Using PostgreSQL as a Dead Letter Queue for Event-Driven Systems
3 months ago
- #Kafka
- #Dead Letter Queue
- #PostgreSQL
- Worked on a system generating daily business reports from multiple data sources using Kafka and PostgreSQL.
- Implemented a Dead Letter Queue (DLQ) in PostgreSQL to handle failed events due to API failures, crashes, or malformed data.
- Designed a DLQ table schema with fields for event type, payload, error details, status, retry count, and timestamps.
- Used indexes to optimize query performance for retries and debugging.
- Introduced a retry mechanism with ShedLock to safely reprocess failed events without duplicate retries.
- Configured retry scheduler with batch size, max retries, and fixed intervals to prevent retry storms.
- Leveraged PostgreSQL's FOR UPDATE SKIP LOCKED feature for concurrent retry processing across instances.
- Achieved operational benefits like predictable failures, easy debugging, and reduced stress with a clear recovery path.
- Combined Kafka for high-throughput ingestion and PostgreSQL for durability and observability.