Monitor APM Serveredit

Use the Elastic Stack monitoring features to gain insight into the real-time health and performance of APM Server. Stack monitoring exposes key metrics, like intake response count, intake error rate, output event rate, output failed event rate, and more.

Monitor APM running on Elastic Cloudedit

Elastic Cloud manages the installation and configuration of a monitoring agent for you — so all you have to do is flip a switch and watch the data pour in.

Monitor a self-installation of APMedit

This guide assumes you are already ingesting APM data into the Elastic Stack.

In 8.0 and later, you can use Metricbeat to collect data about APM Server and ship it to a monitoring cluster. To collect and ship monitoring data:

Configure Elastic Agent to send monitoring dataedit

  1. Enable monitoring of Elastic Agent by adding the following settings to your elastic-agent.yml configuration file:

    agent.monitoring:
      http:
        enabled: true 
        host: localhost 
        port: 6791 

    Enable monitoring

    The host to expose logs/metrics on

    The port to expose logs/metrics on

  2. Stop Elastic Agent

    If Elastic Agent is already running, you must stop it. Use the command that work with your system:

    sudo launchctl unload /Library/LaunchDaemons/co.elastic.elastic-agent.plist

    Elastic Agent will restart automatically if the system is rebooted.

  3. Start Elastic Agent

    Use the command that work with your system:

    sudo launchctl load /Library/LaunchDaemons/co.elastic.elastic-agent.plist

Install and configure Metricbeat to collect monitoring dataedit

  1. Install Metricbeat on the same server as Elastic Agent. To learn how, see Get started with Metricbeat. If you already have Metricbeat installed, skip this step.
  2. Enable the beat-xpack module in Metricbeat.

    For example, to enable the default configuration in the modules.d directory, run the following command, using the correct command syntax for your OS:

    metricbeat modules enable beat-xpack

    For more information, see Configure modules and beat module.

  3. Configure the beat-xpack module in Metricbeat.

    When complete, your modules.d/beat-xpack.yml file should look similar to this:

    - module: beat
      xpack.enabled: true
      period: 10s
      hosts: ["http://localhost:6791"]
      basepath: "/processes/apm-server-default"
      username: remote_monitoring_user
      password: your_password
    1. Do not change the module name or xpack.enabled boolean; these are required for stack monitoring. We recommend accepting the default period for now.
    2. Set the hosts to match the host:port configured in your elastic-agent.yml file. In this example, that’s http://localhost:6791.

      To monitor multiple APM Server instances running in multiple Elastic Agents, specify a list of hosts, for example:

      hosts: ["http://localhost:5066","http://localhost:5067","http://localhost:5068"]

      If you configured Elastic Agent to use encrypted communications, you must access it via HTTPS. For example, use a hosts setting like https://localhost:5066.

    3. APM Server metrics are exposed at /processes/apm-server-default. Add this location as the basepath.
    4. Set the username and password settings as required by your environment. If Elastic security features are enabled, you must provide a username and password so that Metricbeat can collect metrics successfully:

      1. Create a user on the Elasticsearch cluster that has the remote_monitoring_collector built-in role. Alternatively, if it’s available in your environment, use the remote_monitoring_user built-in user.
      2. Add the username and password settings to the beat module configuration file.
  4. Optional: Disable the system module in the Metricbeat.

    By default, the system module is enabled. The information it collects, however, is not shown on the Stack Monitoring page in Kibana. Unless you want to use that information for other purposes, run the following command:

    metricbeat modules disable system
  5. Identify where to send the monitoring data.

    In production environments, you should send your deployment logs and metrics to a dedicated monitoring deployment (referred to as the monitoring cluster). Monitoring indexes logs and metrics into Elasticsearch and these indexes consume storage, memory, and CPU cycles like any other index. By using a separate monitoring deployment, you avoid affecting your other production deployments and can view the logs and metrics even when a production deployment is unavailable.

    For example, specify the Elasticsearch output information in the Metricbeat configuration file (metricbeat.yml):

    output.elasticsearch:
      # Array of hosts to connect to.
      hosts: ["http://es-mon-1:9200", "http://es-mon2:9200"] 
    
      # Optional protocol and basic auth credentials.
      #protocol: "https"
      #api_key:  "id:api_key" 
      #username: "elastic"
      #password: "changeme"

    In this example, the data is stored on a monitoring cluster with nodes es-mon-1 and es-mon-2.

    Specify one of api_key or username/password.

    If you configured the monitoring cluster to use encrypted communications, you must access it via HTTPS. For example, use a hosts setting like https://es-mon-1:9200.

    The Elasticsearch monitoring features use ingest pipelines, therefore the cluster that stores the monitoring data must have at least one ingest node.

    If the Elasticsearch security features are enabled on the monitoring cluster, you must provide a valid user ID and password so that Metricbeat can send metrics successfully:

    1. Create a user on the monitoring cluster that has the remote_monitoring_agent built-in role. Alternatively, if it’s available in your environment, use the remote_monitoring_user built-in user.
    2. Add the username and password settings to the Elasticsearch output information in the Metricbeat configuration file.

    For more information about these configuration options, see Configure the Elasticsearch output.

  6. Start Metricbeat to begin collecting APM monitoring data.
  7. View the monitoring data in Kibana.