Chandra Shekhar Pandey

Areas of Expertise

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

Recent Posts

Autoscaling Red Hat Fuse applications with OpenShift

Autoscaling Red Hat Fuse applications with OpenShift

In this article, we demonstrate Red Hat OpenShift’s horizontal autoscaling feature with Red Hat Fuse applications. The result is a Spring Boot-based application that uses the Apache Camel component twitter-search that searches Twitter for tweets based on specific keywords. If traffic or the number of tweets increases, and this application cannot serve all requests, then the application autoscales itself by increasing the number of pods. The ability to serve all requests is monitored by tracking this application’s CPU utilization on a particular pod. Also, as soon as traffic or CPU utilization is back to normal, the number of pods is reduced to the minimum configured value.

There are two types of scaling: horizontal and vertical. Horizontal scaling is where the number of application instances or containers is increased. Vertical scaling is where system resources like CPU and memory are increased at the running application’s or container’s runtime. Horizontal scaling can be used for stateless applications, whereas vertical scaling is more suitable for stateful applications.

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4 steps to set up the MQTT secure client for Red Hat AMQ 7.4 on OpenShift

4 steps to set up the MQTT secure client for Red Hat AMQ 7.4 on OpenShift

In this article, we show how to set up Red Hat AMQ 7.4 on Red Hat OpenShift. Also, we show how to connect the external Message Queuing Telemetry Transport (MQTT) secure client to the AMQ 7.4 platform. MQTT is a Java-based client that uses the Eclipse Paho library and can publish and consume messages from Red Hat AMQ 7.4 Broker on OpenShift using secure transport. These commands and code have been verified with OpenShift 3.11.

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

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

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.

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

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

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.

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Logging incoming and outgoing messages for Red Hat AMQ 7

Logging incoming and outgoing messages for Red Hat AMQ 7

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

Using the STOMP Protocol with Apache ActiveMQ Artemis Broker

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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Setting Up a Failover Scenario Using Apache Camel ZooKeeper

Setting Up a Failover Scenario Using Apache Camel ZooKeeper

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.

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Deploying a Spring Boot App with MySQL on OpenShift

Deploying a Spring Boot App with MySQL on OpenShift

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.

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

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

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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