How to De-Risk a Mission-Critical PostgreSQL Migration

Speed is the wrong finish line for a mission-critical PostgreSQL migration. This field-tested method covers defining success in numbers, validating data at three checkpoints, rehearsing against a production copy, following a runbook, and keeping a rollback path open until sign-off.
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How Fast Should You Patch Production PostgreSQL?

PostgreSQL's August 2026 release closed 28 CVEs in a single day, a record. The fix itself is a fast binary swap. What actually determines your risk is how long it takes you to apply it. Here's how to set a patch SLA and hit it without breaking production.
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PostgreSQL Wait Events: A Production Diagnostic Guide

A query plan tells you what PostgreSQL intended to do. A wait event tells you what it actually did with its time. Most performance work I see in production starts one layer too high, in the EXPLAIN output, when the cheaper answer is already sitting in pg_stat_activity.This is a refresh of a guide I wrote in late 2024. Two things have changed since then. PostgreSQL 17 added pg_wait_events as a first-class catalog view. PostgreSQL 18 shipped asynchronous I/O and changed how I/O wait should be read in production. Both shifts deserve their own treatment, and I have folded them into this update along with five production cases from work my team did over the last two quarters.
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Long-running transactions, job queues, and the cascade that wreaks havoc

A scheduled PostgreSQL migration step held an open transaction snapshot for hours during the initial data copy. A job queue running at production write velocity began to slow down. Twelve hours later, the queue was seven million rows deep, the primary was pinned at 100 percent CPU across 24 cores, and customer support was fielding complaints about delayed transactions.
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You have a Patroni leader election. You are only halfway to PostgreSQL high availability.

A PostgreSQL primary loses power at 2am. Writes resume in under thirty seconds. The on-call engineer reads the alert in the morning, sees that the cluster healed itself, and goes back to coffee. That is the outcome PostgreSQL high availability is supposed to deliver.A working Patroni cluster, on its own, gets you partway there. The leader election runs. A standby gets promoted. The cluster state in etcd stays consistent. Then the application keeps trying to reach an IP address that points at the wrong node now, the old primary needs a manual rejoin, and the on-call engineer is on a conference bridge instead of in bed.
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