Docs » Get started with the Splunk Distribution of the OpenTelemetry Collector » Collector components » Collector components: Connectors » Span Metrics connector

Span Metrics connector 🔗

The Splunk Distribution of the OpenTelemetry Collector uses the Span Metrics connector to aggregate requests, errors and duration (R.E.D) OpenTelemetry metrics from span data.

As an exporter, the supported pipeline type is traces. As a receiver, the supported pipeline type is metrics. See Process your data with pipelines for more information.

Overview 🔗

The connector pulls span data and aggregates them into Request, Error and Duration (R.E.D) OpenTelemetry metrics.

Requests 🔗

Request counts are computed as the number of spans seen per unique set of dimensions, including Errors. Multiple metrics can be aggregated if, for instance, you wish to view call counts just on service.name and span.name.

calls{service.name="shipping",span.name="get_shipping/{shippingId}",span.kind="SERVER",status.code="Ok"}

Errors 🔗

Error counts are computed from the Request counts which have an Error Status Code metric dimension.

calls{service.name="shipping",span.name="get_shipping/{shippingId},span.kind="SERVER",status.code="Error"}

Duration 🔗

Duration is computed from the difference between the span start and end times and inserted into the relevant duration histogram time bucket for each unique set dimensions.

duration{service.name="shipping",span.name="get_shipping/{shippingId}",span.kind="SERVER",status.code="Ok"}

Common dimensions for metrics 🔗

Each metric has at least the following dimensions because they are common across all spans:

  • service.name

  • span.name

  • span.kind

  • status.code

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 connector as described in the next section.

  2. Restart the Collector.

Sample configuration 🔗

To activate the resource processor, add spanmetrics to the connectors section of your configuration file.

For example:

receivers:
  nop:

exporters:
  nop:

connectors:
  spanmetrics:
    histogram:
      explicit:
        buckets: [100us, 1ms, 2ms, 6ms, 10ms, 100ms, 250ms]
    dimensions:
      - name: http.method
        default: GET
      - name: http.status_code
    exemplars:
      enabled: true
    exclude_dimensions: ['status.code']
    dimensions_cache_size: 1000
    aggregation_temporality: "AGGREGATION_TEMPORALITY_CUMULATIVE"
    metrics_flush_interval: 15s
    metrics_expiration: 5m
    events:
      enabled: true
      dimensions:
        - name: exception.type
        - name: exception.message
    resource_metrics_key_attributes:
      - service.name
      - telemetry.sdk.language
      - telemetry.sdk.name

To complete the configuration, in the service section of your configuration file, include the connector as an exporter in the traces pipeline and as a receiver in the metrics pipeline.

For example:

service:
  pipelines:
    traces:
      receivers: [nop]
      exporters: [spanmetrics]
    metrics:
      receivers: [spanmetrics]
      exporters: [nop]

Configuration options 🔗

The following settings can be optionally configured:

  • histogram. explicit by default. Use it to configure the type of histogram to record calculated from spans duration measurements. Must be either explicit or exponential.

    • disable. false by default. Disables all histogram metrics.

    • unit. ms by default. The time unit for recording duration measurements, calculated from spans duration measurements. Possible values ar ms or s.

    • explicit:

      • buckets. The list of durations defining the duration histogram time buckets. Default buckets: [2ms, 4ms, 6ms, 8ms, 10ms, 50ms, 100ms, 200ms, 400ms, 800ms, 1s, 1400ms, 2s, 5s, 10s, 15s].

    • exponential:

      • max_size. 160 by default. The maximum number of buckets per positive or negative number range.

  • dimensions. The list of dimensions to add together with the default dimensions defined above.

    • Each additional dimension is defined with a name which is looked up in the span’s collection of attributes or resource attributes (process tags) such as ip, host.name or region.

    • If the named attribute is missing in the span, the optional provided default is used.

    • If no default is provided, this dimension will be omitted from the metric.

  • exclude_dimensions. The list of dimensions to be excluded from the default set of dimensions. Use to exclude unneeded data from metrics.

  • dimensions_cache_size. 1000 by default. The size of cache for storing Dimensions to improve Collectors’ memory usage. Must be a positive number.

  • resource_metrics_cache_size. 1000 by default. The size of the cache holding metrics for a service. This is mostly relevant for cumulative temporality to avoid memory leaks and correct metric timestamp resets.

  • aggregation_temporality. AGGREGATION_TEMPORALITY_CUMULATIVE by default. Defines the aggregation temporality of the generated metrics. Possible values are AGGREGATION_TEMPORALITY_CUMULATIVE or AGGREGATION_TEMPORALITY_DELTA.

  • namespace. Defines the namespace of the generated metrics. If a namespace’s provided, the prefix namespace. is added to the generated metric name.

  • metrics_flush_interval. 60 by default. Defines the flush interval of the generated metrics.

  • metrics_expiration. 0 by default. Defines the expiration time as time.Duration, after which, if no new spans are received, metrics will no longer be exported. If you set it to 0 metrics will never expire.

  • exemplars. Use them to configure how to attach exemplars to metrics.

    • enabled. faulse by default. Enabling it will add spans as Exemplars to all metrics. Exemplars are only kept for one flush interval.

  • events. Use it to configure the events metric.

    • enabled. false by default. Enabling it adds the events metric.

    • dimensions: Mandatory if events is enabled. The list of the span’s event attributes to add as dimensions to the events metric, which will be included on top of the common and configured dimensions for span and resource attributes.

  • resource_metrics_key_attributes. Filter the resource attributes used to produce the resource metrics key map hash. Use this in case changing resource attributes (e.g. process id) are breaking counter metrics.

Migrate from the Span Metrics processor to the Span Metrics connector 🔗

The spanmetrics connector is a port of the Span processor, but with multiple improvements and breaking changes. It was done to bring the spanmetrics connector closer to the OpenTelemetry specification and make the component agnostic to exporters logic.

The connector comes with the following changes:

  • The operation metric attribute is renamed to span.name.

  • The latency histogram metric name is changed to duration.

  • The _total metric prefix was dropped from generated metrics names.

  • The Prometheus-specific metrics labels sanitization was dropped.

Other improvements include:

  • Added support for OTel exponential histograms for recording span duration measurements.

  • Added support for the milliseconds and seconds histogram units.

  • Added support for generating metrics resource scope attributes. The spanmetrics connector generates the number of metrics resource scopes that corresponds to the number of the spans resource scopes, so it generates more metrics. Previously, spanmetrics generated a single metrics resource scope.

Use the Span Metrics connector with Prometheus components 🔗

The spanmetrics connector can be used with Prometheus exporter components such as Prometheus receiver.

For some functionality of the exporters, for example, to generate the target_info metric, the incoming spans resource scope attributes must contain the service.name and service.instance.id attributes.

Let’s look at the example of using the spanmetrics connector with the prometheusremotewrite exporter:

receivers:
  otlp:
    protocols:
      http:
      grpc:

exporters:
  prometheusremotewrite:
    endpoint: http://localhost:9090/api/v1/write
    target_info:
      enabled: true

connectors:
  spanmetrics:
    namespace: span.metrics

service:
  pipelines:
    traces:
      receivers: [otlp]
      exporters: [spanmetrics]
    metrics:
      receivers: [spanmetrics]
      exporters: [prometheusremotewrite]

This configures the spanmetrics connector to generate metrics from received spans and export those metrics to the Prometheus Remote Write exporter. The target_info metric is generated for each resource scope, while OpenTelemetry metric names and attributes are normalized to be compliant with Prometheus naming rules.

For example, the generated calls OTel sum metric can result in multiple Prometheus calls_total (counter type) time series and the target_info time series. See below:

target_info{job="shippingservice", instance="...", ...} 1
calls_total{span_name="/Address", service_name="shippingservice", span_kind="SPAN_KIND_SERVER", status_code="STATUS_CODE_UNSET", ...} 142

Settings 🔗

The following table shows the configuration options for the spanmetrics connector:

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.

To learn about even more support options, see Splunk Customer Success .