administrators about issues with a cluster. Default dashboards in the OpenShift Container Platform web console include visual representations of cluster metrics to help you to quickly understand the state of your cluster. After installing OpenShift Container Platform 4.12, cluster administrators can optionally enable monitoring for user-defined projects . By using this feature, cluster administrators, developers, and other users can specify how services and pods are monitored in their own projects. You can then query metrics, review dashboards, and manage alerting rules and silences for your own projects in the OpenShift Container Platform web console. Note Cluster administrators can grant developers and other users permission to monitor their own projects. Privileges are granted by assigning one of the predefined monitoring roles. 14.10.2. Logging architecture The major components of the logging are: Collector The collector is a daemonset that deploys pods to each OpenShift Container Platform node. It collects log data from each node, transforms the data, and forwards it to configured outputs. You can use the Vector collector or the legacy Fluentd collector. Note Fluentd is deprecated and is planned to be removed in a future release. Red Hat provides bug fixes and support for this feature during the current release lifecycle, but this feature no longer receives enhancements. As an alternative to Fluentd, you can use Vector instead. Log store The log store stores log data for analysis and is the default output for the log forwarder. You can use the default LokiStack log store, the legacy Elasticsearch log store, or forward logs to additional external log stores. Note The Logging 5.9 release does not contain an updated version of the OpenShift Elasticsearch Operator. If you currently use the OpenShift Elasticsearch Operator released with Logging 5.8, it will continue to work with Logging until the EOL of Logging 5.8. As an alternative to using the OpenShift Elasticsearch Operator to manage the default log storage, you can use the Loki Operator. For more information on the Logging lifecycle dates, see Platform Agnostic Operators . Visualization You can use a UI component to view a visual representation of your log data. The UI provides a graphical interface to search, query, and view stored logs. The OpenShift Container Platform web console UI is provided by enabling the OpenShift Container Platform console plugin. Note The Kibana web console is now deprecated is planned to be removed in a future logging release. Logging collects container logs and node logs. These are categorized into types: Application logs Container logs generated by user applications running in the cluster, except infrastructure container applications. Infrastructure logs Container logs generated by infrastructure namespaces: openshift* , kube* , or default , as well as journald messages from nodes. Audit logs Logs generated by auditd, the node audit system, which are stored in the /var/log/audit/audit.log file, and logs from the auditd , kube-apiserver , openshift-apiserver services, as well as the ovn project if enabled. For more information on OpenShift Logging, see the OpenShift Logging documentation. 14.10.3. About Telemetry Telemetry sends a carefully chosen subset of the cluster monitoring metrics to Red Hat. The Telemeter Client fetches the metrics values every four minutes and thirty seconds and uploads the data to Red Hat. These metrics are described in this document. This stream of data is used by Red Hat to monitor the clusters in real-time and to react as necessary to problems that impact our customers. It also allows Red Hat to roll out OpenShift Container Platform upgrades to customers to minimize service impact and continuously improve the upgrade experience. This debugging information is available to Red Hat Support and Engineering teams with the same restrictions as accessing data reported through support cases. All connected cluster information is used by Red Hat to help make OpenShift Container Platform better and more intuitive to use. 14.10.3.1. Information collected by Telemetry The following information is collected by Telemetry: 14.10.3.1.1. System information Version information, including the OpenShift Container Platform cluster version and installed update details that are used to determine update version availability Update information, including the number of updates available per cluster, the channel and image repository used for an update, update progress information, and the number of errors that occur in an update The unique random identifier that is generated during an installation Configuration details that help Red Hat Support to provide beneficial support for customers, including node configuration at the cloud infrastructure level, hostnames, IP addresses, Kubernetes pod names, namespaces, and services The OpenShift Container Platform framework components installed in a cluster and their condition and status Events for all namespaces listed as "related objects" for a degraded Operator Information about degraded software Information about the validity of certificates The name of the provider platform that OpenShift Container Platform is deployed on and the data center location 14.10.3.1.2. Sizing Information Sizing information about clusters, machine types, and machines, including the number of CPU cores and the amount of RAM used for each The number of running virtual machine instances in a cluster The number of etcd members and the number of objects stored in the etcd cluster Number of application builds by build strategy type 14.10.3.1.3. Usage information Usage information about components, features, and extensions Usage details about Technology Previews and unsupported configurations Telemetry does not collect identifying information such as usernames or passwords. Red Hat does not intend to collect personal information. If Red Hat discovers that personal information has been inadvertently received, Red Hat will delete such information. To the extent that any telemetry data constitutes personal data, please refer to the Red Hat Privacy Statement for more information about Red Hat's privacy practices. 14.10.4. CLI troubleshooting and debugging commands For a list of the oc client troubleshooting and debugging commands, see the OpenShift Container Platform CLI tools documentation. 14.11. Running cluster checkups OpenShift Virtualization includes predefined checkups that can be used for cluster maintenance and troubleshooting. Important The OpenShift Container Platform cluster checkup framework 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 . 14.11.1. About the OpenShift Container Platform cluster checkup framework A checkup is an automated test workload that allows you to verify if a specific cluster functionality works as expected. The cluster checkup framework uses native Kubernetes resources to configure and execute the checkup. By using predefined checkups, cluster administrators and developers can improve cluster maintainability, troubleshoot unexpected behavior, minimize errors, and save time. They can also review the results of the checkup and share them with experts for further analysis. Vendors can write and publish checkups for features or services that they provide and verify that their customer environments are configured correctly. Running a predefined checkup in an existing namespace involves setting up a service account for the checkup, creating the Role and RoleBinding objects for the service account, enabling permissions for the checkup, and creating the input config map and the checkup job. You can run a checkup multiple times. Important You must always: Verify that the checkup image is from a trustworthy source before applying it. Review the checkup permissions before creating the Role and RoleBinding objects. 14.11.2. Checking network connectivity and latency for virtual machines on a secondary network You use a predefined checkup to verify network connectivity and measure latency between two virtual machines (VMs) that are attached to a secondary network interface. To run a checkup for the first time, follow the steps in the procedure. If you have previously run a checkup, skip to step 5 of the procedure because the steps to install the framework and enable permissions for the checkup are not required. Prerequisites You installed the OpenShift CLI ( oc ). The cluster has at least two worker nodes. The Multus Container Network Interface (CNI) plugin is installed on the cluster. You configured a network attachment definition for a namespace. Procedure Create a manifest file that contains the ServiceAccount , Role , and RoleBinding objects with permissions that the checkup requires for cluster access: Example 14.3. Example role manifest file --- apiVersion: v1 kind: ServiceAccount metadata: name: vm-latency-checkup-sa --- apiVersion: rbac.authorization.k8s.io/v1 kind: Role metadata: name: kubevirt-vm-latency-checker rules: - apiGroups: ["kubevirt.io"] resources: ["virtualmachineinstances"] verbs: ["get", "create", "delete"] - apiGroups: ["subresources.kubevirt.io"] resources: ["virtualmachineinstances/console"] verbs: ["get"] - apiGroups: ["k8s.cni.cncf.io"] resources: ["network-attachment-definitions"] verbs: ["get"] --- apiVersion: rbac.authorization.k8s.io/v1 kind: RoleBinding metadata: name: kubevirt-vm-latency-checker subjects: - kind: ServiceAccount name: vm-latency-checkup-sa roleRef: kind: Role name: kubevirt-vm-latency-checker apiGroup: rbac.authorization.k8s.io --- apiVersion: rbac.authorization.k8s.io/v1 kind: Role metadata: name: kiagnose-configmap-access rules: - apiGroups: [ "" ] resources: [ "configmaps" ] verbs: ["get", "update"] --- apiVersion: rbac.authorization.k8s.io/v1 kind: RoleBinding metadata: name: kiagnose-configmap-access subjects: - kind: ServiceAccount name: vm-latency-checkup-sa roleRef: kind: Role name: kiagnose-configmap-access apiGroup: rbac.authorization.k8s.io Apply the checkup roles manifest: USD oc apply -n <target_namespace> -f <latency_roles>.yaml 1 1 <target_namespace> is the namespace where the checkup is to be run. This must be an existing namespace where the NetworkAttachmentDefinition object resides. Create a ConfigMap manifest that contains the input parameters for the checkup. The config map provides the input for the framework to run the checkup and also stores the results of the checkup. Example input config map apiVersion: v1 kind: ConfigMap metadata: name: kubevirt-vm-latency-checkup-config data: spec.timeout: 5m spec.param.network_attachment_definition_namespace: <target_namespace> spec.param.network_attachment_definition_name: "blue-network" 1 spec.param.max_desired_latency_milliseconds: "10" 2 spec.param.sample_duration_seconds: "5" 3 spec.param.source_node: "worker1" 4 spec.param.target_node: "worker2" 5 1 The name of the NetworkAttachmentDefinition object. 2 Optional: The maximum desired latency, in milliseconds, between the virtual machines. If the measured latency exceeds this value, the checkup fails. 3 Optional: The duration of the latency check, in seconds. 4 Optional: When specified, latency is measured from this node to the target node. If the source node is specified, the spec.param.target_node field cannot be empty. 5 Optional: When specified, latency is measured from the source node to this node. Apply the config map manifest in the target namespace: USD oc apply -n <target_namespace> -f <latency_config_map>.yaml Create a Job object to run the checkup: Example job manifest apiVersion: batch/v1 kind: Job metadata: name: kubevirt-vm-latency-checkup spec: backoffLimit: 0 template: spec: serviceAccountName: vm-latency-checkup-sa restartPolicy: Never containers: - name: vm-latency-checkup image: registry.redhat.io/container-native-virtualization/vm-network-latency-checkup:v4.12.0 securityContext: allowPrivilegeEscalation: false capabilities: drop: ["ALL"] runAsNonRoot: true seccompProfile: type: "RuntimeDefault" env: - name: CONFIGMAP_NAMESPACE value: <target_namespace> - name: CONFIGMAP_NAME value: kubevirt-vm-latency-checkup-config Apply the Job manifest. The checkup uses the ping utility to verify connectivity and measure latency. USD oc apply -n <target_namespace> -f <latency_job>.yaml Wait for the job to complete: USD oc wait job kubevirt-vm-latency-checkup -n <target_namespace> --for condition=complete --timeout 6m Review the results of the latency checkup by running the following command. If the maximum measured latency is greater than the value of the spec.param.max_desired_latency_milliseconds attribute, the checkup fails and returns an error. USD oc get configmap kubevirt-vm-latency-checkup-config -n <target_namespace> -o yaml Example output config map (success) apiVersion: v1 kind: ConfigMap metadata: name: kubevirt-vm-latency-checkup-config namespace: <target_namespace> data: spec.timeout: 5m spec.param.network_attachment_definition_namespace: <target_namespace> spec.param.network_attachment_definition_name: "blue-network" spec.param.max_desired_latency_milliseconds: "10" spec.param.sample_duration_seconds: "5" spec.param.source_node: "worker1" spec.param.target_node: "worker2" status.succeeded: "true" status.failureReason: "" status.completionTimestamp: "2022-01-01T09:00:00Z" status.startTimestamp: "2022-01-01T09:00:07Z" status.result.avgLatencyNanoSec: "177000" status.result.maxLatencyNanoSec: "244000" 1 status.result.measurementDurationSec: "5" status.result.minLatencyNanoSec: "135000" status.result.sourceNode: "worker1" status.result.targetNode: "worker2" 1 The maximum measured latency in nanoseconds. Optional: To view the detailed job log in case of checkup failure, use the following command: USD oc logs job.batch/kubevirt-vm-latency-checkup -n <target_namespace> Delete the job and config map resources that you previously created by running the following commands: USD oc delete job -n <target_namespace> kubevirt-vm-latency-checkup USD oc delete config-map -n <target_namespace> kubevirt-vm-latency-checkup-config Optional: If you do not plan to run another checkup, delete the checkup role and framework manifest files. USD oc delete -f <file_name>.yaml 14.11.3. Additional resources Attaching a virtual machine to multiple networks 14.12. Prometheus queries for virtual resources OpenShift Virtualization provides metrics that you can use to monitor the consumption of cluster infrastructure resources, including vCPU, network, storage, and guest memory swapping. You can also use metrics to query live migration status. Use the OpenShift Container Platform monitoring dashboard to query virtualization metrics. 14.12.1. Prerequisites To use the vCPU metric, the schedstats=enable kernel argument must be applied to the MachineConfig object. This kernel argument enables scheduler statistics used for debugging and performance tuning and adds a minor additional load to the scheduler. See the OpenShift Container Platform machine configuration tasks documentation for more information on applying a kernel argument. For guest memory swapping queries to return data, memory swapping must be enabled on the virtual guests. 14.12.2. About querying metrics The OpenShift Container Platform monitoring dashboard enables you to run Prometheus Query Language (PromQL) queries to examine metrics visualized on a plot. This functionality provides information about the state of a cluster and any user-defined workloads that you are monitoring. As a cluster administrator , you can query metrics for all core OpenShift Container Platform and user-defined projects. As a developer , you must specify a project name when querying metrics. You must have the required privileges to view metrics for the selected project. 14.12.2.1. Querying metrics for all projects as a cluster administrator As a cluster administrator or as a user with view permissions for all projects, you can access metrics for all default OpenShift Container Platform and user-defined projects in the Metrics UI. Prerequisites You have access to the cluster as a user with the cluster-admin cluster role or with view permissions for all projects. You have installed the OpenShift CLI ( oc ). Procedure From the Administrator perspective of the OpenShift Container Platform web console, go to Observe Metrics . To add one or more queries, perform any of the following actions: Option Description Create a custom query. Add your Prometheus Query Language (PromQL) query to the Expression field. As you type a PromQL expression, autocomplete suggestions are displayed in a list. These suggestions include functions, metrics, labels, and time tokens. You can use the keyboard arrows to select one of these suggested items and then press Enter to add the item to your expression. You can also move your mouse pointer over a suggested item to view a brief description of that item. Add multiple queries. Click Add query . Duplicate an existing query. Click the Options menu to the query and select Duplicate query . Delete a query. Click the Options menu to the query and select Delete query . Disable a query from being run. Click the Options menu to the query and select Disable query . To run queries that you created, click Run queries . The metrics from the queries are visualized on the plot. If a query is invalid, the UI shows an error message. Note Queries that operate on large amounts of data might time out or overload the browser when drawing time series graphs. To avoid this, click Hide graph and calibrate your query by using the metrics table. After finding a feasible query, enable the plot to draw the graphs. Optional: The page URL now contains the queries you ran. To use this set of queries again in the future, save this URL. 14.12.2.2. Querying metrics for user-defined projects as a developer You can access metrics for a user-defined project as a developer or as a user with view permissions for the project. In the Developer perspective, the Metrics UI includes some predefined CPU, memory, bandwidth, and network packet queries for the selected project. You can also run custom Prometheus Query Language (PromQL) queries for CPU, memory, bandwidth, network packet and application metrics for the project. Note Developers can only use the Developer perspective and not the Administrator perspective. As a developer, you can only query metrics for one project at a time in the Observe --> Metrics page in the web console for your user-defined project. Prerequisites You have access to the cluster as a developer or as a user with view permissions for the project that you are viewing metrics for. You have enabled monitoring for user-defined projects. You have deployed a service in a user-defined project. You have created a ServiceMonitor custom resource definition (CRD) for the service to define how the service is monitored. Procedure Select the Developer perspective in the OpenShift Container Platform web console. Select Observe Metrics . Select the project that you want to view metrics for in the Project: list. Select a query from the Select query list, or create a custom PromQL query based on the selected query by selecting Show PromQL . Optional: Select Custom query from the Select query list to enter a new query. As you type, autocomplete suggestions appear in a drop-down list. These suggestions include functions and metrics. Click a suggested item to select it. Note In the Developer perspective, you can only run one query at a time. 14.12.3. Virtualization metrics The following metric descriptions include example Prometheus Query Language (PromQL) queries. These metrics are not an API and might change between versions. Note The following examples use topk queries that specify a time period. If virtual machines are deleted during that time period, they can still appear in the query output. 14.12.3.1. vCPU metrics The following query can identify virtual machines that are waiting for Input/Output (I/O): kubevirt_vmi_vcpu_wait_seconds Returns the wait time (in seconds) for a virtual machine's vCPU. Type: Counter. A value above '0' means that the vCPU wants to run, but the host scheduler cannot run it yet. This inability to run indicates that there is an issue with I/O. Note To query the vCPU metric, the schedstats=enable kernel argument must first be applied to the MachineConfig object. This kernel argument enables scheduler statistics used for debugging and performance tuning and adds a minor additional load to the scheduler. Example vCPU wait time query topk(3, sum by (name, namespace) (rate(kubevirt_vmi_vcpu_wait_seconds[6m]))) > 0 1 1 This query returns the top 3 VMs waiting for I/O at every given moment over a six-minute time period. 14.12.3.2. Network metrics The following queries can identify virtual machines that are saturating the network: kubevirt_vmi_network_receive_bytes_total Returns the total amount of traffic received (in bytes) on the virtual machine's network. Type: Counter. kubevirt_vmi_network_transmit_bytes_total Returns the total amount of traffic transmitted (in bytes) on the virtual machine's network. Type: Counter. Example network traffic query topk(3, sum by (name, namespace) (rate(kubevirt_vmi_network_receive_bytes_total[6m])) + sum by (name, namespace) (rate(kubevirt_vmi_network_transmit_bytes_total[6m]))) > 0 1 1 This query returns the top 3 VMs transmitting the most network traffic at every given moment over a six-minute time period. 14.12.3.3. Storage metrics 14.12.3.3.1. Storage-related traffic The following queries can identify VMs that are writing large amounts of data: kubevirt_vmi_storage_read_traffic_bytes_total Returns the total amount (in bytes) of the virtual machine's storage-related traffic. Type: Counter. kubevirt_vmi_storage_write_traffic_bytes_total Returns the total amount of storage writes (in bytes) of the virtual machine's storage-related traffic. Type: Counter. Example storage-related traffic query topk(3, sum by (name, namespace) (rate(kubevirt_vmi_storage_read_traffic_bytes_total[6m])) + sum by (name, namespace) (rate(kubevirt_vmi_storage_write_traffic_bytes_total[6m]))) > 0 1 1 This query returns the top 3 VMs performing the most storage traffic at every given moment over a six-minute time period. 14.12.3.3.2. Storage snapshot data kubevirt_vmsnapshot_disks_restored_from_source_total Returns the total number of virtual machine disks restored from the source virtual machine. Type: Gauge. kubevirt_vmsnapshot_disks_restored_from_source_bytes Returns the amount of space in bytes restored from the source virtual machine. Type: Gauge. Examples of storage snapshot data queries kubevirt_vmsnapshot_disks_restored_from_source_total{vm_name="simple-vm", vm_namespace="default"} 1 1 This query returns the total number of virtual machine disks restored from the source virtual machine. kubevirt_vmsnapshot_disks_restored_from_source_bytes{vm_name="simple-vm", vm_namespace="default"} 1 1 This query returns the amount of space in bytes restored from the source virtual machine. 14.12.3.3.3. I/O performance The following queries can determine the I/O performance of storage devices: kubevirt_vmi_storage_iops_read_total Returns the amount of write I/O operations the virtual machine is performing per second. Type: Counter. kubevirt_vmi_storage_iops_write_total Returns the amount of read I/O operations the virtual machine is performing per second. Type: Counter. Example I/O performance query topk(3, sum by (name, namespace) (rate(kubevirt_vmi_storage_iops_read_total[6m])) + sum by (name, namespace) (rate(kubevirt_vmi_storage_iops_write_total[6m]))) > 0 1 1 This query returns the top 3 VMs performing the most I/O operations per second at every given moment over a six-minute time period. 14.12.3.4. Guest memory swapping metrics The following queries can identify which swap-enabled guests are performing the most memory swapping: kubevirt_vmi_memory_swap_in_traffic_bytes_total Returns the total amount (in bytes) of memory the virtual guest is swapping in. Type: Gauge. kubevirt_vmi_memory_swap_out_traffic_bytes_total Returns the total amount (in bytes) of memory the virtual guest is swapping out. Type: Gauge. Example memory swapping query topk(3, sum by (name, namespace) (rate(kubevirt_vmi_memory_swap_in_traffic_bytes_total[6m])) + sum by (name, namespace) (rate(kubevirt_vmi_memory_swap_out_traffic_bytes_total[6m]))) > 0 1 1 This query returns the top 3 VMs where the guest is performing the most memory swapping at every given moment over a six-minute time period. Note Memory swapping indicates that the virtual machine is under memory pressure. Increasing the memory allocation of the virtual machine can mitigate this issue. 14.12.4. Live migration metrics The following metrics can be queried to show live migration status: kubevirt_migrate_vmi_data_processed_bytes The amount of guest operating system (OS) data that has migrated to the new virtual machine (VM). Type: Gauge. kubevirt_migrate_vmi_data_remaining_bytes The amount of guest OS data that remains to be migrated. Type: Gauge. kubevirt_migrate_vmi_dirty_memory_rate_bytes The rate at which memory is becoming dirty in the guest OS. Dirty memory is data that has been changed but not yet written to disk. Type: Gauge. kubevirt_migrate_vmi_pending_count The number of pending migrations. Type: Gauge. kubevirt_migrate_vmi_scheduling_count The number of scheduling migrations. Type: Gauge. kubevirt_migrate_vmi_running_count The number of running migrations. Type: Gauge. kubevirt_migrate_vmi_succeeded The number of successfully completed migrations. Type: Gauge. kubevirt_migrate_vmi_failed The number of failed migrations. Type: Gauge. 14.12.5. Additional resources Monitoring overview Querying Prometheus Prometheus query examples 14.13. Exposing custom metrics for virtual machines OpenShift Container Platform includes a preconfigured, preinstalled, and self-updating monitoring stack that provides monitoring for core platform components. This monitoring stack is based on the Prometheus monitoring system. Prometheus is a time-series database and a rule evaluation engine for metrics. In addition to using the OpenShift Container Platform monitoring stack, you can enable monitoring for user-defined projects by using the CLI and query custom metrics that are exposed for virtual machines through the node-exporter service. 14.13.1. Configuring the node exporter service The node-exporter agent is deployed on every virtual machine in the cluster from which you want to collect metrics. Configure the node-exporter agent as a service to expose internal metrics and processes that are associated with virtual machines. Prerequisites Install the OpenShift Container Platform CLI oc . Log in to the cluster as a user with cluster-admin privileges. Create the cluster-monitoring-config ConfigMap object in the openshift-monitoring project. Configure the user-workload-monitoring-config ConfigMap object in the openshift-user-workload-monitoring project by setting enableUserWorkload to true . Procedure Create the Service YAML file. In the following example, the file is called node-exporter-service.yaml . kind: Service apiVersion: v1 metadata: name: node-exporter-service 1 namespace: dynamation 2 labels: servicetype: metrics 3 spec: ports: - name: exmet 4 protocol: TCP port: 9100 5 targetPort: 9100 6 type: ClusterIP selector: monitor: metrics 7 1 The node-exporter service that exposes the metrics from the virtual machines. 2 The namespace where the service is created. 3 The label for the service. The ServiceMonitor uses this label to match this service. 4 The name given to the port that exposes metrics on port 9100 for the ClusterIP service. 5 The target port used by node-exporter-service to listen for requests. 6 The TCP port number of the virtual machine that is configured with the monitor label. 7 The label used to match the virtual machine's pods. In this example, any virtual machine's pod with the label monitor and a value of metrics will be matched. Create the node-exporter service: USD oc create -f node-exporter-service.yaml 14.13.2. Configuring a virtual machine with the node exporter service Download the node-exporter file on to the virtual machine. Then, create a systemd service that runs the node-exporter service when the virtual machine boots. Prerequisites The pods for the component are running in the openshift-user-workload-monitoring project. Grant the monitoring-edit role to users who need to monitor this user-defined project. Procedure Log on to the virtual machine. Download the node-exporter file on to the virtual machine by using the directory path that applies to the version of node-exporter file. USD wget https://github.com/prometheus/node_exporter/releases/download/v1.3.1/node_exporter-1.3.1.linux-amd64.tar.gz Extract the executable and place it in the /usr/bin directory. USD sudo tar xvf node_exporter-1.3.1.linux-amd64.tar.gz \ --directory /usr/bin --strip 1 "*/node_exporter" Create a node_exporter.service file in this directory path: /etc/systemd/system . This systemd service file runs the node-exporter service when the virtual machine reboots. [Unit] Description=Prometheus Metrics Exporter After=network.target StartLimitIntervalSec=0 [Service] Type=simple Restart=always RestartSec=1 User=root ExecStart=/usr/bin/node_exporter [Install] WantedBy=multi-user.target Enable and start the systemd service. USD sudo systemctl enable node_exporter.service USD sudo systemctl start node_exporter.service Verification Verify that the node-exporter agent is reporting metrics from the virtual machine. USD curl http://localhost:9100/metrics Example output go_gc_duration_seconds{quantile="0"} 1.5244e-05 go_gc_duration_seconds{quantile="0.25"} 3.0449e-05 go_gc_duration_seconds{quantile="0.5"} 3.7913e-05 14.13.3. Creating a custom monitoring label for virtual machines To enable queries to multiple virtual machines from a single service, add a custom label in the virtual machine's YAML file. Prerequisites Install the OpenShift Container Platform CLI oc . Log in as a user with cluster-admin privileges. Access to the web console for stop and restart a virtual machine. Procedure Edit the template spec of your virtual machine configuration file. In this example, the label monitor has the value metrics . spec: template: metadata: labels: monitor: metrics Stop and restart the virtual machine to create a new pod with the label name given to the monitor label. 14.13.3.1. Querying the node-exporter service for metrics Metrics are exposed for virtual machines through an HTTP service endpoint under the /metrics canonical name. When you query for metrics, Prometheus directly scrapes the metrics from the metrics endpoint exposed by the virtual machines and presents these metrics for viewing. Prerequisites You have access to the cluster as a user with cluster-admin privileges or the monitoring-edit role. You have enabled monitoring for the user-defined project by configuring the node-exporter service. Procedure Obtain the HTTP service endpoint by specifying the namespace for the service: USD oc get service -n <namespace> <node-exporter-service> To list all available metrics for the node-exporter service, query the metrics resource. USD curl http://<172.30.226.162:9100>/metrics | grep -vE "^#|^USD" Example output node_arp_entries{device="eth0"} 1 node_boot_time_seconds 1.643153218e+09 node_context_switches_total 4.4938158e+07 node_cooling_device_cur_state{name="0",type="Processor"} 0 node_cooling_device_max_state{name="0",type="Processor"} 0 node_cpu_guest_seconds_total{cpu="0",mode="nice"} 0 node_cpu_guest_seconds_total{cpu="0",mode="user"} 0 node_cpu_seconds_total{cpu="0",mode="idle"} 1.10586485e+06 node_cpu_seconds_total{cpu="0",mode="iowait"} 37.61 node_cpu_seconds_total{cpu="0",mode="irq"} 233.91 node_cpu_seconds_total{cpu="0",mode="nice"} 551.47 node_cpu_seconds_total{cpu="0",mode="softirq"} 87.3 node_cpu_seconds_total{cpu="0",mode="steal"} 86.12 node_cpu_seconds_total{cpu="0",mode="system"} 464.15 node_cpu_seconds_total{cpu="0",mode="user"} 1075.2 node_disk_discard_time_seconds_total{device="vda"} 0 node_disk_discard_time_seconds_total{device="vdb"} 0 node_disk_discarded_sectors_total{device="vda"} 0 node_disk_discarded_sectors_total{device="vdb"} 0 node_disk_discards_completed_total{device="vda"} 0 node_disk_discards_completed_total{device="vdb"} 0 node_disk_discards_merged_total{device="vda"} 0 node_disk_discards_merged_total{device="vdb"} 0 node_disk_info{device="vda",major="252",minor="0"} 1 node_disk_info{device="vdb",major="252",minor="16"} 1 node_disk_io_now{device="vda"} 0 node_disk_io_now{device="vdb"} 0 node_disk_io_time_seconds_total{device="vda"} 174 node_disk_io_time_seconds_total{device="vdb"} 0.054 node_disk_io_time_weighted_seconds_total{device="vda"} 259.79200000000003 node_disk_io_time_weighted_seconds_total{device="vdb"} 0.039 node_disk_read_bytes_total{device="vda"} 3.71867136e+08 node_disk_read_bytes_total{device="vdb"} 366592 node_disk_read_time_seconds_total{device="vda"} 19.128 node_disk_read_time_seconds_total{device="vdb"} 0.039 node_disk_reads_completed_total{device="vda"} 5619 node_disk_reads_completed_total{device="vdb"} 96 node_disk_reads_merged_total{device="vda"} 5 node_disk_reads_merged_total{device="vdb"} 0 node_disk_write_time_seconds_total{device="vda"} 240.66400000000002 node_disk_write_time_seconds_total{device="vdb"} 0 node_disk_writes_completed_total{device="vda"} 71584 node_disk_writes_completed_total{device="vdb"} 0 node_disk_writes_merged_total{device="vda"} 19761 node_disk_writes_merged_total{device="vdb"} 0 node_disk_written_bytes_total{device="vda"} 2.007924224e+09 node_disk_written_bytes_total{device="vdb"} 0 14.13.4. Creating a ServiceMonitor resource for the node exporter service You can use a Prometheus client library and scrape metrics from the /metrics endpoint to access and view the metrics exposed by the node-exporter service. Use a ServiceMonitor custom resource definition (CRD) to monitor the node exporter service. Prerequisites You have access to the cluster as a user with cluster-admin privileges or the monitoring-edit role. You have enabled monitoring for the user-defined project by configuring the node-exporter service. Procedure Create a YAML file for the ServiceMonitor resource configuration. In this example, the service monitor matches any service with the label metrics and queries the exmet port every 30 seconds. apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: labels: k8s-app: node-exporter-metrics-monitor name: node-exporter-metrics-monitor 1 namespace: dynamation 2 spec: endpoints: - interval: 30s 3 port: exmet 4 scheme: http selector: matchLabels: servicetype: metrics 1 The name of the ServiceMonitor . 2 The namespace where the ServiceMonitor is created. 3 The interval at which the port will be queried. 4 The name of the port that is queried every 30 seconds Create the ServiceMonitor configuration for the node-exporter service. USD oc create -f node-exporter-metrics-monitor.yaml 14.13.4.1. Accessing the node exporter service outside the cluster You can access the node-exporter service outside the cluster and view the exposed metrics. Prerequisites You have access to the cluster as a user with cluster-admin privileges or the monitoring-edit role. You have enabled monitoring for the user-defined project by configuring the node-exporter service. Procedure Expose the node-exporter service. USD oc expose service -n <namespace> <node_exporter_service_name> Obtain the FQDN (Fully Qualified Domain Name) for the route. USD oc get route -o=custom-columns=NAME:.metadata.name,DNS:.spec.host Example output NAME DNS node-exporter-service node-exporter-service-dynamation.apps.cluster.example.org Use the curl command to display metrics for the node-exporter service. USD curl -s http://node-exporter-service-dynamation.apps.cluster.example.org/metrics Example output go_gc_duration_seconds{quantile="0"} 1.5382e-05 go_gc_duration_seconds{quantile="0.25"} 3.1163e-05 go_gc_duration_seconds{quantile="0.5"} 3.8546e-05 go_gc_duration_seconds{quantile="0.75"} 4.9139e-05 go_gc_duration_seconds{quantile="1"} 0.000189423 14.13.5. Additional resources Configuring the monitoring stack Enabling monitoring for user-defined projects Managing metrics Reviewing monitoring dashboards Monitoring application health by using health checks Creating and using config maps Controlling virtual machine states 14.14. OpenShift Virtualization runbooks Runbooks for the OpenShift Virtualization Operator are maintained in the openshift/runbooks Git repository, and you can view them on GitHub. To diagnose and resolve issues that trigger OpenShift Virtualization alerts , follow the procedures in the runbooks. OpenShift Virtualization alerts are displayed in the Virtualization Overview tab in the web console. 14.14.1. CDIDataImportCronOutdated View the runbook for the CDIDataImportCronOutdated alert. 14.14.2. CDIDataVolumeUnusualRestartCount View the runbook for the CDIDataVolumeUnusualRestartCount alert. 14.14.3. CDIDefaultStorageClassDegraded View the runbook for the CDIDefaultStorageClassDegraded alert. 14.14.4. CDIMultipleDefaultVirtStorageClasses View the runbook for the CDIMultipleDefaultVirtStorageClasses alert. 14.14.5. CDINoDefaultStorageClass View the runbook for the CDINoDefaultStorageClass alert. 14.14.6. CDINotReady View the runbook for the CDINotReady alert. 14.14.7. CDIOperatorDown View the runbook for the CDIOperatorDown alert. 14.14.8. CDIStorageProfilesIncomplete View the runbook for the CDIStorageProfilesIncomplete alert. 14.14.9. CnaoDown View the runbook for the CnaoDown alert. 14.14.10. CnaoNMstateMigration View the runbook for the CnaoNMstateMigration alert. 14.14.11. HCOInstallationIncomplete View the runbook for the HCOInstallationIncomplete alert. 14.14.12. HPPNotReady View the runbook for the HPPNotReady alert. 14.14.13. HPPOperatorDown View the runbook for the HPPOperatorDown alert. 14.14.14. HPPSharingPoolPathWithOS View the runbook for the HPPSharingPoolPathWithOS alert. 14.14.15. KubemacpoolDown View the runbook for the KubemacpoolDown alert. 14.14.16. KubeMacPoolDuplicateMacsFound View the runbook for the KubeMacPoolDuplicateMacsFound alert. 14.14.17. KubeVirtComponentExceedsRequestedCPU The KubeVirtComponentExceedsRequestedCPU alert is deprecated . 14.14.18. KubeVirtComponentExceedsRequestedMemory The KubeVirtComponentExceedsRequestedMemory alert is deprecated . 14.14.19. KubeVirtCRModified View the runbook for the KubeVirtCRModified alert. 14.14.20. KubeVirtDeprecatedAPIRequested View the runbook for the KubeVirtDeprecatedAPIRequested alert. 14.14.21. KubeVirtNoAvailableNodesToRunVMs View the runbook for the KubeVirtNoAvailableNodesToRunVMs alert. 14.14.22. KubevirtVmHighMemoryUsage View the runbook for the KubevirtVmHighMemoryUsage alert. 14.14.23. KubeVirtVMIExcessiveMigrations View the runbook for the KubeVirtVMIExcessiveMigrations alert. 14.14.24. LowKVMNodesCount View the runbook for the LowKVMNodesCount alert. 14.14.25. LowReadyVirtControllersCount View the runbook for the LowReadyVirtControllersCount alert. 14.14.26. LowReadyVirtOperatorsCount View the runbook for the LowReadyVirtOperatorsCount alert. 14.14.27. LowVirtAPICount View the runbook for the LowVirtAPICount alert. 14.14.28. LowVirtControllersCount View the runbook for the LowVirtControllersCount alert. 14.14.29. LowVirtOperatorCount View the runbook for the LowVirtOperatorCount alert. 14.14.30. NetworkAddonsConfigNotReady View the runbook for the NetworkAddonsConfigNotReady alert. 14.14.31. NoLeadingVirtOperator View the runbook for the NoLeadingVirtOperator alert. 14.14.32. NoReadyVirtController View the runbook for the NoReadyVirtController alert. 14.14.33. NoReadyVirtOperator View the runbook for the NoReadyVirtOperator alert. 14.14.34. OrphanedVirtualMachineInstances View the runbook for the OrphanedVirtualMachineInstances alert. 14.14.35. OutdatedVirtualMachineInstanceWorkloads View the runbook for the OutdatedVirtualMachineInstanceWorkloads alert. 14.14.36. SingleStackIPv6Unsupported View the runbook for the SingleStackIPv6Unsupported alert. 14.14.37. SSPCommonTemplatesModificationReverted View the runbook for the SSPCommonTemplatesModificationReverted alert. 14.14.38. SSPDown View the runbook for the SSPDown alert. 14.14.39. SSPFailingToReconcile View the runbook for the SSPFailingToReconcile alert. 14.14.40. SSPHighRateRejectedVms View the runbook for the SSPHighRateRejectedVms alert. 14.14.41. SSPTemplateValidatorDown View the runbook for the SSPTemplateValidatorDown alert. 14.14.42. UnsupportedHCOModification View the runbook for the UnsupportedHCOModification alert. 14.14.43. VirtAPIDown View the runbook for the VirtAPIDown alert. 14.14.44. VirtApiRESTErrorsBurst View the runbook for the VirtApiRESTErrorsBurst alert. 14.14.45. VirtApiRESTErrorsHigh View the runbook for the VirtApiRESTErrorsHigh alert. 14.14.46. VirtControllerDown View the runbook for the VirtControllerDown alert. 14.14.47. VirtControllerRESTErrorsBurst View the runbook for the VirtControllerRESTErrorsBurst alert. 14.14.48. VirtControllerRESTErrorsHigh View the runbook for the VirtControllerRESTErrorsHigh alert. 14.14.49. VirtHandlerDaemonSetRolloutFailing View the runbook for the VirtHandlerDaemonSetRolloutFailing alert. 14.14.50. VirtHandlerRESTErrorsBurst View the runbook for the VirtHandlerRESTErrorsBurst alert. 14.14.51. VirtHandlerRESTErrorsHigh View the runbook for the VirtHandlerRESTErrorsHigh alert. 14.14.52. VirtOperatorDown View the runbook for the VirtOperatorDown alert. 14.14.53. VirtOperatorRESTErrorsBurst View the runbook for the VirtOperatorRESTErrorsBurst alert. 14.14.54. VirtOperatorRESTErrorsHigh View the runbook for the VirtOperatorRESTErrorsHigh alert. 14.14.55. VirtualMachineCRCErrors The runbook for the VirtualMachineCRCErrors alert is deprecated because the alert was renamed to VMStorageClassWarning . View the runbook for the VMStorageClassWarning alert. 14.14.56. VMCannotBeEvicted View the runbook for the VMCannotBeEvicted alert. 14.14.57. VMStorageClassWarning View the runbook for the VMStorageClassWarning alert. 14.15. Collecting data for Red Hat Support When you submit a support case to Red Hat Support, it is helpful to provide debugging information for OpenShift Container Platform and OpenShift Virtualization by using the following tools: must-gather tool The must-gather tool collects diagnostic information, including resource definitions and service logs. Prometheus Prometheus is a time-series database and a rule evaluation engine for metrics. Prometheus sends alerts to Alertmanager for processing. Alertmanager The Alertmanager service handles alerts received from Prometheus. The Alertmanager is also responsible for sending the alerts to external notification systems. 14.15.1. Collecting data about your environment Collecting data about your environment minimizes the time required to analyze and determine the root cause. Prerequisites Set the retention time for Prometheus metrics data to a minimum of seven days. Configure the Alertmanager to capture relevant alerts and to send them to a dedicated mailbox so that they can be viewed and persisted outside the cluster. Record the exact number of affected nodes and virtual machines. Procedure Collect must-gather data for the cluster by using the default must-gather image. Collect must-gather data for Red Hat OpenShift Data Foundation, if necessary. Collect must-gather data for OpenShift Virtualization by using the OpenShift Virtualization must-gather image. Collect Prometheus metrics for the cluster. 14.15.1.1. Additional resources Configuring the retention time for Prometheus metrics data Configuring the Alertmanager to send alert notifications to external systems Collecting must-gather data for OpenShift Container Platform Collecting must-gather data for Red Hat OpenShift Data Foundation Collecting must-gather data for OpenShift Virtualization Collecting Prometheus metrics for all projects as a cluster administrator 14.15.2. Collecting data about virtual machines Collecting data about malfunctioning virtual machines (VMs) minimizes the time required to analyze and determine the root cause. Prerequisites Windows VMs: Record the Windows patch update details for Red Hat Support. Install the latest version of the VirtIO drivers. The VirtIO drivers include the QEMU guest agent. If Remote Desktop Protocol (RDP) is enabled, try to connect to the VMs with RDP to determine whether there is a problem with the connection software. Procedure Collect detailed must-gather data about the malfunctioning VMs. Collect screenshots of VMs that have crashed before you restart them. Record factors that the malfunctioning VMs have in common. For example, the VMs have the same host or network. 14.15.2.1. Additional resources Installing VirtIO drivers on Windows VMs Downloading and installing VirtIO drivers on Windows VMs without host access Connecting to Windows VMs with RDP using the web console or the command line Collecting must-gather data about virtual machines 14.15.3. Using the must-gather tool for OpenShift Virtualization You can collect data about OpenShift Virtualization resources by running the must-gather command with the OpenShift Virtualization image. The default data collection includes information about the following resources: OpenShift Virtualization Operator namespaces, including child objects OpenShift Virtualization custom resource definitions Namespaces that contain virtual machines Basic virtual machine definitions Procedure Run the following command to collect data about OpenShift Virtualization: USD oc adm must-gather --image-stream=openshift/must-gather \ --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.12.16 14.15.3.1. must-gather tool options You can specify a combination of scripts and environment variables for the following options: Collecting detailed virtual machine (VM) information from a namespace Collecting detailed information about specified VMs Collecting image, image-stream, and image-stream-tags information Limiting the maximum number of parallel processes used by the must-gather tool 14.15.3.1.1. Parameters Environment variables You can specify environment variables for a compatible script. NS=<namespace_name> Collect virtual machine information, including virt-launcher pod details, from the namespace that you specify. The VirtualMachine and VirtualMachineInstance CR data is collected for all namespaces. VM=<vm_name> Collect details about a particular virtual machine. To use this option, you must also specify a namespace by using the NS environment variable. PROS=<number_of_processes> Modify the maximum number of parallel processes that the must-gather tool uses. The default value is 5 . Important Using too many parallel processes can cause performance issues. Increasing the maximum number of parallel processes is not recommended. Scripts Each script is compatible only with certain environment variable combinations. /usr/bin/gather Use the default must-gather script, which collects cluster data from all namespaces and includes only basic VM information. This script is compatible only with the PROS variable. /usr/bin/gather --vms_details Collect VM log files, VM definitions, control-plane logs, and namespaces that belong to OpenShift Virtualization resources. Specifying namespaces includes their child objects. If you use this parameter without specifying a namespace or VM, the must-gather tool collects this data for all VMs in the cluster. This script is compatible with all environment variables, but you must specify a namespace if you use the VM variable. /usr/bin/gather --images Collect image, image-stream, and image-stream-tags custom resource information. This script is compatible only with the PROS variable. 14.15.3.1.2. Usage and examples Environment variables are optional. You can run a script by itself or with one or more compatible environment variables. Table 14.1. Compatible parameters Script Compatible environment variable /usr/bin/gather PROS=<number_of_processes> /usr/bin/gather --vms_details For a namespace: NS=<namespace_name> For a VM: VM=<vm_name> NS=<namespace_name> PROS=<number_of_processes> /usr/bin/gather --images PROS=<number_of_processes> Syntax USD oc adm must-gather \ --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.12.16 \ -- <environment_variable_1> <environment_variable_2> <script_name> Default data collection parallel processes By default, five processes run in parallel. USD oc adm must-gather \ --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.12.16 \ -- PROS=5 /usr/bin/gather 1 1 You can modify the number of parallel processes by changing the default. Detailed VM information The following command collects detailed VM information for the my-vm VM in the mynamespace namespace: USD oc adm must-gather \ --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.12.16 \ -- NS=mynamespace VM=my-vm /usr/bin/gather --vms_details 1 1 The NS environment variable is mandatory if you use the VM environment variable. Image, image-stream, and image-stream-tags information The following command collects image, image-stream, and image-stream-tags information from the cluster: USD oc adm must-gather \ --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.12.16 \ -- /usr/bin/gather --images 14.15.3.2. Additional resources About the must-gather tool

Commands:
oc edit hyperconverged kubevirt-hyperconverged -n openshift-cnv
apiVersion: hco.kubevirt.io/v1beta1 kind: HyperConverged metadata: name: kubevirt-hyperconverged spec: logVerbosityConfig: kubevirt: virtAPI: 5 1 virtController: 4 virtHandler: 3 virtLauncher: 2 virtOperator: 6
oc get pods -n openshift-cnv
NAME READY STATUS RESTARTS AGE disks-images-provider-7gqbc 1/1 Running 0 32m disks-images-provider-vg4kx 1/1 Running 0 32m virt-api-57fcc4497b-7qfmc 1/1 Running 0 31m virt-api-57fcc4497b-tx9nc 1/1 Running 0 31m virt-controller-76c784655f-7fp6m 1/1 Running 0 30m virt-controller-76c784655f-f4pbd 1/1 Running 0 30m virt-handler-2m86x 1/1 Running 0 30m virt-handler-9qs6z 1/1 Running 0 30m virt-operator-7ccfdbf65f-q5snk 1/1 Running 0 32m virt-operator-7ccfdbf65f-vllz8 1/1 Running 0 32m
oc logs -n openshift-cnv <pod_name>
oc logs -n openshift-cnv virt-handler-2m86x
{"component":"virt-handler","level":"info","msg":"set verbosity to 2","pos":"virt-handler.go:453","timestamp":"2022-04-17T08:58:37.373695Z"} {"component":"virt-handler","level":"info","msg":"set verbosity to 2","pos":"virt-handler.go:453","timestamp":"2022-04-17T08:58:37.373726Z"} {"component":"virt-handler","level":"info","msg":"setting rate limiter to 5 QPS and 10 Burst","pos":"virt-handler.go:462","timestamp":"2022-04-17T08:58:37.373782Z"} {"component":"virt-handler","level":"info","msg":"CPU features of a minimum baseline CPU model: map[apic:true clflush:true cmov:true cx16:true cx8:true de:true fpu:true fxsr:true lahf_lm:true lm:true mca:true mce:true mmx:true msr:true mtrr:true nx:true pae:true pat:true pge:true pni:true pse:true pse36:true sep:true sse:true sse2:true sse4.1:true ssse3:true syscall:true tsc:true]","pos":"cpu_plugin.go:96","timestamp":"2022-04-17T08:58:37.390221Z"} {"component":"virt-handler","level":"warning","msg":"host model mode is expected to contain only one model","pos":"cpu_plugin.go:103","timestamp":"2022-04-17T08:58:37.390263Z"} {"component":"virt-handler","level":"info","msg":"node-labeller is running","pos":"node_labeller.go:94","timestamp":"2022-04-17T08:58:37.391011Z"}
oc get events
oc describe vm <vm>
oc describe vmi <vmi>
oc describe pod virt-launcher-<name>
oc describe vmi vmi-fedora
Status: Conditions: Last Probe Time: <nil> Last Transition Time: <nil> Status: True Type: LiveMigratable Migration Method: LiveMigration Migration State: Completed: true End Timestamp: 2018-12-24T06:19:42Z Migration UID: d78c8962-0743-11e9-a540-fa163e0c69f1 Source Node: node2.example.com Start Timestamp: 2018-12-24T06:19:35Z Target Node: node1.example.com Target Node Address: 10.9.0.18:43891 Target Node Domain Detected: true
oc describe dv <DataVolume>
Status: Conditions: Last Heart Beat Time: 2020-07-15T03:58:24Z Last Transition Time: 2020-07-15T03:58:24Z Message: PVC win10-rootdisk Bound Reason: Bound Status: True Type: Bound Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal Bound 24s datavolume-controller PVC example-dv Bound
Status: Conditions: Last Heart Beat Time: 2020-07-15T04:31:39Z Last Transition Time: 2020-07-15T04:31:39Z Message: Import Complete Reason: Completed Status: False Type: Running Events: Type Reason Age From Message ---- ------ ---- ---- ------- Warning Error 12s (x2 over 14s) datavolume-controller Unable to connect to http data source: expected status code 200, got 404. Status: 404 Not Found
Status: Conditions: Last Heart Beat Time: 2020-07-15T04:31:39Z Last Transition Time: 2020-07-15T04:31:39Z Status: True Type: Ready
spec: readinessProbe: httpGet: 1 port: 1500 2 path: /healthz 3 httpHeaders: - name: Custom-Header value: Awesome initialDelaySeconds: 120 4 periodSeconds: 20 5 timeoutSeconds: 10 6 failureThreshold: 3 7 successThreshold: 3 8
oc create -f <file_name>.yaml
spec: readinessProbe: initialDelaySeconds: 120 1 periodSeconds: 20 2 tcpSocket: 3 port: 1500 4 timeoutSeconds: 10 5
oc create -f <file_name>.yaml
spec: livenessProbe: initialDelaySeconds: 120 1 periodSeconds: 20 2 httpGet: 3 port: 1500 4 path: /healthz 5 httpHeaders: - name: Custom-Header value: Awesome timeoutSeconds: 10 6
oc create -f <file_name>.yaml
spec: readinessProbe: guestAgentPing: {} 1 initialDelaySeconds: 120 2 periodSeconds: 20 3 timeoutSeconds: 10 4 failureThreshold: 3 5 successThreshold: 3 6
oc create -f <file_name>.yaml
apiVersion: kubevirt.io/v1 kind: VirtualMachine metadata: labels: special: vm-fedora name: vm-fedora spec: template: metadata: labels: special: vm-fedora spec: domain: devices: disks: - disk: bus: virtio name: containerdisk - disk: bus: virtio name: cloudinitdisk resources: requests: memory: 1024M readinessProbe: httpGet: port: 1500 initialDelaySeconds: 120 periodSeconds: 20 timeoutSeconds: 10 failureThreshold: 3 successThreshold: 3 terminationGracePeriodSeconds: 180 volumes: - name: containerdisk containerDisk: image: kubevirt/fedora-cloud-registry-disk-demo - cloudInitNoCloud: userData: |- #cloud-config password: fedora chpasswd: { expire: False } bootcmd: - setenforce 0 - dnf install -y nmap-ncat - systemd-run --unit=httpserver nc -klp 1500 -e '/usr/bin/echo -e HTTP/1.1 200 OK\\n\\nHello World!' name: cloudinitdisk
--- apiVersion: v1 kind: ServiceAccount metadata: name: vm-latency-checkup-sa --- apiVersion: rbac.authorization.k8s.io/v1 kind: Role metadata: name: kubevirt-vm-latency-checker rules: - apiGroups: ["kubevirt.io"] resources: ["virtualmachineinstances"] verbs: ["get", "create", "delete"] - apiGroups: ["subresources.kubevirt.io"] resources: ["virtualmachineinstances/console"] verbs: ["get"] - apiGroups: ["k8s.cni.cncf.io"] resources: ["network-attachment-definitions"] verbs: ["get"] --- apiVersion: rbac.authorization.k8s.io/v1 kind: RoleBinding metadata: name: kubevirt-vm-latency-checker subjects: - kind: ServiceAccount name: vm-latency-checkup-sa roleRef: kind: Role name: kubevirt-vm-latency-checker apiGroup: rbac.authorization.k8s.io --- apiVersion: rbac.authorization.k8s.io/v1 kind: Role metadata: name: kiagnose-configmap-access rules: - apiGroups: [ "" ] resources: [ "configmaps" ] verbs: ["get", "update"] --- apiVersion: rbac.authorization.k8s.io/v1 kind: RoleBinding metadata: name: kiagnose-configmap-access subjects: - kind: ServiceAccount name: vm-latency-checkup-sa roleRef: kind: Role name: kiagnose-configmap-access apiGroup: rbac.authorization.k8s.io
oc apply -n <target_namespace> -f <latency_roles>.yaml 1
apiVersion: v1 kind: ConfigMap metadata: name: kubevirt-vm-latency-checkup-config data: spec.timeout: 5m spec.param.network_attachment_definition_namespace: <target_namespace> spec.param.network_attachment_definition_name: "blue-network" 1 spec.param.max_desired_latency_milliseconds: "10" 2 spec.param.sample_duration_seconds: "5" 3 spec.param.source_node: "worker1" 4 spec.param.target_node: "worker2" 5
oc apply -n <target_namespace> -f <latency_config_map>.yaml
apiVersion: batch/v1 kind: Job metadata: name: kubevirt-vm-latency-checkup spec: backoffLimit: 0 template: spec: serviceAccountName: vm-latency-checkup-sa restartPolicy: Never containers: - name: vm-latency-checkup image: registry.redhat.io/container-native-virtualization/vm-network-latency-checkup:v4.12.0 securityContext: allowPrivilegeEscalation: false capabilities: drop: ["ALL"] runAsNonRoot: true seccompProfile: type: "RuntimeDefault" env: - name: CONFIGMAP_NAMESPACE value: <target_namespace> - name: CONFIGMAP_NAME value: kubevirt-vm-latency-checkup-config
oc apply -n <target_namespace> -f <latency_job>.yaml
oc wait job kubevirt-vm-latency-checkup -n <target_namespace> --for condition=complete --timeout 6m
oc get configmap kubevirt-vm-latency-checkup-config -n <target_namespace> -o yaml
apiVersion: v1 kind: ConfigMap metadata: name: kubevirt-vm-latency-checkup-config namespace: <target_namespace> data: spec.timeout: 5m spec.param.network_attachment_definition_namespace: <target_namespace> spec.param.network_attachment_definition_name: "blue-network" spec.param.max_desired_latency_milliseconds: "10" spec.param.sample_duration_seconds: "5" spec.param.source_node: "worker1" spec.param.target_node: "worker2" status.succeeded: "true" status.failureReason: "" status.completionTimestamp: "2022-01-01T09:00:00Z" status.startTimestamp: "2022-01-01T09:00:07Z" status.result.avgLatencyNanoSec: "177000" status.result.maxLatencyNanoSec: "244000" 1 status.result.measurementDurationSec: "5" status.result.minLatencyNanoSec: "135000" status.result.sourceNode: "worker1" status.result.targetNode: "worker2"
oc logs job.batch/kubevirt-vm-latency-checkup -n <target_namespace>
oc delete job -n <target_namespace> kubevirt-vm-latency-checkup
oc delete config-map -n <target_namespace> kubevirt-vm-latency-checkup-config
oc delete -f <file_name>.yaml
topk(3, sum by (name, namespace) (rate(kubevirt_vmi_vcpu_wait_seconds[6m]))) > 0 1
topk(3, sum by (name, namespace) (rate(kubevirt_vmi_network_receive_bytes_total[6m])) + sum by (name, namespace) (rate(kubevirt_vmi_network_transmit_bytes_total[6m]))) > 0 1
topk(3, sum by (name, namespace) (rate(kubevirt_vmi_storage_read_traffic_bytes_total[6m])) + sum by (name, namespace) (rate(kubevirt_vmi_storage_write_traffic_bytes_total[6m]))) > 0 1
kubevirt_vmsnapshot_disks_restored_from_source_total{vm_name="simple-vm", vm_namespace="default"} 1
kubevirt_vmsnapshot_disks_restored_from_source_bytes{vm_name="simple-vm", vm_namespace="default"} 1
topk(3, sum by (name, namespace) (rate(kubevirt_vmi_storage_iops_read_total[6m])) + sum by (name, namespace) (rate(kubevirt_vmi_storage_iops_write_total[6m]))) > 0 1
topk(3, sum by (name, namespace) (rate(kubevirt_vmi_memory_swap_in_traffic_bytes_total[6m])) + sum by (name, namespace) (rate(kubevirt_vmi_memory_swap_out_traffic_bytes_total[6m]))) > 0 1
kind: Service apiVersion: v1 metadata: name: node-exporter-service 1 namespace: dynamation 2 labels: servicetype: metrics 3 spec: ports: - name: exmet 4 protocol: TCP port: 9100 5 targetPort: 9100 6 type: ClusterIP selector: monitor: metrics 7
oc create -f node-exporter-service.yaml
wget https://github.com/prometheus/node_exporter/releases/download/v1.3.1/node_exporter-1.3.1.linux-amd64.tar.gz
sudo tar xvf node_exporter-1.3.1.linux-amd64.tar.gz --directory /usr/bin --strip 1 "*/node_exporter"
[Unit] Description=Prometheus Metrics Exporter After=network.target StartLimitIntervalSec=0 [Service] Type=simple Restart=always RestartSec=1 User=root ExecStart=/usr/bin/node_exporter [Install] WantedBy=multi-user.target
sudo systemctl enable node_exporter.service sudo systemctl start node_exporter.service
curl http://localhost:9100/metrics
go_gc_duration_seconds{quantile="0"} 1.5244e-05 go_gc_duration_seconds{quantile="0.25"} 3.0449e-05 go_gc_duration_seconds{quantile="0.5"} 3.7913e-05
spec: template: metadata: labels: monitor: metrics
oc get service -n <namespace> <node-exporter-service>
curl http://<172.30.226.162:9100>/metrics | grep -vE "^#|^USD"
node_arp_entries{device="eth0"} 1 node_boot_time_seconds 1.643153218e+09 node_context_switches_total 4.4938158e+07 node_cooling_device_cur_state{name="0",type="Processor"} 0 node_cooling_device_max_state{name="0",type="Processor"} 0 node_cpu_guest_seconds_total{cpu="0",mode="nice"} 0 node_cpu_guest_seconds_total{cpu="0",mode="user"} 0 node_cpu_seconds_total{cpu="0",mode="idle"} 1.10586485e+06 node_cpu_seconds_total{cpu="0",mode="iowait"} 37.61 node_cpu_seconds_total{cpu="0",mode="irq"} 233.91 node_cpu_seconds_total{cpu="0",mode="nice"} 551.47 node_cpu_seconds_total{cpu="0",mode="softirq"} 87.3 node_cpu_seconds_total{cpu="0",mode="steal"} 86.12 node_cpu_seconds_total{cpu="0",mode="system"} 464.15 node_cpu_seconds_total{cpu="0",mode="user"} 1075.2 node_disk_discard_time_seconds_total{device="vda"} 0 node_disk_discard_time_seconds_total{device="vdb"} 0 node_disk_discarded_sectors_total{device="vda"} 0 node_disk_discarded_sectors_total{device="vdb"} 0 node_disk_discards_completed_total{device="vda"} 0 node_disk_discards_completed_total{device="vdb"} 0 node_disk_discards_merged_total{device="vda"} 0 node_disk_discards_merged_total{device="vdb"} 0 node_disk_info{device="vda",major="252",minor="0"} 1 node_disk_info{device="vdb",major="252",minor="16"} 1 node_disk_io_now{device="vda"} 0 node_disk_io_now{device="vdb"} 0 node_disk_io_time_seconds_total{device="vda"} 174 node_disk_io_time_seconds_total{device="vdb"} 0.054 node_disk_io_time_weighted_seconds_total{device="vda"} 259.79200000000003 node_disk_io_time_weighted_seconds_total{device="vdb"} 0.039 node_disk_read_bytes_total{device="vda"} 3.71867136e+08 node_disk_read_bytes_total{device="vdb"} 366592 node_disk_read_time_seconds_total{device="vda"} 19.128 node_disk_read_time_seconds_total{device="vdb"} 0.039 node_disk_reads_completed_total{device="vda"} 5619 node_disk_reads_completed_total{device="vdb"} 96 node_disk_reads_merged_total{device="vda"} 5 node_disk_reads_merged_total{device="vdb"} 0 node_disk_write_time_seconds_total{device="vda"} 240.66400000000002 node_disk_write_time_seconds_total{device="vdb"} 0 node_disk_writes_completed_total{device="vda"} 71584 node_disk_writes_completed_total{device="vdb"} 0 node_disk_writes_merged_total{device="vda"} 19761 node_disk_writes_merged_total{device="vdb"} 0 node_disk_written_bytes_total{device="vda"} 2.007924224e+09 node_disk_written_bytes_total{device="vdb"} 0
apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: labels: k8s-app: node-exporter-metrics-monitor name: node-exporter-metrics-monitor 1 namespace: dynamation 2 spec: endpoints: - interval: 30s 3 port: exmet 4 scheme: http selector: matchLabels: servicetype: metrics
oc create -f node-exporter-metrics-monitor.yaml
oc expose service -n <namespace> <node_exporter_service_name>
oc get route -o=custom-columns=NAME:.metadata.name,DNS:.spec.host
NAME DNS node-exporter-service node-exporter-service-dynamation.apps.cluster.example.org
curl -s http://node-exporter-service-dynamation.apps.cluster.example.org/metrics
go_gc_duration_seconds{quantile="0"} 1.5382e-05 go_gc_duration_seconds{quantile="0.25"} 3.1163e-05 go_gc_duration_seconds{quantile="0.5"} 3.8546e-05 go_gc_duration_seconds{quantile="0.75"} 4.9139e-05 go_gc_duration_seconds{quantile="1"} 0.000189423
oc adm must-gather --image-stream=openshift/must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.12.16
oc adm must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.12.16 -- <environment_variable_1> <environment_variable_2> <script_name>
oc adm must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.12.16 -- PROS=5 /usr/bin/gather 1
oc adm must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.12.16 -- NS=mynamespace VM=my-vm /usr/bin/gather --vms_details 1
oc adm must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.12.16 -- /usr/bin/gather --images