Analyze your metrics with Usage Analytics

Use usage analytics to determine the usage of your metrics in Splunk Observability Cloud.

View and understand your metrics usage

The Metrics tab in Usage Analytics provides interactive charts and visual summaries that show how your metrics contribute to your overall usage relative to your subscription plan. You can inspect individual metrics to see which dimensions they include, which tokens they are linked to, and how they are used across dashboards and charts. Usage Analytics provides deeper insights into each metric's context, including its associated dimensions, tokens, and visualizations.

The summary cards show the average hourly metric time series (MTS) count for the selected time period and its trend over time. The Reduce your custom metrics usage card estimates the total MTS reduction from removing metrics and dimensions that have been unused for the last 7 days. The table includes a Potential MTS reduction column for each metric.

Understand metric usage with the metrics table

The metric usage table displays the following fields:

Field

Description

Metric name

The name of the metric.

Billing class

Class of metric for billing purposes. Usage analytics doesn't show APM Monitoring MetricSets, RUM Monitoring MetricSets or tracing metrics.

To learn more about billing classes, see Metric categories.

Data route

The data route path for the metric. You can filter this column to view metrics routed as real-time or archived, depending on how they are processed.

Utilization

Indicates how much the metric is used across your environment. Each metric may appear in multiple Observability Cloud components, but in the Utilization column, it is associated with the highest rank in which it is used. This does not mean the metric is used only in that one component.

For more details, see the following list:

  • R4 – Detectors: The metric is referenced in detectors.

  • R3 – Active charts: The metric is referenced in active charts. An active chart is a chart that has been viewed in the given time period.

  • R2 – API queries: The metric is referenced in an API query.

  • R1 – Inactive charts: The metric is referenced in an inactive chart. This is a chart that hasn't been viewed in the given time period.

  • R0 – Unused: The metric isn't used

Example: If a metric is referenced in both inactive and active charts, Usage Analytics assigns the metric to the highest applicable utilization rank. In this case, the metric would be marked as used in active charts.

Detectors

The number of detectors that reference this metric.

Active chart

The number of active charts that reference this metric.

API queries

The number of API queries that reference this metric.

Inactive charts

The number of inactive charts that reference this metric.

Metric time series (MTS)

The average number of MTS associated with this metric, measured per hour.

Note:

Percentage over total

How much of your total MTS usage this metric utilizes.

Potential MTS reduction

Estimated MTS reduction after:

  • archiving or dropping a metric if it is not used
  • aggregating all unused dimensions if the metric is still in use
Note: The estimate is based on MTS counts from the last hour and is calculated only for metrics in the Custom billing class. Metrics that are already archived or aggregated are also excluded from recommendations.
Note: The table is refreshed every hour, and newly ingested data becomes visible shortly after. If you archive a metric, you will see changes in MUA within one hour.

Show hidden utilization columns

Detectors, active charts, API queries, and inactive charts columns are hidden by default. To show them, follow these steps:

  1. Select Settings in the usage analytics table.

  2. Under Show/Hide Columns, select each utilization column to show in the table.

Note: You can choose to show all utilization columns at once by selecting the Utilization line, or display specific ones individually by selecting the corresponding lines (e.g., Detectors, Active charts, etc.).

Filtering metrics by utilization

You can filter metrics in the usage analytics table to focus on specific utilization levels, such as unused metrics, actively referenced metrics, or those tied to detectors and API queries.

To apply a utilization filter:

  1. Select the filter box labeled Utilization: Any at the top of the page.

  2. From the dropdown menu, select the desired utilization level (e.g., Unused, R3 – Active charts, R4 – Detectors).

  3. Select Run search to apply the filter.

The table will update to show only metrics matching the selected criteria. To clear the filter and return to the full view, select Reset.

Note: Searches with broader filters—such as selecting the last 30 days instead of the last 24 hours—may take longer to complete.

Metric profile: contents and structure

Usage Analytics includes a detailed profile for each metric, helping you understand how it is structured and used across your environment. To access a metric profile, select any metric directly from the metric usage table.

Within the profile view, you can filter the data by Billing class and Time period to narrow down the scope of analysis.

Each metric profile provides insights into:

  • Total number of associated metric time series (MTS)
  • Percentage of total MTS the metric represents
  • Estimated potential MTS reduction for this metric
  • Related tokens and dimensions
  • Referencing charts and detectors

This information helps you assess the scope, relevance, and optimization potential of each metric within your system.

Metric profile data is organized into four separate tables, each focusing on a different aspect of metric usage:

Table

Description

Notes

Dimensions

Lists the dimension names associated with the metric, sorted by average hourly dimension value, maximum hourly dimension value and sample value. High-cardinality dimensions appear at the top. For metrics in the Custom billing class, the table also shows the estimated potential MTS reduction from removing individual dimensions from the metric.

Displays up to 10 000 results.

Tokens

Lists token names and IDs, sorted by the number of metric time series (MTS) associated with each token.

Displays up to 10 000 results.

Charts

Shows charts and dashboards that reference the metric, along with the user who last updated each chart and the time of the update.

Displays up to 10 000 results.

Detectors

Shows detectors that reference the metric, along with the user who last updated each detector and the time of the update.

Displays up to 10 000 results.

Manage and reduce your custom metrics usage

Usage Analytics provides potential MTS reduction estimates that show how much you could reduce your overall custom metric usage. To achieve this reduction, follow these steps:

  1. Archive or drop metrics that are no longer in use.

  2. Aggregate dimensions in metrics that are still in use.

Archive or drop unused metrics

Using the metrics table, you can find metrics that aren't used. If you have any unused metrics, you can archive them so they take up less of your usage plan.

  • Archived metrics are routed to an archival path in Splunk Observability Cloud, where they remain inactive and incur lower billing costs. You can restore them at any time if needed.
  • If you don't plan to use certain metrics in the future, consider dropping them entirely to free up usage capacity.

  • Enable automated archival to archive metrics that are no longer in use.

To learn more:

Aggregate dimensions in metrics that are still in use

After addressing unused metrics, use the Metrics or Dimensions tabs to review potential MTS reductions for metrics that are still in use:

Metrics tab
  1. Filter by metrics that are in use, then sort by the Potential MTS reduction column.
  2. Open a metric profile to compare the potential reduction for its individual dimensions.
  3. Review the metric's Detectors and Charts tabs to understand how it is used before creating aggregation rules.
  4. Select Create rules from the metric profile to open the aggregation flow. Dimensions with no usage in the last 7 days are preselected; review or change the selection before creating a rule.
  5. Handle the original metric. When the aggregated metric is ready (without specified dimensions), archive or drop the original metric.
Dimensions tab
  1. Sort dimensions by Potential MTS reduction to find those with the greatest estimated impact.
  2. Select a dimension to see which metrics include it.
  3. Create a separate rule for each metric where you want to aggregate a dimension. You cannot remove a dimension globally.

To learn more, see Use aggregation rules to control your data volume.