Cardinality explosion in metrics backend

A new release passes its 1-hour canary cleanly (error rate, latency, saturation all green; canary served 2% of traffic) and auto-promotes to 100% at 11:00. By 11:25 the metrics/monitoring backend itself starts degrading: the Prometheus remote-write queue backs up, ingestion latency climbs, and several dashboards go blank. The app's own error rate is fine. Recent context: the release added a new histogram metric labeled by customer_id and endpoint. In the 2% canary the unique-series count was modest; at 100% the active series count jumped from ~400k to ~9M and is still climbing. How do you triage and mitigate?