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  Introduction When it comes to database performance tuning, most professionals jump directly into indexing, query optimization, or hardware scaling. However, one of the most underrated yet powerful tools available in  PostgreSQL  is  logging . Postgres logs provide deep insights into query execution, bottlenecks, errors, and system behavior. If configured correctly, logging can act as your  first line of defense  in diagnosing and optimizing performance issues. Why Logging Matters in PostgreSQL Logging is not just for debugging it’s a performance optimization goldmine. With proper logging, you can: Identify  slow-running queries Detect  lock contention issues Monitor  checkpoint and I/O behavior Analyze  connection spikes Track  deadlocks and errors In short, logs transform guesswork into  data-driven tuning . Key Logging Parameters You Must Configure Postgres provides several configuration parameters in  postgresql.conf ...
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Postgres Migrations Using Logical Replication

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  Migrating a PostgreSQL database is never a trivial task – especially when you’re dealing with production systems, large datasets, and strict uptime requirements. Whether you’re upgrading PostgreSQL versions or shifting infrastructure, choosing the right migration strategy is critical. Let’s explore the available approaches and then deep dive into  logical replication , the most flexible option when downtime isn’t acceptable. Common PostgreSQL Migration Approaches 1. Dump & Restore (pg_dump / pg_restore) This is the most straightforward method. Captures schema + data + objects Easy to execute and widely used Ideal for  small to medium databases (50–150 GB) On modern systems, migrations can complete in under an hour. Limitation: Requires downtime during restore. 2. WAL-Based Migration Using tools like pgBackRest or WAL-G: Take a base backup Stream WAL logs to the target system Maintain near real-time sync Best for  large databases (TB scale) Minimal downtime duri...
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