Chapter 13. Logging, events, and monitoring 13.1. Viewing virtual machine logs 13.1.1. About virtual machine logs Logs are collected for OpenShift Container Platform builds, deployments, and pods. In OpenShift Virtualization, virtual machine logs can be retrieved from the virtual machine launcher pod in either the web console or the CLI. The -f option follows the log output in real time, which is useful for monitoring progress and error checking. If the launcher pod is failing to start, use the -- option to see the logs of the last attempt. Warning ErrImagePull and ImagePullBackOff errors can be caused by an incorrect deployment configuration or problems with the images that are referenced. 13.1.2. Viewing virtual machine logs in the CLI Get virtual machine logs from the virtual machine launcher pod. Procedure Use the following command: USD oc logs <virt-launcher-name> 13.1.3. Viewing virtual machine logs in the web console Get virtual machine logs from the associated virtual machine launcher pod. Procedure In the OpenShift Virtualization console, click Workloads Virtualization from the side menu. Click the Virtual Machines tab. Select a virtual machine to open the Virtual Machine Overview screen. In the Details tab, click the virt-launcher-<name> pod in the Pod section. Click Logs . 13.2. Viewing events 13.2.1. 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 . 13.2.2. Viewing the events for a virtual machine in the web console You can view the stream events for a running a virtual machine from the Virtual Machine Overview panel of the web console. The ▮▮ button pauses the events stream. The ▶ button continues a paused events stream. Procedure Click Workloads Virtualization from the side menu. Click the Virtual Machines tab. Select a virtual machine to open the Virtual Machine Overview screen. Click Events to view all events for the virtual machine. 13.2.3. 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 13.2.4. 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> 13.3. Diagnosing data volumes using events and conditions Use the oc describe command to analyze and help resolve issues with data volumes. 13.3.1. 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. 13.3.2. 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 13.4. 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. 13.4.1. About the Virtual Machines dashboard Access virtual machines from the OpenShift Container Platform web console by navigating to the Workloads Virtualization page. The Workloads Virtualization page contains two tabs: Virtual Machines Virtual Machine Templates The following cards describe each virtual machine: Details provides identifying information about the virtual machine, including: Name Namespace Date of creation Node name IP address Inventory lists the virtual machine's resources, including: Network interface controllers (NICs) Disks Status includes: The current status of the virtual machine A note indicating whether or not the QEMU guest agent is installed on the virtual machine Utilization includes charts that display usage data for: CPU Memory Filesystem Network transfer Note Use the drop-down list to choose a duration for the utilization data. The available options are 1 Hour , 6 Hours , and 24 Hours . Events lists messages about virtual machine activity over the past hour. To view additional events, click View all . 13.5. 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. 13.5.1. 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. 13.5.2. 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 13.5.3. 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 13.5.4. 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 13.5.5. 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 13.5.6. Additional resources Monitoring application health by using health checks 13.6. 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 . 13.6.1. About the OpenShift Container Platform dashboards page 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. Cluster Capacity charts help administrators understand when additional resources are required in the cluster. The charts contain an inner ring that displays current consumption, while an outer ring displays thresholds configured for the resource, including information about: CPU time Memory allocation Storage consumed Network resources consumed 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. Events lists messages related to recent activity in the cluster, such as pod creation or virtual machine migration to another host. Top Consumers 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). 13.7. 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 stack 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. 13.7.1. 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. 13.7.2. 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. 13.7.3. Additional resources Monitoring overview Reviewing monitoring dashboards 13.8. OpenShift Container Platform cluster monitoring, logging, and Telemetry OpenShift Container Platform provides various resources for monitoring at the cluster level. 13.8.1. About OpenShift Container Platform monitoring OpenShift Container Platform includes a pre-configured, pre-installed, 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 4.9, 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. 13.8.2. About logging subsystem components The logging subsystem components include a collector deployed to each node in the OpenShift Container Platform cluster that collects all node and container logs and writes them to a log store. You can use a centralized web UI to create rich visualizations and dashboards with the aggregated data. The major components of the logging subsystem are: collection - This is the component that collects logs from the cluster, formats them, and forwards them to the log store. The current implementation is Fluentd. log store - This is where the logs are stored. The default implementation is Elasticsearch. You can use the default Elasticsearch log store or forward logs to external log stores. The default log store is optimized and tested for short-term storage. visualization - This is the UI component you can use to view logs, graphs, charts, and so forth. The current implementation is Kibana. For more information on OpenShift Logging, see the OpenShift Logging documentation. 13.8.3. 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. 13.8.3.1. Information collected by Telemetry The following information is collected by Telemetry: 13.8.3.1.1. 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 13.8.3.1.2. 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 13.8.3.1.3. 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. 13.8.4. CLI troubleshooting and debugging commands For a list of the oc client troubleshooting and debugging commands, see the OpenShift Container Platform CLI tools documentation. 13.9. Prometheus queries for virtual resources OpenShift Virtualization provides metrics for monitoring how infrastructure resources are consumed in the cluster. The metrics cover the following resources: vCPU Network Storage Guest memory swapping Use the OpenShift Container Platform monitoring dashboard to query virtualization metrics. 13.9.1. 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. 13.9.2. 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. 13.9.2.1. 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. Note Only cluster administrators have access to the third-party UIs provided with OpenShift Container Platform Monitoring. Prerequisites You have access to the cluster as a user with the cluster-admin role or with view permissions for all projects. You have installed the OpenShift CLI ( oc ). Procedure In the Administrator perspective within the OpenShift Container Platform web console, select Observe Metrics . Select Insert Metric at Cursor to view a list of predefined queries. To create a custom query, add your Prometheus Query Language (PromQL) query to the Expression field. To add multiple queries, select Add Query . To delete a query, select to the query, then choose Delete query . To disable a query from being run, select to the query and choose Disable query . Select Run Queries to run the queries that you have created. 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, select Hide graph and calibrate your query using only the metrics table. Then, 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. Additional resources See the Prometheus query documentation for more information about creating PromQL queries. 13.9.2.2. 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. Developers cannot access the third-party UIs provided with OpenShift Container Platform monitoring that are for core platform components. Instead, use the Metrics UI 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 From 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. Choose a query from the Select Query list, or run a custom PromQL query by selecting Show PromQL . Note In the Developer perspective, you can only run one query at a time. Additional resources See the Prometheus query documentation for more information about creating PromQL queries. 13.9.3. 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. 13.9.3.1. 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. 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. 13.9.3.2. 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. kubevirt_vmi_network_transmit_bytes_total Returns the total amount of traffic transmitted (in bytes) on the virtual machine's network. 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. 13.9.3.3. Storage metrics 13.9.3.3.1. 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. kubevirt_vmi_storage_write_traffic_bytes_total Returns the total amount of storage writes (in bytes) of the virtual machine's storage-related traffic. 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. 13.9.3.3.2. 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. kubevirt_vmi_storage_iops_write_total Returns the amount of read I/O operations the virtual machine is performing per second. 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. 13.9.3.4. 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. kubevirt_vmi_memory_swap_out_traffic_bytes_total Returns the total amount (in bytes) of memory the virtual guest is swapping out. 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. 13.9.4. Additional resources Monitoring overview 13.10. 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. 13.10.1. 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 Container Storage, if necessary. Collect must-gather data for OpenShift Virtualization by using the OpenShift Virtualization must-gather image. Collect Prometheus metrics for the cluster. 13.10.1.1. 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 Container Storage Collecting must-gather data for OpenShift Virtualization Collecting Prometheus metrics for all projects as a cluster administrator 13.10.2. 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. 13.10.2.1. 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 13.10.3. 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:v{HCOVersion} 13.10.3.1. 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 and image stream information Limiting the maximum number of parallel processes used by the must-gather tool 13.10.3.1.1. 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 only compatible with certain environment variable combinations. gather_vms_details Collect VM log files, VM definitions, and namespaces (and their child objects) that belong to OpenShift Virtualization resources. 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. gather Use the default must-gather script, which collects cluster data from all namespaces and includes only basic VM information. This script is only compatible with the PROS variable. gather_images Collect image and image stream custom resource information. This script is only compatible with the PROS variable. 13.10.3.1.2. Usage and examples Environment variables are optional. You can run a script by itself or with one or more compatible environment variables. Table 13.1. Compatible parameters Script Compatible environment variable gather_vms_details For a namespace: NS=<namespace_name> For a VM: VM=<vm_name> NS=<namespace_name> PROS=<number_of_processes> gather PROS=<number_of_processes> gather_images PROS=<number_of_processes> To customize the data that must-gather collects, you append a double dash ( -- ) to the command, followed by a space and one or more compatible parameters. Syntax USD oc adm must-gather \ --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.7 \ -- <environment_variable_1> <environment_variable_2> <script_name> 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:v4.9.7 \ -- NS=mynamespace VM=my-vm gather_vms_details 1 1 The NS environment variable is mandatory if you use the VM environment variable. Default data collection limited to three parallel processes The following command collects default must-gather information by using a maximum of three parallel processes: USD oc adm must-gather \ --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.7 \ -- PROS=3 gather Image and image stream information The following command collects image and image stream information from the cluster: USD oc adm must-gather \ --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.7 \ -- gather_images 13.10.3.2. Additional resources About the must-gather tool

Commands:
oc logs <virt-launcher-name>
oc get events
oc describe vm <vm>
oc describe vmi <vmi>
oc describe pod virt-launcher-<name>
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
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
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
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
oc adm must-gather --image-stream=openshift/must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v{HCOVersion}
oc adm must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.7 -- <environment_variable_1> <environment_variable_2> <script_name>
oc adm must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.7 -- NS=mynamespace VM=my-vm gather_vms_details 1
oc adm must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.7 -- PROS=3 gather
oc adm must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.7 -- gather_images