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Deep Dive Into CodeReady Containers Deployment on Linux

Are you considering Red Hat CodeReady Containers (CRC) for your local OpenShift development? Are you going to install CRC on Linux? In this blog, I am going to walk you through the deployment of CRC on Linux. We will take a closer look at how CRC works and review some of the configuration options. Fasten your seatbelts, the tour begins.

This blog uses CRC version 1.21.0, which is based on OpenShift Container Platform (OCP) version 4.6.9. I am installing CRC on Debian 10 GNU/Linux but any modern Linux distribution like Fedora or Ubuntu will do. As of version 1.21.0, CRC can be deployed on a Linux host that meets the following requirements:

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Local Development With OpenShift and Tilt

In this article, I am going to show you how to use Tilt to facilitate local OpenShift development. Tilt's capabilities will be demonstrated in a practical example that uses buildah and CodeReady Containers. If you develop containerized applications on OpenShift, this blog post is for you.

How Does Tilt Facilitate Local Development?

The diagram below depicts a development workflow orchestrated by Tilt. After you execute the tilt up command on your development machine, Tilt will keep running while performing the following actions:

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Open Policy Agent, Part II – Developing Policies

In the previous part of the series, we explored Open Policy Agent and implemented an ACL-based access control for our application. In this entry, I am going to share with you some of the discoveries that I made while evaluating Open Policy Agent in regards to policy design and development.

Policy Design

After evaluating policy rules, OPA returns a result of the policy decision to your application. This result is a JSON structure. Based on your requirements, this JSON structure can contain a single member holding a true or false (authorized/not authorized) value. However, you can create policies whose evaluation results in an arbitrarily complex JSON document. For example, OPA can return a list of nodes on which Kubernetes should schedule a workload.

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Troubleshooting the Performance of Vert.x Applications, Part I – The Event Loop Model

This article is the first in a series of three articles which share my experience with troubleshooting the performance of Vert.x applications. The first article provides an overview of the Vert.x event loop model, the second article covers techniques to prevent delays on the event loop, and the third article focuses on troubleshooting of event loop delays.

Programming with Vert.x requires a good understanding of its event loop model. From what I saw in practice, delayed or blocked event loop threads are the number one contributor to performance problems with Vert.x applications. But don't worry. In this article, we are going to review the event loop model.