messaging

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](/skills/architecture/) - System design patterns
• [Database](/skills/database/) - Transactional outbox
• [DevOps](/skills/devops/) - Message broker deployment