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Grafana Agent Flow mode Tasks Collect and forward Prometheus metrics
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Collect and forward Prometheus metrics

You can configure Grafana Agent Flow to collect Prometheus metrics and forward them to any Prometheus-compatible database.

This topic describes how to:

  • Configure metrics delivery.
  • Collect metrics from Kubernetes Pods.

Components used in this topic

Before you begin

  • Ensure that you have basic familiarity with instrumenting applications with Prometheus.
  • Have a set of Prometheus exports or applications exposing Prometheus metrics that you want to collect metrics from.
  • Identify where you will write collected metrics. Metrics can be written to Prometheus or Prometheus-compatible endpoints such as Grafana Mimir, Grafana Cloud, or Grafana Enterprise Metrics.
  • Be familiar with the concept of Components in Grafana Agent Flow.

Configure metrics delivery

Before components can collect Prometheus metrics, you must have a component responsible for writing those metrics somewhere.

The prometheus.remote_write component is responsible for delivering Prometheus metrics to one or Prometheus-compatible endpoints. After a prometheus.remote_write component is defined, you can use other Grafana Agent Flow components to forward metrics to it.

To configure a prometheus.remote_write component for metrics delivery, complete the following steps:

  1. Add the following prometheus.remote_write component to your configuration file.

    river
    prometheus.remote_write "<LABEL>" {
      endpoint {
        url = "<PROMETHEUS_URL>"
      }
    }

    Replace the following:

    • <LABEL>: The label for the component, such as default. The label you use must be unique across all prometheus.remote_write components in the same configuration file.
    • <PROMETHEUS_URL> The full URL of the Prometheus-compatible endpoint where metrics will be sent, such as https://prometheus-us-central1.grafana.net/api/prom/push.
  2. If your endpoint requires basic authentication, paste the following inside the endpoint block.

    river
    basic_auth {
      username = "<USERNAME>"
      password = "<PASSWORD>"
    }

    Replace the following:

    • <USERNAME>: The basic authentication username.
    • <PASSWORD>: The basic authentication password or API key.
  3. If you have more than one endpoint to write metrics to, repeat the endpoint block for additional endpoints.

The following example demonstrates configuring prometheus.remote_write with multiple endpoints and mixed usage of basic authentication, and a prometheus.scrape component which forwards metrics to it.

river
prometheus.remote_write "default" {
  endpoint {
    url = "http://localhost:9090/api/prom/push"
  }

  endpoint {
    url = "https://prometheus-us-central1.grafana.net/api/prom/push"

    // Get basic authentication based on environment variables.
    basic_auth {
      username = env("<REMOTE_WRITE_USERNAME>")
      password = env("<REMOTE_WRITE_PASSWORD>")
    }
  }
}

prometheus.scrape "example" {
  // Collect metrics from the default listen address.
  targets = [{
    __address__ = "127.0.0.1:12345",
  }]

  forward_to = [prometheus.remote_write.default.receiver]
}

For more information on configuring metrics delivery, refer to prometheus.remote_write.

Collect metrics from Kubernetes Pods

Grafana Agent Flow can be configured to collect metrics from Kubernetes Pods by:

  1. Discovering Kubernetes Pods to collect metrics from.
  2. Collecting metrics from those discovered Pods.

To collect metrics from Kubernetes Pods, complete the following steps:

  1. Follow Configure metrics delivery to ensure collected metrics can be written somewhere.

  2. Discover Kubernetes Pods:

    1. Add the following discovery.kubernetes component to your configuration file to discover every Pod in the cluster across all Namespaces.

      river
      discovery.kubernetes "<DISCOVERY_LABEL>" {
        role = "pod"
      }

      Replace the following

      • <DISCOVERY_LABEL>: The label for the component, such as pods. The label you use must be unique across all discovery.kubernetes components in the same configuration file.

      This generates one Prometheus target for every exposed port on every discovered Pod.

    2. To limit the Namespaces that Pods are discovered in, add the following block inside the discovery.kubernetes component.

      river
      namespaces {
        own_namespace = true
        names         = [<NAMESPACE_NAMES>]
      }

      Replace the following:

      • <NAMESPACE_NAMES>: A comma-delimited list of strings representing Namespaces to search. Each string must be wrapped in double quotes. For example, "default","kube-system".

      If you don’t want to search for Pods in the Namespace Grafana Agent Flow is running in, set own_namespace to false.

    3. To use a field selector to limit the number of discovered Pods, add the following block inside the discovery.kubernetes component.

      river
      selectors {
        role  = "pod"
        field = "<FIELD_SELECTOR>"
      }

      Replace the following:

      • <FIELD_SELECTOR>: The Kubernetes field selector to use, such as metadata.name=my-service. For more information on field selectors, refer to the Kubernetes documentation on Field Selectors.

      Create additional selectors blocks for each field selector you want to apply.

    4. To use a label selector to limit the number of discovered Pods, add the following block inside the discovery.kubernetes component.

      river
      selectors {
        role  = "pod"
        label = "LABEL_SELECTOR"
      }

      Replace the following:

      • <LABEL_SELECTOR>: The Kubernetes label selector, such as environment in (production, qa). For more information on label selectors, refer to the Kubernetes documentation on Labels and Selectors.

      Create additional selectors blocks for each label selector you want to apply.

  3. Collect metrics from discovered Pods:

    1. Add the following prometheus.scrape component to your configuration file.

      river
      prometheus.scrape "<SCRAPE_LABEL>" {
        targets    = discovery.kubernetes.<DISCOVERY_LABEL>.targets
        forward_to = [prometheus.remote_write.<REMOTE_WRITE_LABEL>.receiver]
      }

      Replace the following:

      • <SCRAPE_LABEL>: The label for the component, such as pods. The label you use must be unique across all prometheus.scrape components in the same configuration file.
      • <DISCOVERY_LABEL>: The label for the discovery.kubernetes component.
      • <REMOTE_WRITE_LABEL>: The label for your existing prometheus.remote_write component.

The following example demonstrates configuring Grafana Agent Flow to collect metrics from running production Kubernetes Pods in the default Namespace.

river
discovery.kubernetes "pods" {
  role = "pod"

  namespaces {
    own_namespace = false

    names = ["default"]
  }

  selectors {
    role  = "pod"
    label = "environment in (production)"
  }
}

prometheus.scrape "pods" {
  targets    = discovery.kubernetes.pods.targets
  forward_to = [prometheus.remote_write.default.receiver]
}

prometheus.remote_write "default" {
  endpoint {
    url = "http://localhost:9090/api/prom/push"
  }
}

For more information on configuring Kubernetes service delivery and collecting metrics, refer to discovery.kubernetes and prometheus.scrape.

Collect metrics from Kubernetes Services

You can configure Grafana Agent Flow to collect metrics from Kubernetes Services by:

  1. Discovering Kubernetes Services to collect metrics from.
  2. Collecting metrics from those discovered Services.

To collect metrics from Kubernetes Services, complete the following steps.

  1. Follow Configure metrics delivery to ensure collected metrics can be written somewhere.

  2. Discover Kubernetes Services:

    1. Add the following discovery.kubernetes component to your configuration file to discover every Services in the cluster across all Namespaces.

      river
      discovery.kubernetes "<DISCOVERY_LABEL>" {
        role = "service"
      }

      Replace the following:

      • <DISCOVERY_LABEL>: A label for the component, such as services. The label you use must be unique across all discovery.kubernetes components in the same configuration file.

      This will generate one Prometheus target for every exposed port on every discovered Service.

    2. To limit the Namespaces that Services are discovered in, add the following block inside the discovery.kubernetes component.

      river
      namespaces {
        own_namespace = true
        names         = [<NAMESPACE_NAMES>]
      }

      Replace the following:

      • <NAMESPACE_NAMES>: A comma-delimited list of strings representing Namespaces to search. Each string must be wrapped in double quotes. For example, "default","kube-system".

      If you don’t want to search for Services in the Namespace Grafana Agent Flow is running in, set own_namespace to false.

    3. To use a field selector to limit the number of discovered Services, add the following block inside the discovery.kubernetes component.

      river
      selectors {
        role  = "service"
        field = "<FIELD_SELECTOR>"
      }

      Replace the following:

      • <FIELD_SELECTOR>: The Kubernetes field selector, such as metadata.name=my-service. For more information on field selectors, refer to the Kubernetes documentation on Field Selectors.

      Create additional selectors blocks for each field selector you want to apply.

    4. To use a label selector to limit the number of discovered Services, add the following block inside the discovery.kubernetes component.

      river
      selectors {
        role  = "service"
        label = "<LABEL_SELECTOR>"
      }

      Replace the following:

      • <LABEL_SELECTOR>: The Kubernetes label selector, such as environment in (production, qa). For more information on label selectors, refer to the Kubernetes documentation on Labels and Selectors.

      Create additional selectors blocks for each label selector you want to apply.

  3. Collect metrics from discovered Services:

    1. Add the following prometheus.scrape component to your configuration file.

      river
      prometheus.scrape "<SCRAPE_LABEL>" {
        targets    = discovery.kubernetes.<DISCOVERY_LABEL>.targets
        forward_to = [prometheus.remote_write.<REMOTE_WRITE_LABEL>.receiver]
      }

      Replace the following:

      • <SCRAPE_LABEL>: The label for the component, such as services. The label you use must be unique across all prometeus.scrape components in the same configuration file.
      • <DISCOVERY_LABEL>: The label for the discovery.kubernetes component.
      • <REMOTE_WRITE_LABEL>: The label for your existing prometheus.remote_write component.

The following example demonstrates configuring Grafana Agent Flow to collect metrics from running production Kubernetes Services in the default Namespace.

river
discovery.kubernetes "services" {
  role = "service"

  namespaces {
    own_namespace = false

    names = ["default"]
  }

  selectors {
    role  = "service"
    label = "environment in (production)"
  }
}

prometheus.scrape "services" {
  targets    = discovery.kubernetes.services.targets
  forward_to = [prometheus.remote_write.default.receiver]
}

prometheus.remote_write "default" {
  endpoint {
    url = "http://localhost:9090/api/prom/push"
  }
}

For more information on configuring Kubernetes service delivery and collecting metrics, refer to discovery.kubernetes and prometheus.scrape.

Collect metrics from custom targets

You can configure Grafana Agent Flow to collect metrics from a custom set of targets without the need for service discovery.

To collect metrics from a custom set of targets, complete the following steps.

  1. Follow Configure metrics delivery to ensure collected metrics can be written somewhere.

  2. Add the following prometheus.scrape component to your configuration file:

    river
    prometheus.scrape "<SCRAPE_LABEL>" {
      targets    = [<TARGET_LIST>]
      forward_to = [prometheus.remote_write.<REMOTE_WRITE_LABEL>.receiver]
    }

    Replace the following:

    • _<SCRAPE_LABEL>: The label for the component, such as custom_targets. The label you use must be unique across all prometheus.scrape components in the same configuration file.

    • <TARGET_LIST>: A comma-delimited list of Objects denoting the Prometheus target. Each object must conform to the following rules:

      • There must be an __address__ key denoting the HOST:PORT of the target to collect metrics from.
      • To explicitly specify which protocol to use, set the __scheme__ key to "http" or "https". If the __scheme__ key isn’t provided, the protocol to use is inherited by the settings of the prometheus.scrape component. The default is "http".
      • To explicitly specify which HTTP path to collect metrics from, set the __metrics_path__ key to the HTTP path to use. If the __metrics_path__ key isn’t provided, the path to use is inherited by the settings of the prometheus.scrape component. The default is "/metrics".
      • Add additional keys as desired to inject extra labels to collected metrics. Any label starting with two underscores (__) will be dropped prior to scraping.
    • <REMOTE_WRITE_LABEL>: The label for your existing prometheus.remote_write component.

The following example demonstrates configuring prometheus.scrape to collect metrics from a custom set of endpoints.

river
prometheus.scrape "custom_targets" {
  targets = [
    {
      __address__ = "prometheus:9090",
    },
    {
      __address__ = "mimir:8080",
      __scheme__  = "https",
    },
    {
      __address__      = "custom-application:80",
      __metrics_path__ = "/custom-metrics–path",
    },
    {
      __address__ = "grafana-agent:12345",
      application = "grafana-agent",
      environment = "production",
    },
  ]

  forward_to = [prometheus.remote_write.default.receiver]
}

prometheus.remote_write "default" {
  endpoint {
    url = "http://localhost:9090/api/prom/push"
  }
}