expanso-dead-letter-queue

Route failed Kafka messages to a dead-letter topic after retries with exponential backoff.

1|Updated Feb 1, 2026
One-click install
npx skills add https://github.com/expanso-io/expanso-skills --skill expanso-dead-letter-queue
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: expanso-dead-letter-queue
Source: https://github.com/expanso-io/expanso-skills/tree/main/skills/recipes/dead-letter-queue
Command: npx skills add https://github.com/expanso-io/expanso-skills --skill expanso-dead-letter-queue

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill addresses the critical issue of handling messages that fail processing in a message queue system, preventing data loss and enabling robust error management.

Core Features & Use Cases

  • Dead-Letter Queueing: Automatically routes failed messages to a designated DLQ topic.
  • Retry Logic: Implements exponential backoff for retrying failed messages up to a configurable limit.
  • Error Metadata Enrichment: Adds detailed error information to failed messages for easier debugging.
  • Use Case: In a high-throughput event processing system, messages that fail validation or processing can be sent to a DLQ for later analysis, while transient errors are retried automatically.

Quick Start

Run the dead-letter-queue skill using the default Kafka brokers and input topic.

Frequently Asked Questions about expanso-dead-letter-queue

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I handle failed messages in Kafka without losing data?▼

To handle failed messages in Kafka without data loss, you can implement a dead-letter queue pattern that routes unprocessable messages to a designated DLQ topic after exhausting automated retries, preserving them for later analysis.

What is the best way to retry failed Kafka messages with exponential backoff?▼

The best way to retry failed Kafka messages with exponential backoff is to use a dead-letter queue pattern that automatically re-attempts processing up to a configurable limit before permanently routing the message to a DLQ topic.

How does a dead-letter queue improve error handling in message processing systems?▼

A dead-letter queue improves error handling in message processing systems by isolating permanently failed messages, enriching them with detailed error metadata for easier debugging, and preventing data loss while maintaining high-throughput processing.

Can I add error metadata to failed messages routed to a Kafka DLQ?▼

Yes, you can add error metadata to failed messages routed to a Kafka DLQ. This dead-letter queue implementation enriches failed messages with detailed error categorization and contextual information to simplify troubleshooting.

When should I route Kafka messages to a DLQ instead of discarding them?▼

You should route Kafka messages to a DLQ instead of discarding them when messages fail validation or processing in a high-throughput event system, ensuring transient errors are retried while permanently failed data remains accessible for later analysis.

Does this dead-letter queue pattern require additional dependencies to process Kafka topics?▼

No, this dead-letter queue pattern requires no additional dependencies to process Kafka topics. It operates independently using built-in scripts to manage message routing, exponential backoff retries, and error metadata enrichment.