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