Dead Letter Queues

Concepts covered: paDeadLetterQueue

What They Want to Hear 'A dead letter queue (DLQ) is where events go when they cannot be processed. Instead of crashing the pipeline or blocking the stream, the bad event is moved to a separate topic for investigation. This keeps the main pipeline flowing. I monitor DLQ depth as a health metric: if it grows, something is systematically wrong. I reprocess DLQ events after fixing the root cause.' That is the answer. DLQ = safety valve. Monitor depth. Fix root cause, then replay.

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This section is part of the Streaming Systems: Beginner lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live PostgreSQL database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

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