A Telemetry Database That Forgets on Purpose Keeps Rollups and Anomalies Instead of Raw Rows

Mon, 05 Oct 2026 00:00:00 +0000

At 300 requests a second, one latency metric adds about 26 million rows a day. Nobody will read most of them again. What people ask for a month later is the p99 per route for last Tuesday, and the one request that took nine seconds. A rule that deletes rows after 30 days throws away both answers. Keeping every row forever pays storage bills for data nobody reads.

The telemetry store worth building decides at write time what has to survive. It folds everything else into coarser buckets on a schedule and keeps the few raw events that carry information, whole. Forgetting becomes part of the schema, declared in a policy, instead of a cron job that deletes by age. This is the argument for reducing data near the source, applied to time series.

Time Series on App Coding

A Telemetry Database That Forgets on Purpose Keeps Rollups and Anomalies Instead of Raw Rows