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Kafka Fail-Over Using Quarkus Reactive Messaging

Background

Recently, I came across a scenario where, at first glance, we needed an active-active Kafka cluster with bi-directional replication using MirrorMaker2. However, while diving deeper into the nuances of the solution that this particular project demanded, a number of factors showed this wasn't really the case. For example, a look at how the producers/consumers will handle temporary failure and/or guarantee exactly-once processing downstream added a ton of complexity to the problem. 

By taking a step back to the design board, we changed the approach to an active-standby scenario. In this scenario, the active cluster will replicate all its configs, consumer groups, and topics to the standby cluster that will become active in case of failure.  However, this posed a problem: how can I get the minimum possible downtime in my producers without the need to restart them with the new configuration for the new cluster?

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Building a Multi-Feature Pipeline With OpenShift Pipelines

Hi, all! Some Development/Agile/Git workflows make use of multiple feature branches to coordinate their Sprints/Development cycles.

One thing that I saw while working with certain clients is that for every feature, they created a pipeline. This process (although automated in most places) generated a ton of useless and repetitive pipelines.

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Deploying a Scala API on OpenShift With OpenShift Pipelines

I recently took a course on Scala Basics. To further my knowledge, I decided to deploy a simple API on OpenShift using the Pipelines feature and build it using the Scala build tool(not Maven, as there are plenty of tasks for that).

Phase 1

First, we need an app, so as a part of the course, I developed a simple expense tracking API that has all the CRUD features and an endpoint to sum all your expenses. I'm going to walk you through the app. In order to build an API, we're going to leverage the use of the Play Framework.

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SOAP Transformation With Apache Camel Java DSL

One of the most common issues that we usually tackle with customers when modernizing legacy integrations is when they have a collection of legacy SOAP web services that don't integrate well enough with the modern RESTful-based clients.

In this article, we are going to use Apache Camel to build a REST endpoint that will translate REST calls to a SOAP envelope, get the response, and send it back to the client.