How to Set Up RabbitMQ with Docker Compose

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RabbitMQ is an open-source message broker that simplifies the process of handling message queues, enabling applications to communicate with each other asynchronously, distribute tasks across worker nodes, and balance loads efficiently. Deploying RabbitMQ using Docker Compose can streamline the setup, making it straightforward to get a RabbitMQ server running for development, testing, or production environments. This guide will walk you through deploying RabbitMQ with the management plugin enabled, using Docker Compose.

Table of Contents

Prerequisites

Before you start, ensure you have:

Docker installed on your system.
Docker Compose installed on your system.
Basic familiarity with Docker concepts and YAML syntax.

Step 1: Create a Docker Compose File

First, create a directory to house your RabbitMQ setup. This directory will contain your Docker Compose file (docker-compose.yml) and any additional configuration files you might need.

mkdir rabbitmq-docker && cd rabbitmq-docker

Next, create the docker-compose.yml file:

touch docker-compose.yml

Open this file in a text editor and add the following configuration:

version: '3.8'

services:
  rabbitmq:
    image: rabbitmq:3-management
    container_name: rabbitmq
    environment:
      RABBITMQ_DEFAULT_USER: user
      RABBITMQ_DEFAULT_PASS: password
    ports:
      - "5672:5672" # RabbitMQ server
      - "15672:15672" # Management plugin
    volumes:
      - "rabbitmq_data:/var/lib/rabbitmq"
    restart: unless-stopped

volumes:
  rabbitmq_data:

Configuration Explained:

image: Uses the rabbitmq:3-management Docker image, which includes the RabbitMQ server and the management plugin.
container_name: Sets a custom name for the container.
environment: Defines environment variables to set the default username (user) and password (password) for RabbitMQ. You should change these values to secure your instance.
ports: Maps port 5672 for RabbitMQ server connections and port 15672 for accessing the management plugin through a web browser.
volumes: Persists RabbitMQ data to a Docker volume (rabbitmq_data), ensuring data remains intact across container restarts.
restart: Configures the container to restart automatically unless explicitly stopped, ensuring high availability.

Step 2: Launch RabbitMQ

With your docker-compose.yml file ready, launch RabbitMQ by running the following command in the directory containing your Docker Compose file:

docker compose up -d

This command starts RabbitMQ in detached mode, running in the background.

Step 3: Access RabbitMQ Management Plugin

Once RabbitMQ is up and running, you can access the management plugin by navigating to http://localhost:15672 in a web browser. Log in using the default credentials you set in the Docker Compose file (user as the username and password as the password).

Step 4: Managing RabbitMQ

The RabbitMQ management plugin provides a user-friendly web interface for managing your RabbitMQ server. From here, you can:

Create and manage queues: Define new queues, monitor queue length, and inspect messages.
Manage exchanges and bindings: Create and configure exchanges, and bind them to queues.
Monitor your RabbitMQ instance: View important metrics such as message rates, numbers of connections, and more.

Conclusion

Deploying RabbitMQ with Docker Compose offers a straightforward and efficient method for setting up a RabbitMQ server, complete with the management plugin. Following the steps outlined in this guide, you can quickly get a RabbitMQ instance running on your system, ready to handle message queuing for your applications. Docker Compose simplifies the process of managing the RabbitMQ service, making it an ideal choice for developers and system administrators.

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Anastasios Antoniadis

Anastasios Antoniadis is the founder and editor-in-chief of BORDERPOLAR... He is a software engineer, blogger, and avid gamer covering tech, gaming, and coding guides for over 4 years. He is a 2014 graduate of the Department of Informatics and Telecommunications of the University of Athens, an M.Sc. holder in Computer Science, and a Ph.D. student in Program Analysis.