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Dead-Letter Queue Explorer

1 post · Jun 2026

What this trail covers

Notion's DLQ Explorer provides engineers with a controlled, browser-based interface to inspect and recover failed tasks from the dead-letter queue. It leverages AWS Athena with partition projection over existing S3 buckets for querying, and a dedicated re-enqueue workflow with audit trails for recovery. This significantly reduces the time and complexity of investigating and resolving task failures. The Explorer now includes enhanced observability features, allowing for more granular filtering by cell, environment, event name, and error message, and provides detailed audit trails for re-enqueue operations, including who triggered it, when, and the justification provided. Investigations that once took around 20 minutes can now take under a minute.

All Notion trails
  1. Building observability into Notion’s dead-letter queueThis post details the integration of enhanced observability into Notion's dead-letter queue (DLQ) system, building upon the existing DLQ Explorer. Key contributions include: 1. Leveraging AWS Athena with partition projection on date and hour columns for efficient querying of S3-stored dead-task records, avoiding new data pipelines. 2. Implementing a robust IAM and KMS setup across multiple regions and environments for Athena access. 3. Designing a query layer with a user-friendly interface that allows filtering by cell, environment, date range, event name, workspace ID, and free text, with partition pruning applied before other filters. 4. Developing a first-class re-enqueue workflow that streams tasks from S3 to an SQS queue, includes confirmation modals with justification, and logs detailed audit trails of who, when, and why tasks were re-enqueued.