How can dead-letter queues in Azure Service Bus be monitored and processed in a production application?
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Answers
A Dead-Letter Queue (DLQ) should not be treated as a place where failed messages are permanently forgotten. It should be part of your production monitoring and recovery strategy.
Monitor the DLQ message count and investigate important details such as the dead-letter reason, message age, delivery attempts and application errors.
Common causes include:
- Maximum delivery count exceeded
- Message expiration
- Invalid business data
- Processing failures
- Poison messages
Don't blindly replay every message. First classify the failure:
Temporary failure → Retry
Invalid data → Correct and reprocess
Poison message → Investigate
Business rejection → Handle separately
Production consumers should also be designed for duplicate delivery and idempotency. A message may be processed successfully but fail before the application completes the message settlement.
A strong architecture is:
Queue → Consumer → Retry → DLQ → Monitor → Diagnose → Correct → Controlled Replay
Interview tip: Be prepared to explain why DLQ handling is an operational responsibility, not just a coding feature.