Mule 4 Integration with ActiveMQ in AWS

ActiveMQ is message-oriented middleware open-source protocol that is developed by Apache. Its basic function is to send messages between different applications. Amazon managed the implementation of ActiveMQ and integrates it into its AWS cloud services. ActiveMQ makes use of the JMS (Java Message Service) API, which is used to create, send and receive messages.

ActiveMQ which is used in MuleSoft & supports JMS 1.1 and J2EE 1.4 specifications is easy to configure, and its support transport protocols like TCP, AMQP, SSL etc.

This article will describe a step-by-step guide to configure ActiveMQ in AWS and Mule project to integrate ActiveMQ.


  • Mule Runtime 4.2.2
  • Java 1.8
  • AWS account
  • Anypoint Studio7.4


1. Login to AWS Console and then click Amazon MQ

2. Create ActiveMQ broker

3. Select a deployment and storage type then click the next button at the bottom of the page

4. Type broker name, username, and password

5. It will take around 20-25 minutes to create the broker

6. Check the ActiveMQ web console

Note: Please check the security groups for inbound rules of the port.

7. Login to ActiveMQ web console, go to the send menu and create a message payload

8. Go to the Queues menu and verify the queue

9. Create a mule project with a JMS connector to connect with ActiveMQ. Create a mule Flow, drag and drop JMS listener and configure the JMS connector. Select Broker URL from ActiveMQ console and use the username, password which was mentioned in the broker creation process. Test the Connection. After successful connection, deploy the project.

10. After successful deployment, JMS listener will consume the message, log the payload and in the end, will acknowledge the message. Verify the ActiveMQ web console.

Conclusion: Messaging as integration leads to benefits:

  • The client’s applications don’t need to know where the back-end applications are located
  • The producers/consumers of messages don’t have to be active at the same time
  • Scale horizontally by adding services that can handle the messages if too many messages are arrive
  • The client can invoke a message and continue other processing instead of blocking until the service has sent feedback; it can process the response message only when the message is ready.

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