Operator

Open Data Hub 0.6.1: Bug fix release to smooth out redesign regressions

Open Data Hub 0.6.1: Bug fix release to smooth out redesign regressions

It is just a few short weeks since we released Open Data Hub (ODH) 0.6.0, bringing many changes to the underlying architecture and some new features. We found a few issues in this new version with the Kubeflow Operator and a few regressions that came in with the new JupyterHub updates. To make sure your experience with ODH 0.6 does not suffer because we wanted to release early, we offer a new (mostly) bugfix release: Open Data Hub 0.6.1.

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Deploy and bind enterprise-grade microservices with Kubernetes Operators

Deploy and bind enterprise-grade microservices with Kubernetes Operators

Deploying enterprise-grade runtime components into Kubernetes can be daunting. You might wonder:

  • How do I fetch a certificate for my app?
  • What’s the syntax for autoscaling resources with the Horizontal Pod Autoscaler?
  • How do I link my container with a database and with a Kafka cluster?
  • Are my metrics going to Prometheus?
  • Also, how do I scale to zero with Knative?

Operators can help with all of those needs and more. In this article, I introduce three Operators—Runtime Component Operator, Service Binding Operator, and Open Liberty Operator—that work together to help you deploy containers like a pro.

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Open Data Hub 0.6 brings component updates and Kubeflow architecture

Open Data Hub 0.6 brings component updates and Kubeflow architecture

Open Data Hub (ODH) is a blueprint for building an AI-as-a-service platform on Red Hat’s Kubernetes-based OpenShift 4.x. Version 0.6 of Open Data Hub comes with significant changes to the overall architecture as well as component updates and additions. In this article, we explore these changes.

From Ansible Operator to Kustomize

If you follow the Open Data Hub project closely, you might be aware that we have been working on a major design change for a few weeks now. Since we started working closer with the Kubeflow community to get Kubeflow running on OpenShift, we decided to leverage Kubeflow as the Open Data Hub upstream and adopt its deployment tools—namely KFdef manifests and Kustomize—for deployment manifest customization.

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Application deployment improvements in OpenShift 4.4

Application deployment improvements in OpenShift 4.4

The most recent release of Red Hat OpenShift Container Platform provides enhancements and features that make application development even easier. These enhancements include:

  • An enhanced Developer Catalog.
  • Operator-backed services in the Developer Catalog.
  • The GA release of Helm 3.
  • An add context option in the Topology view.

Keep reading to learn more about each of these enhancements in more detail.

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What’s new in the OpenShift 4.4 web console developer experience

What’s new in the OpenShift 4.4 web console developer experience

The developer experience in the Red Hat OpenShift Container Platform web console keeps getting better. You’ve probably already heard about our streamlined user flows to build and deploy applications, plus the ability to understand the structure of your application via the Topology view. Each new release of Red Hat OpenShift includes usability improvements and new features to help developers reach their goals.

In OpenShift 4.4, we focused on making application deployment easier through the Developer Catalog, improving the experience of Operator-backed services, and supporting Helm Charts. As for feature updates, we:

  • Made a number of topology enhancements to help streamline discoverability and scalability.
  • Introduced an application monitoring section.
  • Introduced a new Pipeline Builder.

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Operator SDK: Build Kubernetes Operators and deploy them on OpenShift

Operator SDK: Build Kubernetes Operators and deploy them on OpenShift

The Operator SDK makes it simple to build Kubernetes-native applications, providing the tools to build, test, and package Operators. The SDK also helps the developer to build Operators without requiring knowledge of Kubernetes API complexities.

In this article, we will create a sample Operator for deploying a sample application based on Spring Boot and Camel. This application is a simple Camel route that uses the undertow component. After building the Operator, we will deploy it on an OpenShift cluster.

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Building Kubernetes applications on OpenShift with Red Hat Marketplace

Building Kubernetes applications on OpenShift with Red Hat Marketplace

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.

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Modern web applications on OpenShift, Part 4: Openshift Pipelines

Modern web applications on OpenShift, Part 4: Openshift Pipelines

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.

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Build and deploy a serverless app with Camel K and Red Hat OpenShift Serverless 1.5.0 Tech Preview

Build and deploy a serverless app with Camel K and Red Hat OpenShift Serverless 1.5.0 Tech Preview

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.

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