Slide 5 of 7

Reduce cardinality you already have

Reduce cardinality you already have

If the Cardinality tab already shows high-cardinality or unused metrics, you don’t have to reinstrument anything to fix it. Adaptive Metrics reduces cardinality from inside Grafana Cloud by aggregating away the labels nobody uses, while keeping the metric itself.

How Adaptive Metrics helps

Adaptive Metrics analyzes how your organization uses its metrics across dashboards, alerts, recording rules, and queries. It then recommends aggregating underutilized metrics into lower-cardinality versions. Applying a recommendation doesn’t delete the metric, rather it aggregates away unused label dimensions, and your existing dashboards, rules, and queries continue to work without modification. If usage changes later, you can remove the aggregation and the metric is stored at full cardinality again.

Unnecessary series are stopped before they’re persisted, without modifying your collector configuration.

To set up and manage recommendations end to end, follow the Optimize metrics with Adaptive Metrics learning path.

Script

Prevention is only half the job. What about the high-cardinality and unused metrics already showing up in your Cardinality tab?

The good news is you don’t have to reinstrument anything. Adaptive Metrics works from inside Grafana Cloud, aggregating away the labels nobody uses while keeping the metric itself.

It works by analyzing how your organization actually uses its metrics, across dashboards, alerts, recording rules, and queries. From that analysis, it recommends aggregating underutilized metrics into lower-cardinality versions.

Applying a recommendation doesn’t delete the metric. Unused label dimensions are aggregated away, your existing dashboards, rules, and queries continue to work, and if usage changes later you can remove the aggregation and store the metric at full cardinality again.

To set up and manage recommendations end to end, follow the Adaptive Metrics learning path linked on this slide.