Usage Analytics in Splunk Observability Cloud

Analyze metric time series and dimensional distributions to optimize usage and reduce overhead.

Use Usage Analytics in Splunk Observability Cloud to you monitor, analyze, and optimize your metric usage. Usage Analytics provides:

Note: Usage Analytics and subscription usage might vary. Usage Analytics data are estimated in a different resolution than billing data and reflect your full ingestion data without application throttling. Use Usage Analytics to identify your cost contributors and areas for cost optimization. For the accurate view of your subscription usage, refer to the Subscription Overview.

Access usage analytics

To view Usage Analytics in Splunk Observability Cloud, select Metrics in the navigation menu, then select Usage analytics from the panel.
  • Data on the Usage Analytics pages is refreshed every hour.
  • Usage Analytics does not include APM Monitoring MetricSets, RUM Monitoring MetricSets, or tracing metrics.

Note: If you send too many queries in a short period of time, a rate limiting message might appear. If this happens, wait 2 minutes and refresh the page.

Use the Metrics and Dimensions tabs to manage telemetry data

Use the Metrics and Dimensions tabs to manage telemetry data, reduce volume, improve system efficiency, optimize cost of linked Metrics Pipeline Management and Metrics Pipeline Automation.

To help you optimize usage, Usage Analytics offers 2 analytical views:

Metrics tab

Use the Metrics tab to review individual metrics, their metric profiles, utilization levels, associated detectors, charts, and API queries.

Use this view to:

  • Review custom metrics with high cardinality that might significantly impact your usage limits.
  • Trace the origin and ownership of specific metrics to determine whether they should be modified or deprecated.

See Analyze your metrics with Usage Analytics for more information.

Dimensions tab

Use the Dimensions tab to analyze individual dimensions and their usage in the context of metrics. Use this view for cardinality insights, usage percentages, and trend analysis to help you understand how dimensions contribute to overall MTS distribution and telemetry volume.

Use this view to:

  • Identify dimensions with high cardinality that may increase ingestion volume and affect performance.
  • Analyze how specific dimensions are used across metrics to detect redundancy or inefficiencies.
  • Understand which dimensions contribute most to metric fan-out and consider consolidation or filtering strategies.
  • Detect unused or low-value dimensions that could be deprecated to reduce data volume

See Analyze your dimensions with Usage Analytics for more information.

Use AI Assistant for Usage Analytics

Usage Analytics data is integrated with the Splunk AI Assistant in Observability Cloud.

You can use it to:

  • Analyze your metrics usage
  • Identify top cost contributors
  • Identify contributors to MTS cardinality anomalies (spikes and drops)

To learn more about AI Assistant and see example prompts, see Splunk AI Assistant in Observability Cloud.

Note: Alpha features are available in limited environments.