Labels

The Labels tab analyzes label-level impact on storage and cardinality.

• Lists all labels attached to the metric
• Shows each label's usage, cardinality, and unique value count
• Highlights labels driving high series counts

Explore label details

From the Labels tab, click any label row (for example, operation or host_name) to open its detailed view.

This view helps you analyze how a specific label contributes to metric usage, variation, and value diversity.

The label details page includes two sub-tabs:

• Metrics: Lists all metrics associated with the selected label
• Live values: Displays recent values for that label

Use this view to understand which metrics and label values drive data volume and cardinality.

Metrics tab

The Metrics tab shows how the selected label is used across different metrics.

For each metric, you can review:

• Usage: Data volume attributed to the label
• % Usage: Relative share of total usage
• Unique Values: Count of distinct label values
• Last Ingested: Timestamp of the latest ingestion for that metric

Example: Selecting the operation label lists metrics such as cx_service_catalog_service_duration_cx_bucket and latency_ms_sum, showing how each contributes to total usage.

Use this view to detect metrics that are heavily influenced by the chosen label or that have excessive label variations.

Live values tab

The Live values tab lets you explore the actual values for a selected label.

• Displays a sample of up to 1,000 values at a time. You can narrow the results using the search bar to filter by specific strings or patterns.
• "Live" refers to a best-effort view of the last 24 hours of data. The list reflects values recently observed in your environment rather than a complete historical record.
• Values are aggregated across all metrics that include the selected label, not limited to a single metric. Use this view to identify active label values and verify that expected data is still being ingested.

Use this view to:

• Inspect label values to understand what data is associated with a label.
• Spot noise or garbage values in high-cardinality labels that may indicate misconfigured instrumentation.
• Confirm label consistency, such as checking that values follow expected formats or naming patterns (for example, region: us-east-1, not region: useast).

Example: If you select the label operation, you might see hundreds of API operation names such as: GET /items, POST /checkout, grpc.health.v1.HealthCheck, etc.