Upgrading PostgreSQL in production is not fun. You have real data, real users, and a version of Postgres that's probably several major releases behind. The obvious approach (dump, upgrade, restore) works fine on a 10GB database on a Saturday night. It doesn't work when you have TBs of data, applications that can't afford hours of downtime, and a team watching the monitoring dashboard at 2am. Logical replication solves this. I’ve run it in production, and it works well, but there are a few practical considerations that are easier to appreciate once you’ve been through the process yourself. Why Logical Replication You keep your source cluster running (old Postgres version, production traffic, and all), bring up a destination cluster with the new version, and replicate all data changes while both run in parallel. When the destination has caught up, you cut over. Downtime is seconds to minutes, not hours. Source is your existing cluster (say, Postgres 14). Destination is your new cluster running Postgres 17. The thing most guides skim over is that logical replication does not copy schema, it only copies data. PostgreSQL replicates INSERT, UPDATE, and DELETE operations, but not your table definitions, indexes, roles, or anything structural. An example would be if logical replication is setup then truncate operation on a single source table would also be replicated, but table1, table2, and table3, etc. won't be replicated. You have to handle that yourself before replication starts. Miss this, and your subscription will either fail silently or throw confusing errors that don't point you back to the actual problem. Step 1: The Primary Key Check Logical replication requires every replicated table to have a replica identity to replicate UPDATE and DELETE operations. By default, that's the primary key. Tables without one will still replicate INSERTs, but any UPDATE or DELETE will error on the publisher. Replica Identity A published table must have a replica identity configured so that UPDATE and DELETE operations can be replicated, because the replica identity is what allows the correct row to be located on the subscriber. By default, the replica identity is the primary key. A suitable unique index can also be used, subject to certain requirements. If no suitable key exists, the replica identity can be set to FULL, which uses the entire row as the key. Replica identity FULL should be treated as a fallback to be used only when no other option is available, because without a suitable index on the subscriber, the row search can be very inefficient. If a table without a replica identity is added to a publication that replicates UPDATE or DELETE operations, those operations will fail on the publisher. INSERT operations proceed regardless of the replica identity.

If you have ever been in the middle of a database migration and suddenly found your logical replication slots missing, you know how unsettling that feeling is. No obvious error. No warning. Just gone. That is exactly what happened to us while migrating data from a Patroni-managed cluster to a standalone PostgreSQL cluster. What started as a smooth operation turned into a debugging session that taught us something important about how Patroni behaves after a restart.The SetupWe were running a data migration where the source was a Patroni cluster and the target was a another PostgreSQL cluster. Logical replication was our chosen approach, which meant we had created replication slots on the Patroni side to track the changes flowing out. Things were going well at the start. Data was moving, lag was low, and we felt good about the plan.Something Went WrongAt some point, the publisher node on the Patroni side got restarted. After the restart, our logical replication slots were simply gone. This was strange. These were not temporary slots. Temporary slots are expected to disappear after a session ends, but permanent slots are supposed to survive restarts. PostgreSQL itself has no reason to drop them.

Everyone wants high availability, and that’s completely understandable. When an app goes down, users get frustrated, business stops, and pressure builds.But here’s the challenge: high availability often feels like a big monster. Many people think, If I need to set up high availability, I must master every tool involved. And there’s another common belief too: Open-source tools are not enough for real HA, so I must buy paid tools.