In Part 6 of this series, we looked into details that determine how your integration becomes the key to transforming your customer experience. It started with laying out the process of how I’ve approached the use case by researching successful customer portfolio solutions as the basis for a generic architectural blueprint.
Having completed our discussions on the blueprint details, it’s time to look at a few specific examples. This article walks you through an example integration scenario showing how expanding the previously discussed details provides blueprints for your own integration scenarios.
Continue reading “Integration blueprint example for process automation (part 7)”
After being introduced to Linux containers and running a simple application, the next step seems obvious: How to get multiple containers running in order to put together an entire system. Although there are multiple solutions, the clear winner is Kubernetes. In this article, we’ll look at how Kubernetes facilitates running multiple containers in a system.
Continue reading “Introduction to Kubernetes: From container to containers”
You’ve crushed the whole containers thing—it was much easier than you anticipated, and you’ve updated your resume. Now it’s time to move into the spotlight, walk the red carpet, and own the whole Kubernetes game. In this blog post, we’ll get our Kubernetes environment up and running on Windows 10, spin up an image in a container, and drop the mic on our way out the door—headed to Coderland.
Continue reading “How to set up your first Kubernetes environment on Windows”
By following my previous article in this series, you’ve crushed the whole containers thing. It was much easier than you anticipated, and you’ve updated your resume. Now it’s time to move into the spotlight, walk the red carpet, and own the whole Kubernetes game. In this blog post, we’ll get our Kubernetes environment up and running on macOS, spin up an image in a container, and head to Coderland.
Continue reading “How to set up your first Kubernetes environment on macOS”
In this article, I will discuss the prerequisites and requirements for the successful implementation of Red Hat OpenShift 3.11 disconnected installation using Red Hat Satellite as the local Docker registry, which I have been able to do with the support of my colleagues. I also discuss adjustments that may be required post install.
This work is based on the following references:
Continue reading “Red Hat OpenShift 3.11 disconnected installation using Satellite Docker registry”
We are extremely pleased to announce that the preview release of the Red Hat OpenShift Connector for JetBrains products (IntelliJ IDEA, WebStorm, etc.) is now available in Preview Mode and supports Java and Node.js components. You can download the OpenShift Connector plugin from the JetBrains marketplace or install it directly from the plugins gallery in JetBrains products.
In this article, we’ll look at features and benefits of the plugin and installation details, and show a demo of how using the plugin improves the end-to-end experience of developing and deploying Spring Boot applications to your OpenShift cluster.
Continue reading “What Red Hat OpenShift Connector for JetBrains products offers developers”
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”
Are serverless and Function as a Service (FaaS) the same thing?
No, they’re not.
Wait. Yes, they are.
Frustrating, right? With terms being thrown about at conferences, in articles (I’m looking at myself right now), conversations, etc., things can be confusing (or, sadly, sometimes misleading). Let’s take a look at some aspects of serverless and FaaS to see where things stand.
Continue reading “The evolution of serverless and FaaS: Knative brings change”
Red Hat Data Grid is an in-memory, distributed, NoSQL datastore solution. With it, your applications can access, process, and analyze data at in-memory speed to deliver a superior user experience. In-memory Data Grid has a variety of use cases in today’s environment, such as fast data access for low-latency apps, storing objects (NoSQL) in a datastore, achieving linear scalability with data distribution/partitioning, and data high-availability across geographies, among many others. With containers getting more attention, the need to have Data Grid running on a container platform like OpenShift is clear, and we are seeing more and more customers aligning their architecture with a datastore running natively on a container platform.
In this article, I will talk about multiple layers of security available while deploying Data Grid on OpenShift. The layers of security offer a combination of security measures provided by Data Grid as well as by OpenShift/Kubernetes.
Continue reading “Five layers of security for Red Hat Data Grid on OpenShift”
Learn how to use Red Hat OpenShift Application Runtimes launcher to create a new application and deploy it to an OpenShift cluster. The steps described in this video are also explained step by step in the tutorial on GitHub.
Watch the video now:
Continue reading “How to create a new application with Red Hat OpenShift Application Runtimes launcher”