Developers are the epicenter for creating solutions, quickly, that enable enterprises to react to evolving ecosystems. At Red Hat, we have embraced rapid, communal evolution since our inception. We were founded on the open source principles that many of you have come to depend on: transparent, open, iterative collaboration that can change the world in a moment.
Continue reading Building Kubernetes applications on OpenShift with Red Hat Marketplace
When I wrote part 3 of this series, Modern web applications on OpenShift: Part 3 — OpenShift as a development environment, I said that was the final part. However, there is new tech that fits in very nicely with deploying modern Web Applications to OpenShift, so part 4 is necessary. As a refresher, in the first article, we looked at how to deploy a modern web application using the fewest commands. In the second part, we took a deeper look into how the new source-to-image (S2I) web app builder works and how to use it as part of a chained build. In the third, we took a look at how to run your app’s “development workflow” on Red Hat OpenShift. This article talks about OpenShift Pipelines and how this tool can be used as an alternative to a chained build.
Continue reading “Modern web applications on OpenShift, Part 4: Openshift Pipelines”
Red Hat OpenShift Serverless 1.5.0 (currently in tech preview) runs on Red Hat OpenShift Container Platform 4.3. It enables stateful, stateless, and serverless workloads to all operate on a single multi-cloud container platform. Apache Camel K is a lightweight integration platform that runs natively on Kubernetes. Camel K has serverless superpowers.
In this article, I will show you how to use OpenShift Serverless and Camel K to create a serverless Java application that you can scale up or down on demand.
Continue reading “Build and deploy a serverless app with Camel K and Red Hat OpenShift Serverless 1.5.0 Tech Preview”
DevNation Live tech talks are hosted by the Red Hat technologists who create our products. These sessions include real solutions plus code and sample projects to help you get started. In this talk, you’ll learn about crafting Kubernetes Operators from Josh Wood and Burr Sutter.
Continue reading Crafting Kubernetes Operators
Red Hat Data Grid helps applications access, process, and analyze data at in-memory speed. Red Hat Data Grid 8.0 is included in the latest update to Red Hat Runtimes, providing a distributed in-memory, NoSQL datastore. This release includes a new Operator for handling complex applications, a new server architecture that reduces memory consumption and increases security, a faster API with new features, a new CLI, and compatibility with a variety of observability tools.
Continue reading Red Hat Data Grid 8.0 brings new server architecture, improved REST API, and more
The Operator Framework is an open source toolkit for managing Kubernetes-native applications. This framework and its features provide the ability to develop tools that simplify complexities, such as installing, configuring, managing, and packaging applications on Kubernetes and Red Hat OpenShift. In this article, we show how to use third-party APIs in Operator-SDK projects.
In projects built with Operator-SDK, only the Kubernetes API schemas are added by default. However, you might need to create, read, update, or delete a resource that is from another API—even one that you created yourself via other Operator projects.
Let’s check out an example scenario: How to create a Route resource from the OpenShift API for an Operator-SDK project.
Continue reading “How to use third-party APIs in Operator SDK projects”
In this article, we will see a similar pattern when writing the REST API in any known framework vs. writing an Operator using Kubernetes’ client libraries. The idea behind this article is not to explain how to write a REST API, but instead to explain the internals of Kubernetes by working with an analogy.
To follow along, you will need the following installed:
As a developer, if you have used the REST API with frameworks like Quarkus/Spring (Java), Express (Nodejs), Ruby on Rails, Flask (Python), Golang (mux), etc., understanding and writing an operator will be easier for you. We will use this experience with other languages or frameworks to build our understanding.
Continue reading “Operator pattern: REST API for Kubernetes and Red Hat OpenShift”
You might find yourself in situations where you believe that a logic implementation should occur only if and when your Operator is running on a specific Kubernetes platform. So, you probably want to know how to get the cluster vendor from the operator. In this article, we will discuss why relying on the vendor is not a good idea. Also, we will show how to solve this kind of scenario.
Continue reading “Why not couple an Operator’s logic to a specific Kubernetes platform?”
The Red Hat Integration Q4 release adds many new features and capabilities with an increasing focus around cloud-native data integration. The features I’m most excited about are the introduction of the schema registry, the advancement of change data capture capabilities based on Debezium to technical preview, and data virtualization (technical preview) capabilities.
Data integration is a topic that has not received much attention from the cloud-native community so far, and we will cover it in more detail in future posts. Here, we jump straight into demonstrating the latest release of data virtualization (DV) capabilities on Red Hat OpenShift 4. This is a step-by-step visual tutorial describing how to create a simple virtual database using Red Hat Integration’s data virtualization Operator. By the end of the tutorial, you will learn:
- How to deploy the DV Operator.
- How to create a virtual database.
- How to access the virtual database.
The steps throughout this article work on any Openshift 4.x environment with operator support, even on time- and resource-constrained environments such as the Red Hat OpenShift Interactive Learning Portal.
Continue reading “First steps with the data virtualization Operator for Red Hat OpenShift”
In this article, we take a look at user flow improvements for deploying applications in Red Hat OpenShift 4.3‘s Developer perspective. You can learn more about all of the developer-focused console improvements in the OpenShift 4.3 release article here. Since the initial launch of the Developer perspective in the OpenShift 4.2 release, we’ve had frequent feedback sessions with developers, developer advocates, stakeholders, and other community members to better understand how the experience meets their needs. While, overall, the user interface has been well received, we continue to gather and use the feedback to enhance our flows.
Continue reading Deploying applications in the OpenShift 4.3 Developer perspective