Notes

Curious notes on production reliability

A collection of notes and observations on production reliability — how real systems fail, degrade and recover, across databases, queues and the rest of the stack.

Incidents Postgres incidents rarely start with "Postgres broke" When production degrades, Postgres is the first suspect — but it is usually where other system problems become visible, not the cause. How to separate trigger, mechanism and amplifier. 11 min read

Connections Connection pools and Postgres: why more connections do not mean more performance When the pool fills, the instinct is to make it bigger. But a connection pool is a pressure valve, not a throughput dial — and raising it often turns a controlled slowdown into a larger failure. 17 min read

Replication Postgres replication: when a standby exists but does not save you A standby looks like a safety net on the architecture diagram. But replication is a mechanism, not a guarantee — lag, slots, query conflicts, split-brain and timelines all create new failure modes. 13 min read

WAL WAL and checkpoints: the invisible machinery behind Postgres durability WAL and checkpoints are part of the contract between Postgres, storage, replication, backups and latency. A practical reliability model of how this machinery behaves under write pressure. 16 min read

Locks Postgres locks: how one ALTER TABLE can stop your product Locks are not a bug — they are how Postgres protects your data. But a single waiting ALTER TABLE can queue every query behind it. How lock incidents really unfold, and how to respond safely. 12 min read

Migrations Schema migrations in Postgres: why safe SQL can be dangerous in production A migration can pass review, run instantly on staging, and still freeze production. In production a schema change is an operational event — locks, scans, rewrites, WAL and rolling deploys all matter. 16 min read

Vacuum Autovacuum: the quiet Postgres process that becomes a loud reliability problem Autovacuum is easy to ignore until storage grows, plans go unstable, or wraparound warnings appear. It is not optional maintenance — it is part of Postgres survival, and it needs capacity, observability and tuning. 15 min read

Monitoring Postgres monitoring: which metrics help, and which ones create noise More metrics do not automatically create better reliability. Good monitoring starts from user impact and follows pressure into Postgres — turning ten red panels into a hypothesis. 16 min read

Performance A slow Postgres query is a symptom, not a diagnosis A slow query is easy to notice and easy to misunderstand. The same SQL can be fast yesterday and dangerous today. Diagnose the mechanism — plan, statistics, locks, IO, bloat, concurrency — not just the symptom. 14 min read

Reliability Why Postgres reliability cannot be learned from documentation alone Documentation teaches mechanisms; incidents test judgment. The hard part is synthesis — choosing the safest action while Postgres, the application, traffic and people all interact under pressure. 16 min read