OpenShift Container Platform

Easing application development on Red Hat OpenShift with odo

Easing application development on Red Hat OpenShift with odo

Have you ever developed applications on a platform like Red Hat OpenShift?

I’m a Java developer with more than 15 years of coding experience, and although I’ve been working with OpenShift for more than three years now, I haven’t found it especially easy to use as a day-to-day development platform. Why? There are many reasons, but the key ones involve complexity and speed. In this article, I’ll explain further and provide an introduction to the odo command-line tool.

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Using Quiver with AMQ on Red Hat OpenShift Container Platform

Using Quiver with AMQ on Red Hat OpenShift Container Platform

As part of the Red Hat UKI Professional Services team, I have worked with several customers who are implementing AMQ Broker on Red Hat OpenShift Container Platform (OCP). One question customers typically ask is, “How do we validate that the AMQ configuration is correct for our scenario?” Previously, I would have suggested one of the following:

These tools can give you indicators around:

  • Is the broker up and running? That is, can it receive/publish messages for this configuration?
  • Can the broker handle a certain performance characteristic? That is, what is my minimum publish rate per second for this configuration?
  • And much more.

The problem with these tools is that you cannot choose the client technology. This could lead to real-world differences and limited technology choices, which in turn might lead you down the wrong technology path. In other words:

  • Do you get the same performance from JMeter versus the AMQ clients you would use in production? Are you comparing like for like? Apples with apples?

So, what do I think is the answer? Quiver [1]. In this article, I’ll provide an overview and demo of using Quiver with Red Hat AMQ on Red Hat OpenShift.  If you’re looking for more information on Red Hat AMQ and how it can help, check out this webinar.

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Red Hat OpenShift 3.11 disconnected installation using Satellite Docker registry

Red Hat OpenShift 3.11 disconnected installation using Satellite Docker registry

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:

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Announcing Red Hat CodeReady Studio, the latest evolution of Red Hat Developer Studio

Announcing Red Hat CodeReady Studio, the latest evolution of Red Hat Developer Studio

Red Hat has been shipping a distribution of Eclipse IDE for years now, including all of the great features of Eclipse along with the add-ons, plugins, and tooling that make working with our products easy and enjoyable. These distributions have gone by different names over the years to indicate how they fit into the Red Hat ecosystem, and to tap into the trust that developers have when they think about Red Hat and what a Red Hat product means for them: it’ll be reliable; it’ll have a published lifecycle; it’s built from source; and if you submit a bug, we’ll fix it (and give the fix to the community). This change is no different.

Red Hat CodeReady Studio is the latest evolution of Red Hat Developer Studio, which itself was an evolution of JBoss Developer Studio. We’re proud to include our distribution of Eclipse IDE in the expanding CodeReady portfolio. Based on the latest Eclipse 4.11, with the latest additions of JBoss Tools and end-to-end testing that ensures everything works as expected, developers can count on the same great experience they’ve grown used to. With tools for working with Fuse and other middleware products and connectors for Red Hat OpenShift that enable super-fast, container-native “inner loop” development cycles, CodeReady Studio is absolutely one of the best desktop IDEs an enterprise JavaTM developer can use.

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IoT edge development and deployment with containers through OpenShift: Part 1

IoT edge development and deployment with containers through OpenShift: Part 1

Usually, we think about IoT applications as something very special made for low power devices that have limited capabilities. For this reason, we tend to use completely different technologies for IoT application development than the technology we use for creating a datacenter’s services.

This article is part 1 of a two-part series. In it, we’ll explore some techniques that may give you a chance to use containers as a medium for application builds—techniques that enable the portability of containers across different environments. Through these techniques, you may be able to use the same language, framework, or tool used in your datacenter straight to the “edge,” even with different CPU architectures!

We usually use “edge” to refer to the geographic distribution of computing nodes in a network of IoT devices that are at the “edge” of an enterprise. The “edge” could be a remote datacenter or maybe multiple geo-distributed factories, ships, oil plants, and so on.

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Integration of storage services (part 6)

Integration of storage services (part 6)

In Part 5 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. Now it’s time to cover various blueprint details.

This article covers the final elements in the blueprint, storage services, which are fundamental to the generic architectural overview.

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Automating tests and metrics gathering for Kubernetes and OpenShift  (part 3)

Automating tests and metrics gathering for Kubernetes and OpenShift (part 3)

This is the third of a series of three articles based on a session I held at Red Hat Tech Exchange EMEA. In the first article, I presented the rationale and approach for leveraging Red Hat OpenShift or Kubernetes for automated performance testing, and I gave an overview of the setup. In the second article, we looked at building an observability stack. In this third part, we will see how the execution of the performance tests can be automated and related metrics gathered.

An example of what is described in this article is available in my GitHub repository.

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Announcing .NET Core 2.2 for Red Hat Platforms

Announcing .NET Core 2.2 for Red Hat Platforms

We are very excited to announce the general availability of .NET Core 2.2 for Red Hat Enterprise Linux and OpenShift platforms! This general availability is in lock-step with Microsoft’s release yesterday.

.NET Core is the open-source, cross-platform .NET platform for building microservices. .NET Core is designed to provide the best performance at scale for applications that use microservices and containers. Libraries can be shared with other .NET platforms, such as .NET Framework (Windows) and Xamarin (mobile applications). With .NET Core you have the flexibility of building and deploying applications on Red Hat Enterprise Linux or in containers. Your container-based applications and microservices can easily be deployed to your choice of public or private clouds using Red Hat OpenShift. All of the features of OpenShift and Kubernetes for cloud deployments are available to you.

.NET Core 2.2 continues to broaden its support and tools for application development in an open source environment. The latest version of .NET Core includes the following improvements:

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Quickly try Red Hat Process Automation Manager in your cloud

Quickly try Red Hat Process Automation Manager in your cloud

It’s been some time since I last talked with you about putting JBoss BPM Suite (now called Red Hat Process Automation Manager) into your cloud, and with the new release, it’s time to talk AppDev in the cloud again.

It’s time to update the story and see how to put Red Hat Process Automation Manager in your cloud so you are set up with a standard configuration to start your first business rules project.

With the easy installation demo project described below, you can leverage process automation tooling through the business central web console running containerized on any Red Hat OpenShift.

Let’s take a closer look at how this works.

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EventFlow: Event-driven microservices on OpenShift (Part 1)

EventFlow: Event-driven microservices on OpenShift (Part 1)

This post is the first in a series of three related posts that describes a lightweight cloud-native distributed microservices framework we have created called EventFlow. EventFlow can be used to develop streaming applications that can process CloudEvents, which are an effort to standardize upon a data format for exchanging information about events generated by cloud platforms.

The EventFlow platform was created to specifically target the Kubernetes/OpenShift platforms, and it models event-processing applications as a connected flow or stream of components. The development of these components can be facilitated through the use of a simple SDK library, or they can be created as Docker images that can be configured using environment variables to attach to Kafka topics and process event data directly.

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