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- Williamzujkowski
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- Messaging Rabbitmq Architect
messaging-rabbitmq-architect_skill
- Python
5
GitHub Stars
1
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
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Installation
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npx veilstrat add skill williamzujkowski/cognitive-toolworks --skill messaging-rabbitmq-architect- SKILL.md23.1 KB
Overview
This skill designs production-ready RabbitMQ architectures covering exchanges, quorum and stream queues, routing patterns, clustering, dead letter exchanges, and AMQP best practices. I produce clear topology recommendations, queue arguments, publisher/consumer settings, and error handling patterns. The outputs are actionable: topology diagrams, configuration snippets, and operational rules to implement immediately.
How this skill works
For each requested message flow I validate RabbitMQ version and functional requirements, select exchange types and queue types (classic/quorum/stream) and generate routing and DLX retry patterns. I recommend publisher confirms, delivery modes, consumer ack strategies and prefetch tuning. For clustering and high-throughput scenarios I provide quorum replication, stream queue configuration, and federation or consistent-hash sharding patterns.
When to use it
- Design a resilient production topology with replication and durability requirements
- Implement DLX-based retries and dead-letter handling for failed messages
- Choose between quorum queues and streams for durability vs throughput
- Plan a multi-node cluster with Raft quorum and appropriate node counts
- Shard high-volume workloads using consistent-hash exchanges or stream consumers
Best practices
- Default to topic exchanges for flexible routing unless exact one-to-one mapping is required
- Use quorum queues for production durability; streams for append-only, high-throughput use cases
- Enable publisher confirms and delivery_mode=2 for durability; avoid AMQP transactions
- Use manual consumer acks and start with prefetch=10, then tune based on processing profile
- Implement DLX + TTL retry queues and a delivery-limit policy to avoid infinite redelivery
- Run clusters with an odd number of nodes (3/5) and set x-quorum-initial-group-size accordingly
Example use cases
- Single-exchange topology: events topic exchange → quorum order-processing-queue with confirms and prefetch=10
- Multi-exchange routing: orders, payments, notifications exchanges with topic bindings and DLX for failed orders
- Retry/backoff: retry-order-5s and retry-order-30s TTL queues that route back to main queue, final DLX for manual inspection
- Clustering: 3-node cluster example, quorum queue replication and network/port requirements
- High-throughput streaming: stream queue config with x-max-age and consumer offset strategies for audit/event logs
FAQ
Use quorum queues for replicated, durable workloads. Use stream queues when you need append-only log semantics and very high throughput.
How do I implement retries without losing ordering?
Use DLX + TTL retry queues for delays. For strict ordering use single active consumer (x-single-active-consumer=true) or route to a single shard so retries preserve order.