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How to run Red Hat CodeReady Containers on Windows 10 Enterprise

How to run Red Hat CodeReady Containers on Windows 10 Enterprise

Red Hat CodeReady Containers allows you to spin up a small Red Hat OpenShift cluster on your local PC, with the need for a server, a cloud, or a team of operations people. For developers who want to get started immediately with cloud-native development, containers, and Kubernetes (as well as OpenShift), it’s a simple and slick tool. It runs on macOS, Linux, and all versions of Windows 10.

Except for Windows 10 Enterprise.

Which I painfully learned.

Because I lazily didn’t pay attention to the documentation.

OK, so I’m the only developer who glosses over documentation. Fortunately for you, I struggled and managed to get CRC running on my Windows 10 Enterprise notebook computer, and this article explains what is involved to get it working. So, in a sense, you’re welcome that I’m lazy.

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Install Red Hat OpenShift Operators on your laptop using Red Hat CodeReady Containers and Red Hat Marketplace

Install Red Hat OpenShift Operators on your laptop using Red Hat CodeReady Containers and Red Hat Marketplace

Red Hat CodeReady Containers (CRC) is the quickest way for developers to get started with clusters on Red Hat OpenShift 4.1 or newer. CodeReady Containers is designed to run on a local computer. It simplifies setup and testing by emulating the cloud development environment locally with all of the tools that you need to develop container-based applications.

Red Hat Marketplace is an open cloud marketplace that makes it easy to discover and purchase the certified, containerized tools you need to build enterprise-first applications. It was created to help developers using OpenShift build applications and deploy them across a hybrid cloud. Red Hat Marketplace works on any developer workstation that is running CodeReady Containers.

This article guides you through the steps of setting up Red Hat Marketplace and installing containerized products in your local CodeReady Containers-based OpenShift clusters.

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Enable OpenShift Virtualization on Red Hat OpenShift

Enable OpenShift Virtualization on Red Hat OpenShift

Imagine an information technology (IT) world where everything is ideal: Every company has switched over to cloud-native applications, every application is containerized, everything is automated, and the IT people see that the world is good. Things are not so ideal in the real world, though, as we know. Applications remain tightly coupled with traditional virtual machine (VM) resources such as software libraries and hardware resources. The effort to migrate them from VMs to containers seems insurmountable, requiring years of dedicated spending and hours from developers and software architects.

The dilemma is that companies want all of their applications to eventually run on containers, but they also need to support applications running on VMs until that glorious shift happens. Given that application migration from VMs to containers will happen over the long haul, some companies are exploring a lift-and-shift approach. In theory, lift-and-shift would let us migrate tightly-coupled legacy applications to a container platform like Red Hat OpenShift. Rather than rewriting application code, developers would simply write interfaces (essentially, code with patterns) that are compatible with the existing structure.

Unfortunately, this scenario is unrealistic for legacy projects involving hundreds of application modules and packages. Therefore, it is logical to ask: What if there was a way to support existing applications running on virtual machines and new applications running on containers in one unified container-based platform?

Luckily, there is a way: Use a Kubernetes-based platform like OpenShift.

In this article, I introduce OpenShift Virtualization, a feature for Red Hat OpenShift Container Platform (OCP). OpenShift Virtualization allows you to run and manage virtual-machine workloads alongside container workloads.

Note: As of version 2.4 when CNV went GA, Container-Native Virtualization was renamed OpenShift Virtualization.

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New features in Red Hat CodeReady Studio 12.16.0.GA and JBoss Tools 4.16.0.Final for Eclipse 2020-06

New features in Red Hat CodeReady Studio 12.16.0.GA and JBoss Tools 4.16.0.Final for Eclipse 2020-06

JBoss Tools 4.16.0 and Red Hat CodeReady Studio 12.16 for Eclipse 4.16 (2020-06) are now available. For this release, we focused on improving Quarkus– and container-based development and fixing bugs. We also updated the Hibernate Tools runtime provider and Java Developer Tools (JDT) extensions, which are now compatible with Java 14. Additionally, we made many changes to platform views, dialogs, and toolbars in the user interface (UI).

This article is an overview of what’s new in JBoss Tools 4.16.0 and Red Hat CodeReady Studio 12.16 for Eclipse 4.16 (2020-06).

Installation

First, let’s look at how to install these updates. CodeReady Studio (previously Red Hat Developer Studio) comes with everything pre-bundled in its installer. Simply download the installer from the Red Hat CodeReady Studio product page and run it as follows:

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Debugging vHost user TX contention in Open vSwitch

Debugging vHost user TX contention in Open vSwitch

It isn’t always easy to understand how Open vSwitch (OVS) cycles are spent, especially because various parameters and configuration options can affect how OVS behaves. Members of the Open vSwitch community are actively working to understand what causes packets drops in Open vSwitch. Efforts so far have included adding a custom statistic for vHost TX retries, tracking vHost TX contention, and adding a coverage counter to count vHost IRQs. We are particularly interested in the user space datapath that uses the Data Plane Development Kit (DPDK) for fast I/O.

Adding these statistics is an ongoing effort, and we won’t cover all of the corners. In some cases, the statistics leave doubts about what is causing a behavior.

In this article, I will introduce a new counter we’ve added to learn more about contention in the vHost transmission path. I’ll also show you how to use the new counter with perf, and I’ll discuss what’s next for our ongoing efforts.

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Red Hat Universal Base Images for Docker users

Red Hat Universal Base Images for Docker users

Red Hat Universal Base Images (UBIs) allow developers using Docker on Windows and Mac platforms to tap into the benefits of the large Red Hat ecosystem. This article demonstrates how to use Red Hat Universal Base Images with Docker from a non-Red Hat system, such as a Windows or Mac workstation.

Red Hat Enterprise Linux and Docker

When Red Hat Enterprise Linux (RHEL) 8 was released almost a year ago, and it came with lots of new features related to containers. The biggest ones were the new container tools (Podman, Buildah, and skopeo) and the new Red Hat Universal Base Images. There was also confusion because RHEL 8 dropped support for the Docker toolset. Some developers thought that they could not work with Docker anymore, and had to either migrate to a Red Hat-ecosystem Linux system such as CentOS or stay away from Red Hat customers.

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Managing JBoss EAP/Wildfly using Jcliff

Managing JBoss EAP/Wildfly using Jcliff

Systems management can be a difficult task. Not only does one need to determine what the end state should be but, more importantly, how to ensure systems attain and remain at this state. Doing so in an automated fashion is just as critical, because there may be a large number of target instances. In regard to enterprise Java middleware application servers, these instances are typically configured using a set of XML based files. Although these files may be manually configured, most application servers have a command-line based tool or set of tools that abstracts the end user from having to worry about the underlying configuration. WebSphere Liberty includes a variety of tools to manage these resources, whereas JBoss contains the jboss-cli tool.

Although each tool accomplishes its utilitarian use case as it allows for proper server management, it does fail to adhere to one of the principles of automation and configuration management: idempotence. Ensuring the desired state does not equate to executing the same action with every iteration. Additional intelligence must be introduced. Along with idempotence, another core principle of configuration management is that values be expressed declaratively and stored in a version control system.

Jcliff is a Java-based utility that is built on top of the JBoss command-line interface and allows for the desired intent for the server configuration to be expressed declaratively, which in turn can be stored in a version control system. We’ll provide an overview of the Jcliff utility including inherent benefits, installation options, and several examples showcasing the use.

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Command-line tools for Kubernetes: kubectl, stern, kubectx, kubens

Command-line tools for Kubernetes: kubectl, stern, kubectx, kubens

If you’ve ever worked with your hands, you know that you can’t do the job right without the right tools. That adage carries over quite well to software development as well. The right tools can make the difference between success or failure, regardless of the underlying technology. In the Kubernetes ecosystem, more and more tools are being introduced as folks find ways to solve a common problem. This article looks are four of those tools.

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How to run systemd in a container

How to run systemd in a container

I have been talking about systemd in a container for a long time. Way back in 2014, I wrote “Running systemd within a Docker Container.” And, a couple of years later, I wrote another article, “Running systemd in a non-privileged container,” explaining how things hadn’t gotten much better. In that article, I stated, “Sadly, two years later if you google Docker systemd, this is still the article people see—it’s time for an update.” I also linked to a talk about how upstream Docker and upstream systemd would not compromise. In this article, I’ll look at the progress that’s been made and how Podman can help.

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