opensearch-docs-cn/_data-prepper/common-use-cases/metrics-traces.md

layout	title	parent	nav_order
default	Deriving metrics from traces	Common use cases	20

Deriving metrics from traces

You can use Data Prepper to derive metrics from OpenTelemetry traces. The following example pipeline receives incoming traces and extracts a metric called durationInNanos, aggregated over a tumbling window of 30 seconds. It then derives a histogram from the incoming traces.

The pipeline contains the following pipelines:

• entry-pipeline – Receives trace data from the OpenTelemetry collector and forwards it to the trace_to_metrics_pipeline pipeline.

• trace-to-metrics-pipeline - Receives the trace data from the entry-pipeline pipeline, aggregates it, and derives a histogram of durationInNanos from the traces based on the value of the serviceName field. It then sends the derived metrics to the OpenSearch index called metrics_for_traces.

entry-pipeline:
  source:
    otel_trace_source:
      # Provide the path for ingestion. ${pipelineName} will be replaced with pipeline name.
      # In this case it would be "/entry-pipeline/v1/traces". This will be endpoint URI path in OpenTelemetry Exporter configuration.
      path: "/${pipelineName}/v1/traces"
  sink:
    - pipeline:
        name: "trace-to-metrics-pipeline"

trace-to-metrics-pipeline:
  source:
    pipeline:
      name: "entry-pipeline"
  processor:
    - aggregate:
        # Pick the required identification keys
        identification_keys: ["serviceName"]
        action:
          histogram:
            # Pick the appropriate values for each of the following fields
            key: "durationInNanos"
            record_minmax: true
            units: "seconds"
            buckets: [0, 10000000, 50000000, 100000000]
        # Specify an aggregation period
        group_duration: "30s"
  sink:
    - opensearch:
        ...
        index: "metrics_for_traces"

{% include copy-curl.html %}