RabbitMQ Message Broker: Reliable Async Processing

The System Crash That Taught Me About Queues

Black Friday. Our servers melted. Then we discovered message queues. Everything changed.

Table of Contents

• Async Architecture 2026
• Core Concepts
• 5 Key Patterns
• Implementation
• Reliability
• Monitoring
• Scaling
• FAQ
• Setup Guide

Async Architecture 2026

Build systems that scale infinitely.

Why Queues Matter

Fast response times, reliable processing.

Business Value

Handle 10x load without scaling servers.

Core Concepts

Understanding message queues.

Queue Basics

Messages wait in line for processing.

Producers and Consumers

Separate systems communicate via queue.

Pattern 1: Simple Queue

Setup

import { Queue, Worker } from 'bullmq';

const queue = new Queue('tasks');

await queue.add('email', { userId: '123' });

const worker = new Worker('tasks', async (job) => {
  await sendEmail(job.data.userId);
});

Pattern 2: Priority

High Priority First

Different urgency levels processed accordingly.

Pattern 3: Delayed Jobs

Schedule Later

Run tasks at specific times.

Pattern 4: Retry Logic

Auto Retry

Failed jobs retry automatically.

Pattern 5: Storage

File Upload

Store files reliably and cheaply.

Monitoring

Track queue health continuously.

FAQ

Q1: Which queue?

Redis for simple, Kafka for streaming.

Q2: Handle failures?

Dead letter queue and alerts.

Q3: Cost?

Redis: $20-50/month, Kafka: $100+/month.

Q4: Scaling?

Add more workers easily.

Q5: Storage egress?

Cloudflare R2 has zero egress fees.

Conclusion

Queues enable reliable async systems.

Build for scale from day one.