Analyze your dimensions with Usage Analytics

Use the Dimensions tab in Usage Analytics to explore how contextual dimensions affect your metric footprint.

View and explore your dimensional usage

The Dimensions tab in Usage Analytics provides interactive charts and detailed tables that reveal how contextual dimensions contribute to your overall metric footprint. It’s designed to help you assess dimensional cardinality, distribution, and usage across your environment.

A summary card displays the total number of dimensions and their unique values, offering a quick snapshot of dimensional richness. A trend chart shows how the number of dimensional values changes over time, helping you spot growth patterns or anomalies. The card also shows the estimated MTS reduction you could achieve by aggregating all unused dimensions in Custom metrics that remain in use.

The core of the tab is the dimensions table, which lists each dimension alongside key usage indicators:

  • Presence in detectors, dashboards, charts, and API queries
  • Number of unique values and their share of total dimensional values
  • Contribution to metric time series (MTS) volume
  • Potential MTS reduction from aggregating dimensions across metrics in the Custom billing class
  • Association with specific metrics

You can sort and filter the table to focus on dimensions with high cardinality, broad usage, or optimization potential. Sort by Potential MTS reduction to find dimensions with the greatest estimated impact. Selecting a dimension opens a detailed profile.

Note: Custom properties are not listed as separate dimensions in the main dimensions table. To view the properties and tags associated with a dimension, open its profile and select the Properties or Tags tab.

Understand dimensions usage with the dimensions table

The dimension usage table displays the following fields:

Field

Description

Dimension name

The name of the dimension.

Utilization

Indicates how a dimension is used across your environment. Each dimension 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 dimension is used only in that one component.

Example: If a dimension is referenced in both inactive charts and dashboards filters, Usage Analytics assigns the dimension with the highest applicable utilization rank. In this case, the dimension would be marked as used in dashboard filters.

For more details, see the following list:

  • R5 – Detectors: The dimension is referenced in detectors.

  • R4 – Dashboard filters: The dimension is referenced as a filter on the top of your dashboards.

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

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

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

  • R0 – Unused: The dimension isn't used.

Note: Utilization at the dimension level includes the use of properties and tags associated with that dimension. If an associated property or tag is used, the dimension is marked as used. The Utilization column does not distinguish whether the usage comes from the dimension itself, a specific property, or a specific tag.

For example, if a property or tag associated with a dimension is used, Usage Analytics marks the dimension as used. It does not identify the specific property or tag responsible for that status.

Detectors Indicates the number of detectors in which this dimension is used, as a part of the metric.
Dashboard filters Number of dashboards where this dimension is used as a top filter. This usage is independent of any metric context.
Active chart Indicates the number of active charts in which this dimension is used, as a part of the metric. An active chart is one that has been viewed in the given time period.
API queries Indicates the number of API queries that reference this dimension.
Inactive charts Indicates the number of inactive charts in which this dimension is used, as a part of the metric. An inactive chart is one that hasn't been viewed in the given time period.
Unique values The average number of unique dimensional values per hour.
Percentage of total values The average number of dimensional values (for the given dimension) over the total number of all dimension values per hour.
Metrics with dimension The average number of metrics with the dimension per hour.
MTS with dimension The average number of MTS with the dimension per hour.
Percentage of total MTS The average number of MTS with the given dimension over the total number of all MTS per hour.
Potential MTS reduction

Estimated MTS reduction after removing this dimension from all metrics where it is not used.

Note: The estimate is based on MTS counts from the last hour and is calculated only for metrics in the Custom billing class. Internal dimensions are excluded from recommendations.

Show hidden utilization columns

The dimensions table includes several detailed utilization columns: Detectors, Dashboard filters, Active charts, API queries, and Inactive charts which are hidden by default. These columns are designed to provide a quick, high-level view of how often each dimension is used within each component, helping decide whether to explore a dimension in more detail and identify underutilized or high-impact dimensions.

To display them:

  1. Select Settings in the usage analytics table.

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

Filtering dimensions by utilization

You can filter dimensions in the usage analytics table to focus on specific utilization levels, such as unused dimensions, actively referenced dimensions, 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 and charts will update to show only dimensions 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.

Dimensions profile: contents and structure

Usage Analytics includes dimension profiles for each of your dimensions. These profiles provide a comprehensive view of how a dimension is used across your environment and how it contributes to your metric footprint.

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

To access a dimension profile, select any dimension directly from the dimensions table.

Each dimension profile includes the following tables:

Table

Description

Notes

Metrics

This tab provides the primary interface for managing dimensions. Dimensions cannot be removed globally; they can only be removed within the context of a specific metric. By selecting the Settings icon next to a metric and choosing Aggregate dimension, you'll be redirected to Metric Pipeline Management (MPM), where you can remove the dimension from that metric.

The Dimension utilization column in this tab shows how the selected dimension is used specifically within each listed metric — for example, whether it's used in detectors, charts, or API queries. The Potential MTS reduction column estimates the reduction for aggregating the dimension in each metric. This contextual view helps identify optimization opportunities at the metric level.

Displays up to 10 000 results.

Dashboard filters

Lists dashboards where the dimension is used as a filter, along with the user who last updated each dashboard and the time of the update.

Displays up to 10 000 results.

Charts

Displays dashboards containing charts that reference the dimension, including the user who last updated each chart and the timestamp of the update.

Displays up to 10 000 results.

Detectors

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

Displays up to 10000 results.

Sample values Shows a selection of values for the dimension. Displays up to 10 randomly selected values per dimension.

Properties

Lists all properties associated with the selected dimension.

Displays up to 10 000 results.

Tags

Lists all tags associated with the selected dimension.

Displays up to 10 000 results.

Note: To narrow down long lists of charts and detectors, enter a metric name in the search bar. Since dimensions are always used within metrics in these two components, this helps you identify where a specific dimension is used in context. Note that this behavior does not apply to dashboard filters. Currently, each search bar supports filtering results based on up to 10,000 metrics.

Manage and reduce your dimensions usage

This section provides practical strategies for identifying dimensions that can be aggregated, archived, or dropped to help reduce your overall metric time series (MTS) volume and simplify your environment.

Aggregate unused dimensions

Using the dimensions table, you can find dimensions that aren't actively used in detectors, charts, dashboard filters, or API queries. If you have unused dimensions, consider dropping or aggregating them to reduce your usage footprint and simplify your environment.

To decide whether to aggregate a dimension:

  1. Sort the dimensions table by the Potential MTS reduction column, then select a dimension to open its profile.
  2. Identify metrics where the dimension is not actively used — these can be safely excluded.

  3. For metrics where the dimension is in use,review the Detectors and Charts tabs to check where the dimension is used.
  4. If appropriate, create a separate aggregation rule for each metric where you want to remove the dimension. You cannot remove a dimension globally.

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

Consider rerouting part of your metric to the archived data route

If you're unsure whether to drop or keep a dimension, consider archiving the entire metric and creating an exception rule. This rule will allow metrics with dimensions you're confident about to remain in the real-time data route.

To learn more, see Use routing exception rules to route a specific MTS or restore archived data.