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    Kibana

    This document describes how to configure your Google Kubernetes Engine deployment so that you can use Google Cloud Managed Service for Prometheus to collect metrics from Kibana. This document shows you how to do the following:

    • Set up Kibana to report metrics.
    • Configure a PodMonitoring resource for Managed Service for Prometheus to collect the exported metrics.
    • Access a dashboard in Cloud Monitoring to view the metrics.
    • Configure alerting rules to monitor the metrics.

    These instructions apply only if you are using managed collection with Managed Service for Prometheus. If you are using self-deployed collection, then see the Kibana documentation for installation information.

    These instructions are provided as an example and are expected to work in most Kubernetes environments. If you are having trouble installing an application or exporter due to restrictive security or organizational policies, then we recommend you consult open-source documentation for support.

    For information about Kibana, see Kibana .

    Prerequisites

    To collect metrics from the Kibana exporter by using Managed Service for Prometheus and managed collection, your deployment must meet the following requirements:

    • Your cluster must be running Google Kubernetes Engine version 1.28.15-gke.2475000 or later.
    • You must be running Managed Service for Prometheus with managed collection enabled. For more information, see Get started with managed collection .
    • To use dashboards available in Cloud Monitoring for the Kibana integration, you must use kibana-prometheus-exporter version 8.0.0 or later.

      For more information about available dashboards, see View dashboards .

    Kibana exposes Prometheus-format metrics only after you install the Kibana exporter plugin. To install the plugin, follow the installation instructions .

    The installation process requires the use of bin/kibana-plugin install PLUGIN . One way to install the plugin is to define a custom Kibana Docker image; see the following example:

       
FROM  
kibana: KIBANA_VERSION 
  
RUN  
bin/kibana-plugin  
install  
https://github.com/pjhampton/kibana-prometheus-exporter/releases/download/ PLUGIN_VERSION 
/kibanaPrometheusExporter- PLUGIN_VERSION 
.zip

    After building the image and pushing it to a remote repository, it can be used within the Kubernetes deployment. For example:

       
 apiVersion 
 : 
  
 v1 
  
 kind 
 : 
  
 ConfigMap 
  
 metadata 
 : 
  
 name 
 : 
  
 kibana 
  
 data 
 : 
  
 kibana.yml 
 : 
  
 | 
  
 server.name: kibana 
  
 server.host: "0.0.0.0" 
  
 # Update this with credentials to match your Elasticsearch instance 
  
 elasticsearch.hosts: http://username:password@elasticsearch-service-name:9200 
  
 --- 
  
 apiVersion 
 : 
  
 apps/v1 
  
 kind 
 : 
  
 Deployment 
  
 metadata 
 : 
  
 name 
 : 
  
 kibana 
  
 labels 
 : 
  
 app.kubernetes.io/name 
 : 
  
 kibana 
  
 spec 
 : 
  
 ... 
  
 template 
 : 
  
 ... 
  
 spec 
 : 
  
 containers 
 : 
  
 - 
  
 name 
 : 
  
 kibana 
  
 image 
 : 
  
  CUSTOM_IMAGE 
 
  
 ports 
 : 
  
 - 
  
 containerPort 
 : 
  
 5601 
  
 name 
 : 
  
 kibana 
  
 protocol 
 : 
  
 TCP 
  
 volumeMounts 
 : 
  
 - 
  
 mountPath 
 : 
  
 /usr/share/kibana/config/kibana.yml 
  
 subPath 
 : 
  
 kibana.yml 
  
 name 
 : 
  
 kibana 
  
 volumes 
 : 
  
 - 
  
 name 
 : 
  
 kibana 
  
 configMap 
 : 
  
 name 
 : 
  
 kibana 
  
 items 
 : 
  
 - 
  
 key 
 : 
  
 kibana.yml 
  
 path 
 : 
  
 kibana.yml

    To verify that the Kibana exporter is emitting metrics on the expected endpoints, do the following:

    1. Set up port-forwarding with the following command:

      kubectl -n NAMESPACE_NAME 
port-forward POD_NAME 
5601

    2. Access the endpoint localhost:5601/_prometheus/metrics by using the browser or the curl utility in another terminal session.

    Define a PodMonitoring resource

    For target discovery, the Managed Service for Prometheus Operator requires a PodMonitoring resource that corresponds to the Kibana exporter in the same namespace.

    You can use the following PodMonitoring configuration:

      # Copyright 2024 Google LLC 
 # 
 # Licensed under the Apache License, Version 2.0 (the "License"); 
 # you may not use this file except in compliance with the License. 
 # You may obtain a copy of the License at 
 # 
 #     http://www.apache.org/licenses/LICENSE-2.0 
 # 
 # Unless required by applicable law or agreed to in writing, software 
 # distributed under the License is distributed on an "AS IS" BASIS, 
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 
 # See the License for the specific language governing permissions and 
 # limitations under the License. 
 apiVersion 
 : 
  
 monitoring.googleapis.com/v1 
 kind 
 : 
  
 PodMonitoring 
 metadata 
 : 
  
 name 
 : 
  
 kibana 
  
 labels 
 : 
  
 app.kubernetes.io/name 
 : 
  
 kibana 
  
 app.kubernetes.io/part-of 
 : 
  
 google-cloud-managed-prometheus 
 spec 
 : 
  
 endpoints 
 : 
  
 - 
  
 port 
 : 
  
 5601 
  
 scheme 
 : 
  
 http 
  
 interval 
 : 
  
 30s 
  
 path 
 : 
  
 /_prometheus/metrics 
  
 selector 
 : 
  
 matchLabels 
 : 
  
 app.kubernetes.io/name 
 : 
  
 kibana

    To apply configuration changes from a local file, run the following command:

    kubectl apply -n NAMESPACE_NAME 
-f FILE_NAME

    You can also use Terraform to manage your configurations.

    Define rules and alerts

    You can use the following Rules configuration to define alerts on your Kibana metrics:

      # Copyright 2024 Google LLC 
 # 
 # Licensed under the Apache License, Version 2.0 (the "License"); 
 # you may not use this file except in compliance with the License. 
 # You may obtain a copy of the License at 
 # 
 #     http://www.apache.org/licenses/LICENSE-2.0 
 # 
 # Unless required by applicable law or agreed to in writing, software 
 # distributed under the License is distributed on an "AS IS" BASIS, 
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 
 # See the License for the specific language governing permissions and 
 # limitations under the License. 
 apiVersion 
 : 
  
 monitoring.googleapis.com/v1 
 kind 
 : 
  
 Rules 
 metadata 
 : 
  
 name 
 : 
  
 kibana-rules 
  
 labels 
 : 
  
 app.kubernetes.io/component 
 : 
  
 rules 
  
 app.kubernetes.io/name 
 : 
  
 kibana-rules 
  
 app.kubernetes.io/part-of 
 : 
  
 google-cloud-managed-prometheus 
 spec 
 : 
  
 groups 
 : 
  
 - 
  
 name 
 : 
  
 kibana 
  
 interval 
 : 
  
 30s 
  
 rules 
 : 
  
 - 
  
 alert 
 : 
  
 KibanaHighCPUUsage 
  
 annotations 
 : 
  
 description 
 : 
  
 |- 
  
 Kibana high cpu usage 
  
 VALUE = {{ $value }} 
  
 LABELS: {{ $labels }} 
  
 summary 
 : 
  
 Kibana high cpu usage (instance {{ $labels.instance }}) 
  
 expr 
 : 
  
 kibana_os_load5 >= 90 
  
 for 
 : 
  
 5m 
  
 labels 
 : 
  
 severity 
 : 
  
 critical 
  
 - 
  
 alert 
 : 
  
 KibanaHighMemoryUsage 
  
 annotations 
 : 
  
 description 
 : 
  
 |- 
  
 Kibana high memory usage 
  
 VALUE = {{ $value }} 
  
 LABELS: {{ $labels }} 
  
 summary 
 : 
  
 Kibana high memory usage (instance {{ $labels.instance }}) 
  
 expr 
 : 
  
 kibana_os_mem_bytes_used / kibana_os_mem_bytes_total >= 0.9 
  
 for 
 : 
  
 5m 
  
 labels 
 : 
  
 severity 
 : 
  
 critical

    To apply configuration changes from a local file, run the following command:

    kubectl apply -n NAMESPACE_NAME 
-f FILE_NAME

    You can also use Terraform to manage your configurations.

    For more information about applying rules to your cluster, see Managed rule evaluation and alerting .

    You can adjust the alert thresholds to suit your application.

    Verify the configuration

    You can use Metrics Explorer to verify that you correctly configured the Kibana exporter. It might take one or two minutes for Cloud Monitoring to ingest your metrics.

    To verify the metrics are ingested, do the following:

    1. In the Google Cloud console, go to the Metrics explorer page:

      Go to Metrics explorer

      If you use the search bar to find this page, then select the result whose subheading is Monitoring .

    2. In the toolbar of the query-builder pane, select the button whose name is either MQL or PromQL .
    3. Verify that PromQL is selected in the Language toggle. The language toggle is in the same toolbar that lets you format your query.
    4. Enter and run the following query:
      up{job="kibana", cluster=" CLUSTER_NAME 
", namespace=" NAMESPACE_NAME 
"}

    View dashboards

    The Cloud Monitoring integration includes the Kibana Prometheus Overview dashboard. Dashboards are automatically installed when you configure the integration. You can also view static previews of dashboards without installing the integration.

    To view an installed dashboard, do the following:

    1. In the Google Cloud console, go to the Dashboards page:

      Go to Dashboards

      If you use the search bar to find this page, then select the result whose subheading is Monitoring .

    2. Select the Dashboard List tab.
    3. Choose the Integrations category.
    4. Click the name of the dashboard, for example, Kibana Prometheus Overview .

    To view a static preview of the dashboard, do the following:

    1. In the Google Cloud console, go to the Integrations page:

      Go to Integrations

      If you use the search bar to find this page, then select the result whose subheading is Monitoring .

    2. Click the Kubernetes Engine deployment-platform filter.
    3. Locate the Kibana integration and click View Details .
    4. Select the Dashboards tab.

    Troubleshooting

    For information about troubleshooting metric ingestion problems, see Problems with collection from exporters in Troubleshooting ingestion-side problems .
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