As a software developer, it’s often necessary to access a relational database—or any type of database, for that matter. If you’ve been held back by that situation where you need to have someone in operations provision a database for you, then this article will set you free. I’ll show you how to spin up (and wipe out) a MySQL database in seconds using Red Hat OpenShift.
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Red Hat OpenShift 4.1 offers a developer preview of OpenShift Pipelines, which enable the creation of cloud-native, Kubernetes-style continuous integration and continuous delivery (CI/CD) pipelines based on the Tekton project. In a recent article on the Red Hat OpenShift blog, I provided an introduction to Tekton and pipeline concepts and described the benefits and features of OpenShift Pipelines.
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One of the things I enjoy most about using Red Hat OpenShift is the Developer Catalog. The Developer Catalog is a central location where a team working with Red Hat OpenShift can encapsulate and share how application components and services are deployed.
The Developer Catalog is often used to define an infrastructure pattern referred to as a builder image. A builder image is a container image that supports a particular language or framework, following best practices and Source-to-Image (s2i) specifications.
The OpenShift Developer Catalog provides several standard builder images supporting applications written in Node.js, Ruby, Python, and more. And while the Developer Catalog has many easy ways to get started deploying several supported languages, the catalog is also flexible in allowing you to add your own builder images to support an infrastructure pattern that is not preloaded in the catalog.
Continue reading “Using a custom builder image on Red Hat OpenShift with OpenShift Do”
JBoss Tools 4.12.0 and Red Hat CodeReady Studio 12.12 for Eclipse 2019-06 are here and are waiting for you. In this article, I’ll cover the highlights of the new releases and show how to get started.
Continue reading “Get started with Red Hat CodeReady Studio 12.12.0.GA and JBoss Tools 4.12.0.Final for Eclipse 2019-06”
With the release of Red Hat AMQ Streams 1.2, Red Hat Integration now includes a developer preview of Change Data Capture (CDC) capabilities to enable data integration for modern cloud-native microservices-based applications. CDC features are based on the upstream project Debezium and are natively integrated with Apache Kafka and Strimzi to run on top of Red Hat OpenShift Container Platform, the enterprise Kubernetes, as part of the AMQ Streams release.
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In previous articles, I’ve covered two strategies for improving .NET Core build speed on Red Hat OpenShift by reducing time to restore dependencies: adding a local NuGet server and using incremental builds. In this article, I’ll look at another strategy: using a custom base image that has includes the dependencies.
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API-first design is a commonly used approach where you define the interfaces for your application before providing an actual implementation. This approach gives you a lot of benefits. For example, you can test whether your API has the right structure before investing a lot of time implementing it, and you can share your ideas with other teams early to get valuable feedback. Later in the process, delays in the back-end development will not affect front-end developers dependent on your service so much, because it’s easy to create mock implementations of a service from the API definition.
Much has been written about the benefits of API-first design, so this article will instead focus on how to efficiently take an OpenAPI definition and bring it into code with Red Hat Fuse.
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We are thrilled to announce an updated release of the data streaming component of our messaging suite, Red Hat AMQ streams 1.2, which is part of Red Hat integration.
Red Hat AMQ streams, based on the Apache Kafka project, offers a distributed backbone that allows microservices and other applications to share data with extremely high throughput and extremely low latency. AMQ streams makes running and managing Apache Kafka a Kubernetes-native experience, by additionally delivering Red Hat OpenShift Operators, a simplified and automated way to deploy, manage, upgrade and configure a Kafka ecosystem installation on Kubernetes.
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Have you tried Red Hat Enterprise Linux 8 (RHEL8) yet? Read on to learn how to quickly set up a LAMP stack on RHEL8 so you can play around with the new features built into the operating system.
A LAMP stack is made up of four main components and some glue. The first main component in a LAMP stack (the “L”) is Linux. In my example, I’m using Red Hat Enterprise Linux 8 for that, which gives me a secure operating system, a modern programming environment, and a user-friendly set of tools to control it.
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Cloud-native environment architecture can be challenging to understand. To help make sense of it for application developers and software/system architects, I will attempt to explain the various parts and how they work together. Toward this end, I find it helpful to think about the architecture in four separate layers: application software development, service scaling, application network, and container orchestration platform.
In this article, I will describe the first technology layer: application software development. I drew the following diagram to make these concepts easier to visualize.
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