role-backend:message-queues
Implements message queue systems using RabbitMQ, Apache Kafka, Redis Streams, AWS SQS/SNS, and Google Pub/Sub. Covers topics, exchanges, dead letter queues, idempotency, ordering guarantees, consumer groups, backpressure handling, and message serialization. Use when setting up async communication...
SKILL.md
Full skill instructions
Message Queues
When to use
- Choosing between RabbitMQ, Kafka, Redis Streams, SQS, or Pub/Sub for a new integration
- Designing RabbitMQ exchange topology (direct, topic, fanout, headers)
- Designing Kafka topic partitioning and consumer group structure
- Implementing idempotent consumers that handle duplicate delivery safely
- Setting up dead letter queues and replay tooling for failed messages
- Enforcing ordering guarantees without sacrificing throughput
- Managing backpressure between fast producers and slow consumers
- Choosing message serialization format (JSON vs Avro vs Protobuf)
Core principles
- At-least-once is the default — every consumer must be idempotent; duplicates will arrive
- Partition key determines order — group messages by entity ID, not randomly
- DLQ depth is never acceptable as a steady state — it means something is broken
- Schema versioning from day one — breaking changes without a registry are production incidents waiting to happen
- Consumer lag is the real SLA — not throughput; lag tells you whether processing keeps pace with production
Reference Files
references/brokers-patterns.md— technology selection table with ordering and delivery guarantees, RabbitMQ exchange types and configuration, Kafka topic design and consumer group rules, and schema registry with Avro/Protobuf guidancereferences/reliability-patterns.md— DLQ setup and retention policy, idempotent consumer implementation with idempotency table SQL, ordering guarantees and retry trade-offs, backpressure techniques, message serialization format selection, and claim-check pattern for oversized payloads