Chandra Shekhar Pandey, Author at Red Hat Developer

Areas of Expertise

Red Hat JBoss Fuse, Red Hat JBoss AMQ, Activemq, FIS, Openshift, Java

Red Hat AMQ 6.3 on OpenShift: Set up, connect SSL client, and configure logging

By Chandra Shekhar Pandey March 28, 2019September 3, 2019

In this article, we will discuss how to set up Red Hat AMQ 6.3 on OpenShift. We will also set up an external Camel-based SSL client to connect to AMQ Broker, a pure-Java multiprotocol message broker.

By using the procedures in this article, you can easily set up the broker in your OpenShift environment and also set up a Camel-based client to quickly produce and consume messages. Also, you can change the log level to get verbose logs, thus getting a better understanding of the complete setup.

I recommend using a source-to-image (s2i) approach for deploying Red Hat AMQ 6.x on OpenShift, but if you do not use an s2i approach, this article will help you to configure logging to get verbose logs. Note that the Red Hat AMQ image used here is ephemeral; it doesn’t support persistence.

Continue reading “Red Hat AMQ 6.3 on OpenShift: Set up, connect SSL client, and configure logging”

How to configure a JDBC Appender for Red Hat Fuse 7 with Karaf

By Chandra Shekhar Pandey January 23, 2019January 23, 2019

For some integration projects it is helpful to persist application logs in a relational database instead of a plain log file. In this article, I show how to configure a JDBC appender for Red Hat Fuse 7 running in an Apache Karaf environment. There are instructions that describe how to persist messagess with PostgreSQL. Instead, I will show how to setup a JDBC appender for Oracle Database 11g.

I have tested this procedure with Oracle Database 11g Express Edition. A major difference I found is with the table syntax and the fact that the Oracle Database 11g sequence and trigger were required to auto-generate the primary key. Hence, users of Oracle Database 11g should find this article useful.

Continue reading “How to configure a JDBC Appender for Red Hat Fuse 7 with Karaf”

Logging incoming and outgoing messages for Red Hat AMQ 7

By Chandra Shekhar Pandey October 26, 2018September 3, 2019

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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Using the STOMP Protocol with Apache ActiveMQ Artemis Broker

By Chandra Shekhar Pandey June 14, 2018September 3, 2019

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.

Continue reading “Using the STOMP Protocol with Apache ActiveMQ Artemis Broker”

Setting Up a Failover Scenario Using Apache Camel ZooKeeper

By Chandra Shekhar Pandey April 3, 2018April 3, 2018

In this article, we will discuss using the Apache Camel ZooKeeper component, and demonstrate how easily we can set up a fail-over scenario for Apache Camel Routes. While working in a clustered environment, situations arise where a user wants to have a backup or slave route which will become active only when the master (or the currently active) route stops working. There are different ways to achieve this: one can use Quartz to configure a master-slave setup; JGroups can also be used. In a Fabric8 environment, there is a master component which can easily be set up as a failover scenario.

Continue reading “Setting Up a Failover Scenario Using Apache Camel ZooKeeper”

Deploying a Spring Boot App with MySQL on OpenShift

By Chandra Shekhar Pandey March 27, 2018January 29, 2019

This article shows how to take an existing Spring Boot standalone project that uses MySQL and deploy it on Red Hat OpenShift, In the process, we’ll create docker images which can be deployed to most container/cloud platforms. I’ll discuss creating a Dockerfile, pushing the container image to an OpenShift registry, and finally creating running pods with the Spring Boot app deployed.

To develop and test using OpenShift on my local machine, I used Red Hat Container Development Kit (CDK), which provides a single-node OpenShift cluster running in a Red Hat Enterprise Linux VM, based on minishift. You can run CDK on top of Windows, macOS, or Red Hat Enterprise Linux. For testing, I used Red Hat Enterprise Linux Workstation release 7.3. It should work on macOS too.

To create the Spring Boot app I used this article as a guide. I’m using an existing openshift/mysql-56-centos7 docker image to deploy MySQL to OpenShift.

Continue reading “Deploying a Spring Boot App with MySQL on OpenShift”

Enabling Byteman Script with Red Hat JBoss Fuse and AMQ – Part 2

By Chandra Shekhar Pandey January 18, 2018January 19, 2018

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.

Continue reading “Enabling Byteman Script with Red Hat JBoss Fuse and AMQ – Part 2”

Enabling Byteman Script with Red Hat JBoss Fuse and AMQ – Part1

By Chandra Shekhar Pandey January 2, 2018January 12, 2018

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.

Continue reading “Enabling Byteman Script with Red Hat JBoss Fuse and AMQ – Part1”

Using Camel-Undertow component supporting http2 connection

By Chandra Shekhar Pandey December 12, 2017December 11, 2017

This article would help to configure http2 protocol support for the camel-undertow component.

Camel’s undertow component use embedded undertow web-container of version undertow-core:jar:1.4.21. This version also supports the http2 connection.
I have used camel version 2.21.0-SNAPSHOT from upstream https://github.com/apache/camel.
Also, the curl version to test application using camel-undertow component is 7.53.1. This curl version supports –http2 flag for sending an http2 request.
I have also used nghttp to test application from linux terminal. However, this article is not about http2 insights.
For http2 details, I found articles [1] and [2] helpful.

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Configuring mKahaDB persistence storage for ActiveMQ

By Chandra Shekhar Pandey November 22, 2017November 27, 2017

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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Blog Articles

Chandra Shekhar Pandey

Senior Software Maintenance Engineer, Red Hat Pvt Ltd