Stop Tuning Blind: Query Observability as the Foundation for Database Optimization

A team notices a checkout endpoint slowing down. Response times have crept from 80ms to 900ms over two weeks, but the infrastructure dashboard shows nothing abnormal. So the engineer does what most teams do first: adds an index on the column mentioned in the ticket, deploys, and moves on. Two weeks later, the same endpoint is slow again. A different engineer adds another index. Then another. The table now carries 23 indexes. Every INSERT pays write amplification across all of them. The original slow query is still slow, because the root cause was never the missing index. Stale statistics after a schema migration had triggered a plan regression, and no one caught it because no one was watching query-level execution data. This guide inverts the usual approach. Instead of starting with indexing techniques and treating observability as an afterthought, it starts with the telemetry pipeline: how to capture query-level execution data, correlate it with application traces, and build the feedb