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Showing content from https://cloud.google.com/kubernetes-engine/docs/how-to/configure-automatic-application-monitoring below:

Configure automatic application monitoring for workloads | Google Kubernetes Engine (GKE)

You can save time and effort configuring and maintaining monitoring applications running on Google Kubernetes Engine (GKE) by enabling automatic application monitoring for supported workloads.

When you enable automatic application monitoring, GKE detects deployed instances of supported workloads and deploys PodMonitoring resources for each detected workload instance.

Automatic application monitoring also installs out-of-the-box dashboards for monitoring applications. The metrics are collected by Google Cloud Managed Service for Prometheus.

Automatic application monitoring supports the following workloads:

• Apache Airflow
• Istio
• RabbitMQ
• AI model servers:
  • JetStream
  • NVIDIA Triton
  • TensorFlow Serving
  • Text Generation Inference
  • TorchServe
  • vLLM

The metrics scraping interval for AI model servers is 15s. For non-AI workloads, the scraping interval is 30s.

For more information about other out-of-the-box observability solutions that you can configure manually, see Introduction to exporter configuration in the Google Cloud Observability documentation.

Before you start, make sure that you have performed the following tasks:

• Enable the Google Kubernetes Engine API.
Enable Google Kubernetes Engine API
• If you want to use the Google Cloud CLI for this task, install and then initialize the gcloud CLI. If you previously installed the gcloud CLI, get the latest version by running gcloud components update. Note: For existing gcloud CLI installations, make sure to set the compute/region property. If you use primarily zonal clusters, set the compute/zone instead. By setting a default location, you can avoid errors in the gcloud CLI like the following: One of [--zone, --region] must be supplied: Please specify location. You might need to specify the location in certain commands if the location of your cluster differs from the default that you set.

• Enable the Cloud Monitoring API.

To enable automatic application monitoring, your GKE cluster must meet the following requirements:

• Your cluster must be running GKE version 1.28 or later.
• You must have gcloud CLI version 492.0.0 or later.
• Your cluster must have Google Cloud Managed Service for Prometheus managed collection enabled. Google Cloud Managed Service for Prometheus managed collection is enabled by default for new clusters.

You can enable automatic application monitoring for new or existing GKE clusters using the Google Cloud console, the Google Cloud CLI or the GKE API.

Metrics scraping takes up to 10 minutes to start for supported workloads after you deploy a new workload or after you enable automatic application monitoring for a cluster.

To enable automatic application monitoring for a new cluster, do the following:

1. In the Google Cloud console, go to the Create an Autopilot cluster page.

   Go to Create an Autopilot cluster

   You can also complete this task by creating a Standard cluster.

2. For an Autopilot mode cluster, click Advanced settings. For a Standard mode cluster, click Features.

3. In the Operations section, select Enable automatic application monitoring.

4. Click Create.

You can also enable automatic application monitoring for an existing cluster by updating the Enable automatic application monitoring field in the Operations section of the Cluster Details tab.

To enable automatic application monitoring for a new cluster, use the option --auto-monitoring-scope=ALL:

gcloud container clusters create-auto CLUSTER_NAME \
    --location=COMPUTE_LOCATION \
    --auto-monitoring-scope=ALL

Replace the following:

• CLUSTER_NAME: the name of the new cluster.
• COMPUTE_LOCATION: the Compute Engine location for the cluster.

You can also update an existing cluster using the command gcloud container clusters update.

To enable automatic application monitoring for a new cluster, make a POST request to the method clusters.create:

POST https://container.googleapis.com/v1/projects/PROJECT_ID/locations/COMPUTE_LOCATION/clusters

{
  "cluster": {
    "name": "CLUSTER_NAME",
    "initialNodeCount": 1,
    "monitoringConfig": {
      "managedPrometheusConfig": {
        "enabled": true,
        "autoMonitoringConfig": {
          "scope": "ALL"
        }
      }
    }
  }
}

Replace the following:

• PROJECT_ID: your Google Cloud project ID.
• CLUSTER_NAME: the name of the new cluster.
• COMPUTE_LOCATION: the Compute Engine location for the cluster.

You can determine if automatic application monitoring is enabled or disabled for a cluster using the Google Cloud console, the gcloud CLI, or the GKE API.

Do the following:

1. Go to the Google Kubernetes Engine page in the Google Cloud console:

   Go to Google Kubernetes Engine

2. In the cluster list, click the name of the cluster.

3. In the Features section, the Automatic application monitoring field indicates if automatic application monitoring is enabled or disabled.

Describe the cluster:

gcloud container clusters describe CLUSTER_NAME \
    --location=COMPUTE_LOCATION \
    --format='value(monitoringConfig.managedPrometheusConfig.autoMonitoringConfig.scope)'

Replace the following:

• CLUSTER_NAME: the name of the cluster.
• COMPUTE_LOCATION: the Compute Engine location for the cluster.

The output is similar to the following:

autoMonitoringConfig.scope: ALL

In the output, if the value of autoMonitoringConfig.scope field is ALL, automatic application monitoring is enabled. Otherwise, automatic application monitoring is disabled.

Make a GET request to the method clusters.get:

GET https://container.googleapis.com/v1/projects/PROJECT_ID/locations/COMPUTE_LOCATION/clusters/CLUSTER_NAME

Replace the following:

• PROJECT_ID: your Google Cloud project ID.
• CLUSTER_NAME: the name of the cluster.
• COMPUTE_LOCATION: the Compute Engine location for the cluster.

The output is similar to the following:

autoMonitoringConfig.scope: ALL

In the output, if the value of autoMonitoringConfig.scope field is ALL, automatic application monitoring is enabled. Otherwise, automatic application monitoring is disabled.

When you enable automatic application monitoring, GKE installs out-of-the-box dashboards for monitoring applications for supported workloads that are deployed to your cluster. You won't see dashboards for supported workloads that have never run on a cluster.

To view the dashboards with telemetry from automatically monitored workloads in the Google Kubernetes Engine page, do the following:

1. Go to the Google Kubernetes Engine page in the Google Cloud console:

   Go to Google Kubernetes Engine

2. Click the name of the cluster where you want to view dashboards for automatically monitored workloads.

3. Click the Observability tab. The Integrations section shows configured dashboards for supported workloads running on the cluster.

To view the dashboards with telemetry from automatically monitored workloads in the Cloud Monitoring page, do the following:

1. Go to the Dashboards page.

   Go to Dashboards

2. Click the Dashboard List tab.

3. Select the Integrations category.

4. Click the name of the dashboard. For example, RabbitMQ Prometheus Overview.

If you disable automatic application monitoring on a cluster, the PodMonitoring resources that GKE created remain intact and GKE continues to monitor existing supported workloads. GKE stops automatically monitoring new instances of supported workloads that you deploy to the cluster. To stop monitoring existing supported workloads, you must delete the PodMonitoring resources that GKE created. If you re-enable automatic application monitoring for a cluster, GKE detects and reconciles the PodMonitoring resources that it previously created.

You can disable automatic application monitoring for a cluster using the Google Cloud console, the gcloud CLI, or the GKE API.

1. Go to the Google Kubernetes Engine page in the Google Cloud console:

   Go to Google Kubernetes Engine

2. Click the name of the cluster.

3. In the Features list, find the Automatic application monitoring field.

4. Click editEdit.

5. Deselect Enable automatic application monitoring.

6. Click Save.

Update the cluster using the option --auto-monitoring-scope=NONE:

gcloud container clusters update CLUSTER_NAME \
    --location=COMPUTE_LOCATION \
    --auto-monitoring-scope=NONE

Replace the following:

• CLUSTER_NAME: the name of the cluster.
• COMPUTE_LOCATION: the Compute Engine location for the cluster.

Make a PUT request to the method clusters.update:

PUT https://container.googleapis.com/v1/projects/PROJECT_ID/locations/COMPUTE_LOCATION/clusters/CLUSTER_NAME

{
  "update": {
    "desiredMonitoringConfig": {
      "managedPrometheusConfig": {
        "autoMonitoringConfig": {
          "scope": "NONE"
        }
      }
    }
  }
}

Replace the following:

• PROJECT_ID: your Google Cloud project ID.
• CLUSTER_NAME: the name of the cluster.
• COMPUTE_LOCATION: the Compute Engine location for the cluster.

You can customize the monitoring configuration for individual instances of supported workloads or opt out of monitoring individual instances of supported workloads.

To customize the PodMonitoring resource for a deployed instance of a supported workload without impacting the automatic application monitoring of other workloads, you must exclude the instance from automatic application monitoring and then update the configuration or replace the PodMonitoring resource associated with the target workload instance.

If you update or delete a PodMonitoring resource that GKE created without excluding the associated workload, GKE restores the PodMonitoring resource to ensure continuity while monitoring other supported workloads.

You can identify the PodMonitoring resource that GKE created for a workload using the Google Cloud console:

1. Go to the Object browser page.

   Go to Object browser

2. In the Cluster field, enter the name of the cluster.

3. In the Namespace field, enter the name of the namespace.

4. In the Object Kinds filter, select PodMonitoring.

5. Under monitoring.googleapis.com, select PodMonitoring.

6. Click an object name to inspect the object. The metadata label source:gke-auto-monitoring indicates that GKE created the PodMonitoring resource.

If you don't want to monitor a deployed instance of a supported workload, or if you want to customize the monitoring configuration of a workload, you can exclude the workload from automatic application monitoring.

To exclude a workload, you must add the metadata label allow-gke-auto-monitoring: false to the target workload configuration. For example, the following manifest describes a RabbitMQ StatefulSet that is not monitored by automatic application monitoring:

apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: rabbitmq
  labels:
    allow-gke-auto-monitoring: "false"
spec:
  serviceName: rabbitmq
  replicas: 3

After you exclude a workload instance, you can delete the PodMonitoring resource that GKE created for the workload. GKE does not attempt to restore the PodMonitoring resource if you delete or modify it. If you deploy a new workload with the metadata label allow-gke-auto-monitoring: false, GKE does not create a PodMonitoring resource for the workload.

If you want to stop monitoring a workload or if you want to deploy your own customized PodMonitoring resource for a workload, you can delete the monitoring configuration.

To delete the automatic application monitoring configuration of an individual workload, do the following:

1. Exclude the workload from automatic application monitoring.
2. Identify the PodMonitoring resource that GKE created for the workload.

3. Delete the PodMonitoring resource:

   kubectl delete podmonitoring POD_MONITORING_NAME -n NAMESPACE
   

   Replace the following:

   • POD_MONITORING_NAME: the name of the PodMonitoring resource.
   • NAMESPACE: the namespace of the PodMonitoring resource.

To delete the automatic application monitoring configuration of all workloads in a cluster, do the following:

1. Disable automatic application monitoring.

2. Delete all PodMonitoring resources in the cluster with the metadata label source:gke-auto-monitoring:

   kubectl delete podmonitorings -l source=gke-auto-monitoring --all-namespaces
   

The automatic application monitoring configuration and installation of out-of-the-box dashboards for supported workloads by automatic application monitoring is available at no additional charge. However, Monitoring charges for the ingestion of metrics by Google Cloud Managed Service for Prometheus according to Monitoring pricing.

• Learn how to View observability metrics.

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