It is very common in an integration landscape to have different components connected using a messaging system such as Red Hat AMQ 7 (RHAMQ 7). In this landscape, usually, there are JEE application servers, such as Red Hat JBoss Enterprise Application Platform 7 (JBoss EAP 7), to deploy and run applications connected to the messaging system.
This article describes in detail how to integrate a remote RHAMQ 7 cluster on a JBoss EAP 7 server, and it covers in detail the different configurations and components and some tips to improve your message-driven beans (MDBs) applications.
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In this article, I will discuss how to capture incoming and outgoing messages for Red Hat AMQ 7 (RHAMQ 7). This might advantageous if you need to log the incoming or outgoing traffic, or the messages from a broker, or during development and/or testing when you want to see all message. Additionally, There may also be a need to modify messages in transit. Using RHAMQ 7 interceptors, you can intercept traffic to and from the RHAMQ 7 broker. You can also modify messages using the interceptor.
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This article describes in detail how to integrate Red Hat A-MQ 6.3 on Red Hat JBoss Enterprise Application Platform (EAP) 7 and covers in detail the admin-object configuration, especially the pool-name configuration. The attribute pool-name for the admin-object explanation can lead to confusion. In this post, I will try to clarify many of the steps, give an overview of the components, and how they fit together.
The JBoss EAP requires the configuration of a resource adapter as a central component for integration with the A-MQ 6.3. In addition, the MDBs configuration on the EAP is required to enable the JMS consumers. On the A-MQ 6.3, the configuration of the Transport Connectors is required to open the communication channel with the EAP.
All the steps required to configure EAP 7 to use A-MQ 6.3 as an external JMS broker are described here:
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One thing that is common in the enterprise world, especially in highly regulated industries, is to have separation of duties. Role-based access controls (RBAC) have built-in support for separation of duties. Roles determine what operations a user can and cannot perform. This post provides an example of how to configure proper RBAC on top of Red Hat AMQ, a flexible, high-performance messaging platform based on the open source Apache ActiveMQ Artemis project.
In most of the cases, separation of duties on Red Hat AMQ can be divided into three primary roles:
- Administrator role, which will have all permissions
- Application role, which will have permission to publish, consume, or produce messages to a specific address, subscribe to topics or queues, or create and delete addresses.
- Operation role, which will have read-only permission via the web console or supported protocols
To implement those roles, Red Hat AMQ has several security features that need be configured, as described in the following sections.
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In this article, we will use a Python-based messaging client to connect and subscribe to a topic with a durable subscription in the Apache ActiveMQ Artemis broker. We will use the text-based STOMP protocol to connect and subscribe to the broker. STOMP clients can communicate with any STOMP message broker to provide messaging interoperability among many languages, platforms, and brokers.
If you need to brush up on the difference between persistence and durability in messaging, check Mary Cochran’s article on developers.redhat.com/blog.
A similar process can be used with Red Hat AMQ 7. The broker in Red Hat AMQ 7 is based on the Apache ActiveMQ Artemis project. See the overview on developers.redhat.com for more information.
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Monitoring Red Hat AMQ 7
Red Hat AMQ 7 includes some tools for monitoring the Red Hat AMQ broker. These tools allow you to get metrics about the performance and behavior of the broker and its resources. Metrics are very important for measuring performance and for identifying issues that are causing poor performance.
The following components are included for monitoring the Red Hat AMQ 7 broker:
- Management web console that is based on Hawtio: This console includes some perspectives and dashboards for monitoring the most important components of the broker.
- A Jolokia REST-like API: This provides full access to JMX beans through HTTP requests.
- Red Hat JBoss Operation Network: This is an enterprise, Java-based administration and management platform for developing, testing, deploying, and monitoring Red Hat JBoss Middleware applications.
These tools are incredible and fully integrated with the original product. However, there are cases where Red Hat AMQ 7 is deployed in environments where other tools are used to monitor the broker, for example,
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In my previous article, Enabling Byteman Script with Red Hat JBoss Fuse and AMQ – Part 1, we found a basic use-case for Byteman scripts with Red Hat JBoss Fuse or Red Hat JBoss AMQ. However, the log file was generated separately and only limited operations were possible. In this article I will show you how to use a Java helper class. By using Java, we get advanced operations to view or modify the content. Also, using java.util.logging allows us to log the statements to fuse.log, avoiding the creation of any other log file.
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In a production or customer environment it is not always possible to identify issues by looking at logs, nor is it always possible to setup remote debugging using an integrated development environment (IDE) and remote debug port. Often the issues are specific to the environment and can’t be reproduced. Having byteman scripts can help in these situations to identify issues without actual code changes. Whenever certain java class or logic is invoked, byteman scripts will also be invoked as per defined class and method in the byteman script.
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In this post, I wanted to address how to configure mKahaDB persistence storage on ActiveMQ for better management and reducing disk usage.
Default configured KahaDB persistence adapter works well when all the destinations (queues/topics) being managed by the broker have similar performance. However, an enterprise solution where several third parties are involved is never the case.
There are multiple queues or topics and different consumers or listeners listening to these queues/topics. Some consumers might be slower than other consumers. This will grow the message store’s disk usage rapidly. Due to this situation and being single KahaDB all store destinations might perform slow.
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