Managing replication slots in Postgres is crucial to prevent WAL bloat and ensure efficient Change Data Capture (CDC) processes. Best practices include using the pgoutput plug-in, defining maximum replication slot sizes, enabling heartbeats for idle databases, and utilizing table-level publications and filters to optimize resource usage. These strategies help maintain database performance and avoid operational issues.

The implementation of Log-Structured Merge (LSM) trees in Postgres aimed to enhance write throughput for real-time applications but resulted in issues with physical replication. The article explores the challenges of ensuring replication safety and the role of hot_standby_feedback in mitigating logical consistency problems during high-volume write operations.

Postgres logical replication can struggle with TOAST columns, leading to incomplete change events in Debezium when values remain unchanged. This article examines Debezium's reselect post processor as a solution, alongside more comprehensive approaches using Apache Flink for stateful stream processing to manage TOAST column values effectively.

Postgres replication slots utilize two log sequence numbers (LSNs) — confirmed_flush_lsn and restart_lsn — to manage data streaming and retention effectively. The confirmed_flush_lsn indicates the last acknowledged data by the consumer, while the restart_lsn serves as a retention boundary for WAL segments needed for ongoing transactions. Understanding these differences is essential for troubleshooting replication issues and optimizing WAL retention in production environments.