New Relic One has introduced metric aggregate pruning, a tool to manage dimensional metric cardinality, allowing users to create rules that prioritize important attributes for longer-term trending and analysis while excluding less relevant ones for troubleshooting short-term issues. This feature helps avoid hitting cardinality limits, which can reduce data usefulness. Cardinality refers to the number of unique combinations of key-value pairs in metrics, with high cardinality values requiring more correlated data to analyze. New Relic One uses raw data points and rollups to store and query metrics efficiently. The new pruning ability is ideal for high cardinality attributes like container IDs, which lose value over time but are crucial during incidents. Users can prune attributes using the DROP_ATTRIBUTES_FROM_METRIC_AGGREGATES command or explore other solutions like partitioning data or dropping low-value metrics.