PostgreSQL CDC usually does not fail because WAL is unreliable.
The real problems usually start around the workflow:
<ul>
<li>initial load and CDC are not tied to the same WAL boundary</li>
<li>checkpoints move before target writes are durable</li>
<li>retries replay events into non-idempotent targets</li>
<li>parallel workers break ordering</li>
<li>long transactions create hidden lag</li>
<li>schema changes are handled too late</li>
</ul>
PostgreSQL is the example here, but the same failure pattern shows up in many database replication and migration pipelines: reading changes is only one part. Recovery semantics, ordering, checkpoints, and restart behavior matter more.
<a href="https://streams.dbconvert.com/blog/postgresql-cdc-breaks-in-production" target="_blank" rel="noopener nofollow">https://streams.dbconvert.com/blog/postgresql-cdc-breaks-in-production</a>

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PostgreSQL CDC failures in production rarely stem from WAL unreliability. The real culprits are workflow-level issues: initial load and CDC not sharing the same WAL boundary, checkpoints advancing before writes are durable, non-idempotent retry behavior, ordering broken by parallel workers, hidden lag from long transactions, and late schema change handling. These failure patterns apply broadly to database replication and migration pipelines, where recovery semantics, ordering, and restart behavior matter more than simply reading changes.

Why PostgreSQL CDC Breaks in Production