Docs » Get started with the Splunk Distribution of the OpenTelemetry Collector » Collector components » Collector components: Processors » Metrics generation processor

Metrics generation processor 🔗

The Splunk Distribution of the OpenTelemetry Collector uses the Metrics Generation processor to create new metrics using existing metrics following a given rule.

This processor currently supports the following two rule types for creating a new metric:

  • calculate. Creates a new metric from two existing metrics by applying one of the following arithmetic operations: add, subtract, multiply, divide, or percent.

    • For example, use it to calculate the pod.memory.utilization metric with the equation pod.memory.utilization = (pod.memory.usage.bytes / node.memory.limit.

    • Learn more at Using the calculate rule.

  • scale. Creates a new metric by scaling the value of an existing metric with a given constant number.

    • For example, use it to convert pod.memory.usage metric values from Megabytes to Bytes by multiplying the existing metric’s value by 1,048,576.

Get started 🔗

Follow these steps to configure and activate the component:

  1. Deploy the Splunk Distribution of the OpenTelemetry Collector to your host or container platform:

  1. Configure the metricsgeneration processor as described in the next section.

  2. Restart the Collector.

Sample configuration 🔗

To activate the resource processor, add metricsgeneration to the processors section of your configuration file. Specify the configuration using a list of generation rules. Generation rules find the metrics which match the given metric names and apply the specified operation to those metrics. For example:

processors:
  metricsgeneration:
      # specify the metric generation rules
      rules:
            # Name of the new metric. This is a required field.
          - name: <new_metric_name>

            # Unit for the new metric being generated.
            unit: <new_metric_unit>

            # type describes how the new metric will be generated. It can be one of `calculate` or `scale`.  calculate generates a metric applying the given operation on two operand metrics. scale operates only on operand1 metric to generate the new metric.
            type: {calculate, scale}

            # This is a required field. This must be a gauge or sum metric.
            metric1: <first_operand_metric>

            # This field is required only if the type is "calculate". When required, this must be a gauge or sum metric.
            metric2: <second_operand_metric>

            # Operation specifies which arithmetic operation to apply. It must be one of the five supported operations.
            operation: {add, subtract, multiply, divide, percent}

To complete the configuration, include the processor in the metrics pipeline of the service section of your configuration file. For example:

service:
  pipelines:
    metrics:
      processors: [metricsgeneration]

Configuration example: Create a new metric using two existing metrics 🔗

This example creates the new metric pod.cpu.utilized dividing pod.cpu.usage and node.cpu.limit.

rules:
    - name: pod.cpu.utilized
      type: calculate
      metric1: pod.cpu.usage
      metric2: node.cpu.limit
      operation: divide

Configuration example: Create a new metric scaling the value of an existing metric 🔗

This example creates the new metric pod.memory.usage.bytes from the metric pod.memory.usage.megabytes.

rules:
    - name: pod.memory.usage.bytes
      unit: Bytes
      type: scale
      metric1: pod.memory.usage.megabytes
      operation: multiply
      scale_by: 1048576

Using the calculate rule 🔗

Keep in mind the following specific behaviors of the calculate metric generation rule:

  • The created metric has the same type as the metric configured as the first metric.

  • If the metric being created doesn’t have any valid data points it will not be created. This ensures the processor doesn’t emit empty new metrics.

  • If you want to have metric calculations done on data points whose overlapping attributes match, enable the feature gate metricsgeneration.MatchAttributes. This feature gate is disabled by default, meaning the value used for the second metric during the calculations is simply the first data point’s value.

Settings 🔗

The following table shows the configuration options for the metricsgeneration processor:

Troubleshooting 🔗

If you are a Splunk Observability Cloud customer and are not able to see your data in Splunk Observability Cloud, you can get help in the following ways.

Available to Splunk Observability Cloud customers

Available to prospective customers and free trial users

  • Ask a question and get answers through community support at Splunk Answers .

  • Join the Splunk #observability user group Slack channel to communicate with customers, partners, and Splunk employees worldwide. To join, see Chat groups in the Get Started with Splunk Community manual.

This page was last updated on Feb 04, 2025.