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Metric Usage Analysis

The Metrics Usage Analyzer gives you a detailed view of your ingested metrics and labels. Use it to identify high-volume or high-cardinality metrics, understand ingestion patterns, detect inefficient time series, and optimize your data pipeline.

This tool works with pre-aggregated statistics updated from the ingestion pipeline. Variations, labels, and trends reflect real-time ingestion data.

By regularly using the Metrics Usage Analyzer, observability teams can:

  • Detect wasteful or unused metrics
  • Reduce cardinality
  • Control ingestion volume

Open the usage analysis tab

  1. Go to Settings, then select Metric data.
  2. The Usage Analysis tab opens by default.
  3. Use the sub-tabs to explore:
    • Metrics: Ingested metrics with usage, cardinality, and samples
    • Labels: All labels attached to metrics
    • Queries: Shows query patterns and usage across your metrics.
    • Blocked: Metrics blocked from ingestion

metric usage analyzer home

Review top-level usage

The Metrics sub-tab includes 3 charts that summarize ingestion and cost trends for the selected time range. Use these charts to understand how your metric volume and cardinality change over time:

  • Total samples: Shows how many metric data points were ingested.

    Use this chart to spot ingestion spikes or drops that might indicate deployment issues, misconfigured scrapers, or unexpected increases in data volume.

  • Total cardinality: Shows how many unique time series were generated.

    Use this chart to detect sudden growth in time-series count, often caused by new labels, unexpected label values, or high-cardinality dimensions such as pod_name or operation.

  • Total units: Shows the billing units generated by your metrics.

    Use this chart to see how ingestion or cardinality changes influence your cost. A spike in units without a matching spike in samples often points to excessive cardinality.

These charts help you correlate ingestion patterns with cost, identify high-impact changes quickly, and prioritize where to reduce cardinality or remove unnecessary variations.

Explore the metrics table

The Metrics table lists usage details per metric. Key columns include:

  • Usage: Data volume in GB and billing units
  • % Usage: Share of total usage
  • Samples: Total datapoints ingested

Note

Sample counts might differ from PromQL results because Coralogix applies a 15-second deduplication window.

  • Dimensions: Unique label keys
  • Variations: Unique combinations of label keys
  • Cardinality: Unique time series per metric
  • % Cardinality: Share of total series cardinality
  • Last Ingested: Timestamp of the most recent ingestion event for the metric

Note

Variations reflect label set combinations. For example, (host, region) versus (host, app, region).

Drill into a specific metric

Overview tab

The Overview tab visualizes daily ingestion trends and metric activity.

Panels

  • Metric Unit Usage Per Day: Billing units ingested per day
  • Variation Unit Usage Per Day: Usage trends per variation
  • Label Unit Usage Per Day: Unit consumption per label

Display Modes

Toggle between:

  • Unit Usage
  • Data Volume
  • Sample Count
  • Cardinality

Insights

  • Detect ingestion spikes or drops
  • Identify inactive metrics
  • Compare usage trends over time

Variations tab

The Variations tab breaks down how label combinations affect a metric's volume and cardinality. Use this view to identify which label sets consume the most storage and where to optimize.

For more details, see Variations.

Labels tab

The Labels tab analyzes label-level impact on storage and cardinality. Lists all labels attached to the metric with their usage, cardinality, and unique value count.

For more details, see Labels.

Explore tab

The Explore tab helps you identify which label values contribute most to a metric's cardinality. Drill down to see how individual label values affect the number of generated series and pinpoint which values are driving cardinality growth.

For more details, see Explore Tab.

Block noisy or unused metrics

  • In the Action column of the table, select Block to stop ingesting a metric.

Note

Blocking reduces both data volume and cost by preventing storage and queries of low-value metrics.

Unblock metrics when needed

  • Open the Blocked tab.
  • Select Unblock for any metrics you want to resume ingesting.

Investigate label usage

In the Labels tab, you can:

  • Search for a specific label (for example, task_id)
  • View all metrics that use the label
  • Investigate cardinality and value distribution for that label

Permissions

You must have the METRICS.DATA-ANALYTICS#HIGH:READ permission to access this section. For more information, see Create Roles and Permissions.

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