# A DLQ that is hard to drain is functionally a drop with extra storage cost Canonical URL: Domain: Pipeline Design ยท Difficulty: medium ## Problem A DLQ that is hard to drain is functionally a drop with extra storage cost. The section's three replay capabilities: inspection (decode the envelope and show payload, exception, attempts), annotation (edit a payload before replay with an audit trail), and bounded replay (throttled batch replay with dry-run and a second-failure side channel so a flood does not become a thundering herd). Build the replayer by adding a replay transform off the DLQ whose name covers all three capabilities, plus a side-channel destination for replays that fail again. ## Related - [All practice problems](https://datadriven.io/problems) - [Mock interview mode](https://datadriven.io/interview/a-dlq-that-is-hard-to-drain-is-functionally-a-drop-with-extr-8efd55f8) - [System Design Interview Questions](https://datadriven.io/data-engineering-system-design) - [Data Engineering Interview Prep Guide](https://datadriven.io/data-engineer-interview-prep) - [Daily Challenge](https://datadriven.io/daily) --- Source: DataDriven (https://datadriven.io). 100% free data engineering interview prep. Live code execution against Postgres 16, Python 3.11, and Spark sandboxes. No paywall, no premium tier, no signup gate.