Documentation Grafana Cloud Monitor infrastructure Kubernetes Monitoring Configure Kubernetes Monitoring Configure with Helm chart Application metrics

Scrape and forward application metrics

When you have an application that exports metrics on your Kubernetes Cluster, you can scrape and forward these metrics to Grafana Cloud. To do so, you can extend the configuration in the Grafana Kubernetes Helm chart.

When you are adding a new configuration, it’s helpful to think of it in the following phases:

1. Discovery: How should the collector find my service?
2. Scraping: How should metrics get scraped from my service?
3. Processing: Is there any work that needs to be done to these metrics?
4. Delivery: Where should these metrics be sent?

Discovery

In the discovery phase, you must find the specific Pod or service you want to scrape for metrics. The Grafana Kubernetes Helm chart automatically creates these components that you can use:

• discovery.kubernetes.nodes: Discovers all Nodes in the Cluster.
• discovery.kubernetes.services: Discovers all services in the Cluster.
• discovery.kubernetes.endpoints: Discovers all service endpoints in the Cluster.
• discovery.kubernetes.pods: Discovers all pods in the Cluster.

These are all discovery.kubernetes components, which use the Kubernetes API to gather all the specific resources. Then you want to refine the search to only the service or Pod that you want.

Service discovery

Since you don’t want to scrape every service in your Cluster, you use rules to select your specific service based on its name, namespace, labels, port names, numbers, and many other variables. To do this:

1. Use a discovery.relabel component.
2. Add one or more rules by using special meta-labels that are set automatically by the discovery.kubernetes component.

The following is an example component named blue_database_service. This component takes the list of all services from discovery.kubernetes.services, and filters to a service named “database” in the namespace “blue” with the port named “metrics”:

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discovery.relabel "blue_database_service" {
  targets = discovery.kubernetes.services.targets  // Gets all services
  rule {  // Keep all services named "database"...
    source_labels = ["__meta_kubernetes_service_name"]
    regex = "database"
    action = "keep"
  }
  rule {  // ... that exist in the "blue" namespace...
    source_labels = ["__meta_kubernetes_namespace"]
    regex = "blue"
    action = "keep"
  }
  rule {  // ... and only scrape its port named "metrics".
    source_labels = ["__meta_kubernetes_service_port_name"]
    regex = "metrics"
    action = "keep"
  }
}

The discovery.kubernetes documentation lists the meta labels for services.

This is also a good point in the process to add any extra labels you want to scrape. For example, if to set the label team="blue", you could use this additional rule in the blue_database_service component that was just made:

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rule {
  target_label = "team"
  action = "replace"
  replacement = "blue"
}

Pod discovery

Similar to service discovery, you can use a discovery.relabel component to select the specific Pod or Pods that you want to scrape. The meta labels for Pods are slightly different, but the concept is the same.

The following example filters to a specific set of Pods that begins with the name “analysis”, with the label “system.component=image”:

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discovery.relabel "image_analysis_pods" {
  targets = discovery.kubernetes.pods.targets  // Gets all pods
  rule {  // Keep all pods named "analysis.*"...
    source_labels = ["__meta_kubernetes_pod_name"]
    regex = "analysis.*"
    action = "keep"
  }
  rule {  // ... with the label system.component=image
    source_labels = ["__meta_kubernetes_pod_label_system_component"]
    regex = "image"
    action = "keep"
  }
}

Scraping

To scrape the specific Pod or service you want for metrics, use the prometheus.scrape component. Declare which items to scrape and where to send the scraped metrics, as in the following example:

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prometheus.scrape "processing_app" {
  targets = discovery.relabel.image_analysis_pods.output
  forward_to = [prometheus.remote_write.metrics_service.receiver]
}

(The forward_to field is covered in the Delivery section that follows the Processing section.)

The prometheus.scrape component offers many options to modify how to scrape the data, including:

• Setting the job label
• Frequency of scraping the metrics
• The path to scrape

The following is an example showing several of these options:

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prometheus.scrape "processing_app" {
  targets = discovery.relabel.image_analysis_pods.output
  job_name = "integrations/processing"
  scrape_interval = "120s"
  metrics_path = "/api/v1/metrics"
  forward_to = [prometheus.remote_write.metrics_service.receiver]
}

Processing

You may often want to process the metrics after scraping. Some common reasons are:

• To limit the amount of metrics being sent to Prometheus
• To add, change, or drop labels

For processing, use the prometheus.relabel component. This component uses the same type of rules as discovery.relabel. However, instead of filtering scrape targets, it filters the metrics that were scraped.

The following processing example filters the scraped metrics to drop all other metrics except:

• up
• Anything that starts with processor

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prometheus.scrape "processing_app" {
  targets = discovery.relabel.image_analysis_pods.output
  forward_to = [prometheus.relabel.processing_app.receiver]
}

prometheus.relabel "processing_app" {
  rule {
    source_labels = ["__name__"]
    regex = "up|processor.*"
    action = "keep"
  }
  forward_to = [prometheus.remote_write.metrics_service.receiver]
}

Delivery

The prometheus.scrape and prometheus.relabel components must send their outputs to another component, which is the purpose of their forward_to field. Forwarding can be to another prometheus.relabel component. Eventually, the final step is to send the metrics to a Prometheus server for storage, where it can be either:

• Further processed by recording rules
• Queried and displayed by Grafana

Use the prometheus.remote_write component to send outputs.

The Grafana Kubernetes Helm chart automatically creates the component prometheus.remote_write.metrics_service, configured by the .externalServices.prometheus values. You can use this component to send your metrics to the same destination as the infrastructure metrics.

If you want to use a different destination, create a new prometheus.remote_write component.

Include configuration in Helm chart

To include your configuration in the Grafana Kubernetes Helm chart, save the following into a file and pass it directly to the helm install command:

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$ ls
processor-config.river chart-values.yaml
$ cat processor_config.river
discovery.relabel "image_analysis_pods" {
  targets = discovery.kubernetes.pods.targets  // Gets all pods
  rule {  // Keep all pods named "analysis.*"...
    source_labels = ["__meta_kubernetes_pod_name"]
    regex = "analysis.*"
    action = "keep"
  }
  rule {  // ... with the label system.component=image
    source_labels = ["__meta_kubernetes_pod_label_system_component"]
    regex = "image"
    action = "keep"
  }
}

prometheus.scrape "processing_app" {
  targets = discovery.relabel.image_analysis_pods.output
  forward_to = [prometheus.relabel.processing_app.receiver]
}

prometheus.relabel "processing_app" {
  rule {
    source_labels = ["__name__"]
    regex = "up|processor.*"
    action = "keep"
  }
  forward_to = [prometheus.remote_write.metrics_service.receiver]
}
$ helm install k8s-monitoring grafana/k8s-monitoring --values chart-values.yaml --set-file extraConfig=processor-config.river