Red Hat AMQ

Understanding Red Hat AMQ Streams components for OpenShift and Kubernetes: Part 3

Understanding Red Hat AMQ Streams components for OpenShift and Kubernetes: Part 3

In the previous articles in this series, we first covered the basics of Red Hat AMQ Streams on OpenShift and then showed how to set up Kafka Connect, a Kafka Bridge, and Kafka Mirror Maker. Here are a few key points to keep in mind before we proceed:

  • AMQ Streams is based on Apache Kafka.
  • AMQ Streams for the Red Hat OpenShift Container Platform is based on the Strimzi project.
  • AMQ Streams on containers has multiple components, such as the Cluster Operator, Entity Operator, Mirror Maker, Kafka connect, and Kafka Bridge.

Now that we have everything set up (or so we think), let’s look at monitoring and alerting for our new environment.

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Understanding Red Hat AMQ Streams components for OpenShift and Kubernetes: Part 1

Understanding Red Hat AMQ Streams components for OpenShift and Kubernetes: Part 1

Red Hat AMQ Streams is an enterprise-grade Apache Kafka (event streaming) solution, which enables systems to exchange data at high throughput and low latency. AMQ Streams is available as part of the Red Hat AMQ offering in two different flavors: one on the Red Hat Enterprise Linux platform and another on the OpenShift Container Platform. In this three-part article series, we will cover AMQ Streams on the OpenShift Container Platform.

To get the most out of these articles, it will help to be familiar with messaging concepts, Red Hat OpenShift, and Kubernetes.

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Set up Red Hat AMQ 7 custom certificates on OpenShift

Set up Red Hat AMQ 7 custom certificates on OpenShift

Secure communication over a computer network is one of the most important requirements for a system, and yet it can be difficult to set up correctly. This example shows how to set up Red Hat AMQ 7 end-to-end TLS encryption using a custom X.509 certificate on the Red Hat OpenShift platform.

Prerequisites

You need to have the following in place before you can proceed with this example:

  • An OpenShift cluster up and running.
  • A custom X.509 certificate in PEM format (along with its chain).
  • An active Red Hat Customer Portal account.

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Event-based microservices with Red Hat AMQ Streams

Event-based microservices with Red Hat AMQ Streams

As part of Red Hat’s AMQ offerings, Red Hat offers a Kafka-based event streaming solution both for traditional deployment and microservices-based deployment branded as Red Hat AMQ Streams. The Red Hat OpenShift AMQ Streams deployment option is based on Strimzi, an open source tool that makes Kafka deployment as a container on a Kubernetes platform easy because most of the deployment prerequisites are automated with the OpenShift Operator Framework.

In this article, we look at how to deploy Apache Kafka on Red Hat OpenShift 4, using reasonable sample microservice applications to showcase the endless possibility of innovation brought by OpenShift and Kafka.

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Deploy Red Hat AMQ Streams and Fuse on OpenShift Container Platform 4

Deploy Red Hat AMQ Streams and Fuse on OpenShift Container Platform 4

In the following video, I demonstrate how to deploy Red Hat AMQ Streams (based on upstream Apache Kafka) on OpenShift 4.

I will also demonstrate how to use AMQ Streams in a basic way using Red Hat Fuse.  There is a Camel route exposing a REST endpoint at /goodbye, which—when hit—sends a “Goodbye World” message to the topic.  There is also a timer sending “Hello World” messages periodically to the topic.  A separate Camel route consumes from the topic and logs the messages for our visibility.

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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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Cloud-native messaging on Red Hat OpenShift with Quarkus and AMQ Online

Cloud-native messaging on Red Hat OpenShift with Quarkus and AMQ Online

Quarkus is a Kubernetes-native Java stack tailored for GraalVM and OpenJDK HotSpot, crafted from the best of breed Java libraries and standards, according to the project website. Starting with the 0.17.0 release, Quarkus supports using the Advanced Message Queuing Protocol (AMQP), which is an open standard for passing business messages between applications or organizations.

Red Hat AMQ Online is a Red Hat OpenShift-based mechanism for delivering messaging as a managed service. Previously, we have seen how to use AMQ Online to provision messaging. In this article, we will combine AMQ Online and Quarkus to show how you can create a modern messaging setup on OpenShift using two new technologies from the messaging space.

The guide assumes you have an installation of AMQ Online on OpenShift. Read the installation guide for more information. AMQ Online is based on the EnMasse open source project.

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CDC pipeline with Red Hat AMQ Streams and Red Hat Fuse

CDC pipeline with Red Hat AMQ Streams and Red Hat Fuse

Change Data Capture (CDC) is a pattern that enables database changes to be monitored and propagated to downstream systems. It is an effective way of enabling reliable microservices integration and solving typical challenges, such as gradually extracting microservices from existing monoliths.

With the release of Red Hat AMQ Streams 1.2, Red Hat Integration now includes a developer preview of CDC features based on upstream project Debezium.

This article explains how to make use of Red Hat Integration to create a complete CDC pipeline. The idea is to enable applications to respond almost immediately whenever there is a data change. We capture the changes as they occur using Debezium and stream it using Red Hat AMQ Streams. We then filter and transform the data using Red Hat Fuse and send it to Elasticsearch, where the data can be further analyzed or used by downstream systems.

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Get started with reactive programming with creative Coderland tutorials

Get started with reactive programming with creative Coderland tutorials

The Reactica roller coaster is the latest addition to Coderland, our fictitious amusement park for developers. It illustrates the power of reactive computing, an important architecture for working with groups of microservices that use asynchronous data to work with each other.

In this scenario, we need to build a web app to display the constantly updated wait time for the coaster.

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