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 --previous 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:

    $ 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

  1. In the OpenShift Virtualization console, click WorkloadsVirtualization from the side menu.
  2. Click the Virtual Machines tab.
  3. Select a virtual machine to open the Virtual Machine Overview screen.
  4. In the Details tab, click the virt-launcher-<name> pod in the Pod section.
  5. 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

  1. Click WorkloadsVirtualization from the side menu.
  2. Click the Virtual Machines tab.
  3. Select a virtual machine to open the Virtual Machine Overview screen.
  4. 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:

    $ 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:

    $ oc describe vm <vm>
    $ oc describe vmi <vmi>
    $ 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:

$ 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 WorkloadsVirtualization page. The WorkloadsVirtualization 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

  1. 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.
  2. Create the VMI by running the following command:

    $ 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

  1. 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.
  2. Create the VMI by running the following command:

    $ 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

  1. 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.
  2. Create the VMI by running the following command:

    $ 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: 0
      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

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

  1. In the Administrator perspective in the OpenShift Virtualization web console, navigate to ObserveDashboards.
  2. Select the KubeVirt/Infrastructure Resources/Top Consumers dashboard from the Dashboard list.
  3. Select a predefined time period from the drop-down menu for Period. You can review the data for top consumers in the tables.
  4. 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

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 OpenShift Logging components

The OpenShift Logging 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 OpenShift Logging 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:

  • The unique random identifier that is generated during an installation
  • 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 name of the provider platform that OpenShift Container Platform is deployed on and the data center location
  • 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
  • The OpenShift Container Platform framework components installed in a cluster and their condition and status
  • Usage information about components, features, and extensions
  • Usage details about Technology Previews and unsupported configurations
  • Information about degraded software
  • Information about nodes that are marked as NotReady
  • Events for all namespaces listed as "related objects" for a degraded Operator
  • 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
  • Information about the validity of certificates
  • Number of application builds by build strategy type

Telemetry does not collect identifying information such as user names 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

  1. In the Administrator perspective within the OpenShift Container Platform web console, select ObserveMetrics.
  2. Select Insert Metric at Cursor to view a list of predefined queries.
  3. To create a custom query, add your Prometheus Query Language (PromQL) query to the Expression field.
  4. To add multiple queries, select Add Query.
  5. To delete a query, select kebab next to the query, then choose Delete query.
  6. To disable a query from being run, select kebab next to the query and choose Disable query.
  7. 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.

  8. 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

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

  1. From the Developer perspective in the OpenShift Container Platform web console, select ObserveMetrics.
  2. Select the project that you want to view metrics for in the Project: list.
  3. 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

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

13.10. Collecting OpenShift Virtualization data for Red Hat Support

When opening a support case, it is helpful to provide debugging information about your cluster to Red Hat Support.

The must-gather tool enables you to collect diagnostic information about your OpenShift Container Platform cluster, including virtual machines and other data related to OpenShift Virtualization.

For prompt support, supply diagnostic information for both OpenShift Container Platform and OpenShift Virtualization.

13.10.1. About the must-gather tool

The oc adm must-gather CLI command collects the information from your cluster that is most likely needed for debugging issues, such as:

  • Resource definitions
  • Audit logs
  • Service logs

You can specify one or more images when you run the command by including the --image argument. When you specify an image, the tool collects data related to that feature or product.

When you run oc adm must-gather, a new pod is created on the cluster. The data is collected on that pod and saved in a new directory that starts with must-gather.local. This directory is created in the current working directory.

13.10.2. About collecting OpenShift Virtualization data

You can use the oc adm must-gather CLI command to collect information about your cluster, including features and objects associated with OpenShift Virtualization:

  • The OpenShift Virtualization Operator namespaces (and child objects)
  • All OpenShift Virtualization custom resource definitions (CRDs)
  • All namespaces that contain virtual machines
  • Basic virtual machine definitions

To collect OpenShift Virtualization data with must-gather, you must specify the OpenShift Virtualization image: --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.1.

13.10.3. Gathering data about specific features

You can gather debugging information about specific features by using the oc adm must-gather CLI command with the --image or --image-stream argument. The must-gather tool supports multiple images, so you can gather data about more than one feature by running a single command.

Note

To collect the default must-gather data in addition to specific feature data, add the --image-stream=openshift/must-gather argument.

Prerequisites

  • Access to the cluster as a user with the cluster-admin role.
  • The OpenShift Container Platform CLI (oc) installed.

Procedure

  1. Navigate to the directory where you want to store the must-gather data.
  2. Run the oc adm must-gather command with one or more --image or --image-stream arguments. For example, the following command gathers both the default cluster data and information specific to OpenShift Virtualization:

    $ oc adm must-gather \
     --image-stream=openshift/must-gather \ 1
     --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.1 2
    1
    The default OpenShift Container Platform must-gather image
    2
    The must-gather image for OpenShift Virtualization

    You can use the must-gather tool with additional arguments to gather data that is specifically related to OpenShift Logging and the Red Hat OpenShift Logging Operator in your cluster. For OpenShift Logging, run the following command:

    $ oc adm must-gather --image=$(oc -n openshift-logging get deployment.apps/cluster-logging-operator \
     -o jsonpath='{.spec.template.spec.containers[?(@.name == "cluster-logging-operator")].image}')

    Example 13.1. Example must-gather output for OpenShift Logging

    ├── cluster-logging
    │  ├── clo
    │  │  ├── cluster-logging-operator-74dd5994f-6ttgt
    │  │  ├── clusterlogforwarder_cr
    │  │  ├── cr
    │  │  ├── csv
    │  │  ├── deployment
    │  │  └── logforwarding_cr
    │  ├── collector
    │  │  ├── fluentd-2tr64
    │  ├── eo
    │  │  ├── csv
    │  │  ├── deployment
    │  │  └── elasticsearch-operator-7dc7d97b9d-jb4r4
    │  ├── es
    │  │  ├── cluster-elasticsearch
    │  │  │  ├── aliases
    │  │  │  ├── health
    │  │  │  ├── indices
    │  │  │  ├── latest_documents.json
    │  │  │  ├── nodes
    │  │  │  ├── nodes_stats.json
    │  │  │  └── thread_pool
    │  │  ├── cr
    │  │  ├── elasticsearch-cdm-lp8l38m0-1-794d6dd989-4jxms
    │  │  └── logs
    │  │     ├── elasticsearch-cdm-lp8l38m0-1-794d6dd989-4jxms
    │  ├── install
    │  │  ├── co_logs
    │  │  ├── install_plan
    │  │  ├── olmo_logs
    │  │  └── subscription
    │  └── kibana
    │     ├── cr
    │     ├── kibana-9d69668d4-2rkvz
    ├── cluster-scoped-resources
    │  └── core
    │     ├── nodes
    │     │  ├── ip-10-0-146-180.eu-west-1.compute.internal.yaml
    │     └── persistentvolumes
    │        ├── pvc-0a8d65d9-54aa-4c44-9ecc-33d9381e41c1.yaml
    ├── event-filter.html
    ├── gather-debug.log
    └── namespaces
       ├── openshift-logging
       │  ├── apps
       │  │  ├── daemonsets.yaml
       │  │  ├── deployments.yaml
       │  │  ├── replicasets.yaml
       │  │  └── statefulsets.yaml
       │  ├── batch
       │  │  ├── cronjobs.yaml
       │  │  └── jobs.yaml
       │  ├── core
       │  │  ├── configmaps.yaml
       │  │  ├── endpoints.yaml
       │  │  ├── events
       │  │  │  ├── elasticsearch-im-app-1596020400-gm6nl.1626341a296c16a1.yaml
       │  │  │  ├── elasticsearch-im-audit-1596020400-9l9n4.1626341a2af81bbd.yaml
       │  │  │  ├── elasticsearch-im-infra-1596020400-v98tk.1626341a2d821069.yaml
       │  │  │  ├── elasticsearch-im-app-1596020400-cc5vc.1626341a3019b238.yaml
       │  │  │  ├── elasticsearch-im-audit-1596020400-s8d5s.1626341a31f7b315.yaml
       │  │  │  ├── elasticsearch-im-infra-1596020400-7mgv8.1626341a35ea59ed.yaml
       │  │  ├── events.yaml
       │  │  ├── persistentvolumeclaims.yaml
       │  │  ├── pods.yaml
       │  │  ├── replicationcontrollers.yaml
       │  │  ├── secrets.yaml
       │  │  └── services.yaml
       │  ├── openshift-logging.yaml
       │  ├── pods
       │  │  ├── cluster-logging-operator-74dd5994f-6ttgt
       │  │  │  ├── cluster-logging-operator
       │  │  │  │  └── cluster-logging-operator
       │  │  │  │     └── logs
       │  │  │  │        ├── current.log
       │  │  │  │        ├── previous.insecure.log
       │  │  │  │        └── previous.log
       │  │  │  └── cluster-logging-operator-74dd5994f-6ttgt.yaml
       │  │  ├── cluster-logging-operator-registry-6df49d7d4-mxxff
       │  │  │  ├── cluster-logging-operator-registry
       │  │  │  │  └── cluster-logging-operator-registry
       │  │  │  │     └── logs
       │  │  │  │        ├── current.log
       │  │  │  │        ├── previous.insecure.log
       │  │  │  │        └── previous.log
       │  │  │  ├── cluster-logging-operator-registry-6df49d7d4-mxxff.yaml
       │  │  │  └── mutate-csv-and-generate-sqlite-db
       │  │  │     └── mutate-csv-and-generate-sqlite-db
       │  │  │        └── logs
       │  │  │           ├── current.log
       │  │  │           ├── previous.insecure.log
       │  │  │           └── previous.log
       │  │  ├── elasticsearch-cdm-lp8l38m0-1-794d6dd989-4jxms
       │  │  ├── elasticsearch-im-app-1596030300-bpgcx
       │  │  │  ├── elasticsearch-im-app-1596030300-bpgcx.yaml
       │  │  │  └── indexmanagement
       │  │  │     └── indexmanagement
       │  │  │        └── logs
       │  │  │           ├── current.log
       │  │  │           ├── previous.insecure.log
       │  │  │           └── previous.log
       │  │  ├── fluentd-2tr64
       │  │  │  ├── fluentd
       │  │  │  │  └── fluentd
       │  │  │  │     └── logs
       │  │  │  │        ├── current.log
       │  │  │  │        ├── previous.insecure.log
       │  │  │  │        └── previous.log
       │  │  │  ├── fluentd-2tr64.yaml
       │  │  │  └── fluentd-init
       │  │  │     └── fluentd-init
       │  │  │        └── logs
       │  │  │           ├── current.log
       │  │  │           ├── previous.insecure.log
       │  │  │           └── previous.log
       │  │  ├── kibana-9d69668d4-2rkvz
       │  │  │  ├── kibana
       │  │  │  │  └── kibana
       │  │  │  │     └── logs
       │  │  │  │        ├── current.log
       │  │  │  │        ├── previous.insecure.log
       │  │  │  │        └── previous.log
       │  │  │  ├── kibana-9d69668d4-2rkvz.yaml
       │  │  │  └── kibana-proxy
       │  │  │     └── kibana-proxy
       │  │  │        └── logs
       │  │  │           ├── current.log
       │  │  │           ├── previous.insecure.log
       │  │  │           └── previous.log
       │  └── route.openshift.io
       │     └── routes.yaml
       └── openshift-operators-redhat
          ├── ...
  3. Create a compressed file from the must-gather directory that was just created in your working directory. For example, on a computer that uses a Linux operating system, run the following command:

    $ tar cvaf must-gather.tar.gz must-gather.local.5421342344627712289/ 1
    1
    Make sure to replace must-gather-local.5421342344627712289/ with the actual directory name.
  4. Attach the compressed file to your support case on the Red Hat Customer Portal.

13.10.4. must-gather tool usage for targeted VM data

When you use the must-gather CLI tool to collect OpenShift Virtualization data, the virtual machine (VM) information collected by default is limited to VirtualMachine and VirtualMachineInstance custom resources (CRs). You can request additional or targeted data by including parameters when you run the must-gather command. These parameters include environment variables and scripts.

Supported parameters

Environment variables

NS=<namespace_name>
Gather virtual machine details from the namespace that you specify.
VM=<vm_name>
Gather 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. By default, the tool uses no more than five parallel processes.

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 variable combinations.

gather_vms_details
Collect virtual machine 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 of the supported 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.
Usage

To customize the data that must-gather collects, append a double dash (--) to the command, followed by one or more compatible parameters. If you use any environment variables, you must specify a script.

The following options are valid:

  • You can specify one script without using any environment variables.
  • You can use one or more environment variables in any order, followed by one script.

Syntax

$ oc adm must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.1 \
 -- <environment_variable_1> <environment_variable_2> <script_name>

Examples

  • The following command collects extensive VM details for the my-vm VM in the mynamespace namespace:

    $ oc adm must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.1 -- NS=mynamespace VM=my-vm gather_vms_details
    Important

    If you use the VM environment variable, you must also specify a namespace.

  • The following command collects default must-gather information by using a maximum of three parallel processes:

    $ oc adm must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.1 -- PROS=3 gather
  • The following command collects image and image stream information from the cluster:

    $ oc adm must-gather --image=registry.redhat.io/container-native-virtualization/cnv-must-gather-rhel8:v4.9.1 -- gather_images