By name: messaging description: Message queues, events, and async communication patterns category: skill allowed-tools: Read, Write, Glob, Grep, Bash user-invocable: true context: inject version: 1.0.0
Messaging Skills
Overview
Asynchronous communication patterns for building scalable, decoupled distributed systems. Messaging enables services to communicate without direct coupling, improving reliability and scalability.
Messaging Types
| Type | Description | Use Case | Examples |
|---|---|---|---|
| Point-to-Point | One sender, one receiver | Task distribution | RabbitMQ, SQS |
| Pub/Sub | One sender, many receivers | Event broadcasting | Kafka, Redis Pub/Sub |
| Request/Reply | Synchronous over async | RPC-style calls | RabbitMQ RPC |
| Event Streaming | Ordered, replayable log | Event sourcing | Kafka, Kinesis |
Delivery Guarantees
| Guarantee | Description | Trade-off |
|---|---|---|
| At-most-once | Fire and forget | May lose messages |
| At-least-once | Retry until acknowledged | May have duplicates |
| Exactly-once | Deduplicated delivery | Complex, higher latency |
When to Use Messaging
Use Messaging For
- Decoupling services
- Async task processing
- Event-driven architectures
- Load leveling and buffering
- Cross-service communication
Avoid Messaging When
- Simple request/response is sufficient
- Strong consistency is required
- Real-time response is critical
- System complexity isn't justified
Categories
Fundamentals
Core messaging concepts:
- Messaging Patterns - Common communication patterns
- Sync vs Async - When to use each approach
- Message Types - Commands, events, and queries
Queues
Message queue implementations:
- RabbitMQ - Feature-rich message broker
- Redis Queues - Simple Redis-based queues
- AWS SQS - Managed queue service
- BullMQ - Node.js job queue
Events
Event-driven patterns:
- Event-Driven Architecture - EDA fundamentals
- Apache Kafka - Event streaming platform
- Event Sourcing - State as event log
- Pub/Sub - Publish-subscribe patterns
Patterns
Distributed system patterns:
- Saga Pattern - Distributed transactions
- Outbox Pattern - Reliable event publishing
- Retry Strategies - Handling failures
- Dead Letter Queue - Failed message handling
Reliability
Ensuring message delivery:
- Delivery Guarantees - At-most/least/exactly-once
- Idempotency - Safe message reprocessing
- Message Ordering - Maintaining sequence
Best Practices
Production considerations:
- Message Design - Schema and versioning
- Error Handling - Failure management
- Monitoring - Observability and alerting
Quick Reference
Message Broker Comparison
| Feature | RabbitMQ | Kafka | SQS | Redis |
|---|---|---|---|---|
| Model | Queue | Log | Queue | Queue/Pub-Sub |
| Ordering | Per-queue | Per-partition | FIFO option | Per-queue |
| Persistence | Durable | Always | Always | Optional |
| Replay | No | Yes | No | No |
| Throughput | High | Very High | High | Very High |
| Latency | Low | Low | Medium | Very Low |
Common Patterns
Producer → Queue → Consumer (Point-to-Point)
Producer → Exchange → Queue → Consumer (RabbitMQ)
Producer → Topic → Partition → Consumer Group (Kafka)
Publisher → Channel → Subscribers (Pub/Sub)
Integration with F5
# In f5-config.yaml
messaging:
broker: rabbitmq
queues:
- name: orders
durable: true
dlq: orders-dlq
events:
- topic: order.placed
retention: 7d
Related Skills
- Architecture - System design patterns
- Database - Transactional outbox
- DevOps - Message broker deployment