message-queues

GitHub

指导设计可靠的消息驱动系统,涵盖RabbitMQ、Kafka、SQS等队列类型及模式。详解竞争消费者、发布订阅、分区消费及死信队列机制,提供代码示例与幂等性、监控等最佳实践。

categories/backend/message-queues/SKILL.md cosmicstack-labs/mercury-agent-skills

Trigger Scenarios

消息队列选型与设计 RabbitMQ或Kafka使用问题 死信队列处理方案 分布式系统解耦咨询

Install

npx skills add cosmicstack-labs/mercury-agent-skills --skill message-queues -g -y
More Options

Non-standard path

npx skills add https://github.com/cosmicstack-labs/mercury-agent-skills/tree/main/categories/backend/message-queues -g -y

Use without installing

npx skills use cosmicstack-labs/mercury-agent-skills@message-queues

指定 Agent (Claude Code)

npx skills add cosmicstack-labs/mercury-agent-skills --skill message-queues -a claude-code -g -y

安装 repo 全部 skill

npx skills add cosmicstack-labs/mercury-agent-skills --all -g -y

预览 repo 内 skill

npx skills add cosmicstack-labs/mercury-agent-skills --list

SKILL.md

Frontmatter
{
    "name": "message-queues",
    "metadata": {
        "tags": [
            "message-queues",
            "kafka",
            "rabbitmq",
            "sqs",
            "event-streaming"
        ],
        "author": "cosmicstack-labs",
        "version": "1.0.0",
        "category": "backend"
    },
    "description": "RabbitMQ, Kafka, SQS, pub\/sub, competing consumers, dead letter queues, and event streaming"
}

Message Queues

Design reliable message-driven systems.

Queue Types

Queue Persistence Ordering Use Case
RabbitMQ Optional Per queue Task distribution, RPC
Apache Kafka Durable (disk) Per partition Event streaming, logs
AWS SQS Durable Best effort (std) / Strict (FIFO) Serverless decoupling
Redis Pub/Sub None Per channel Real-time notifications

RabbitMQ Patterns

Work Queues (Competing Consumers)

Producer → Queue → Consumer 1
                 → Consumer 2
                 → Consumer 3
  • Messages distributed round-robin
  • Ack on success, nack on failure (requeue or DLQ)
  • Prefetch count controls concurrency

Pub/Sub (Exchange → Binding → Queue)

  • Fanout: broadcast to all queues
  • Direct: route by routing key
  • Topic: route by pattern (user.*, user.created)
  • Headers: route by header values

Kafka Patterns

Topics & Partitions

  • Messages within a partition are ordered
  • Partitions enable parallelism
  • Consumer group = one instance per partition

Producer

await producer.send({
  topic: 'order-events',
  messages: [{ key: orderId, value: JSON.stringify(order) }],
});

Consumer

await consumer.run({
  eachMessage: async ({ topic, partition, message }) => {
    await processOrder(message.value);
  },
});

Dead Letter Queues

  • Messages that can't be processed go to DLQ
  • Analyze DLQ periodically for systemic issues
  • DLQ messages can be replayed after fix
  • Set max retry count before DLQ

Best Practices

  • Idempotent consumers (same message processed twice = safe)
  • Monitor queue depth, consumer lag, error rate
  • Set message TTL to prevent infinite backlog
  • Use structured message schemas (Avro, Protobuf)
  • Test with network failures and consumer crashes

Version History

  • 38e2523 Current 2026-07-05 19:36

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Indexed
2026-07-05 19:36

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