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.
Continue reading “Enable OpenShift Virtualization on Red Hat OpenShift”
Apache Kafka has become the leading platform for building real-time data pipelines. Today, Kafka is heavily used for developing event-driven applications, where it lets services communicate with each other through events. Using Kubernetes for this type of workload requires adding specialized components such as Kubernetes Operators and connectors to bridge the rest of your systems and applications to the Kafka ecosystem.
In this article, we’ll look at how the open source projects Strimzi, Debezium, and Apache Camel integrate with Kafka to speed up critical areas of Kubernetes-native development.
Note: Red Hat is sponsoring the Kafka Summit 2020 virtual conference from August 24-25, 2020. See the end of this article for details.
Continue reading “Kubernetes-native Apache Kafka with Strimzi, Debezium, and Apache Camel (Kafka Summit 2020)”
Kubernetes Operators reduce the work of human operators or site reliability engineers. Rather than a half-baked definition, I refer you to this original definition from the creators of the Kubernetes Operator Framework: Operators are Kubernetes applications.
Continue reading ‘Hello, World’ tutorial with Kubernetes Operators
As Kubernetes and Red Hat OpenShift platform adoption grow and organizations move a larger portion of their infrastructure to these platforms, organizations are increasingly faced with the challenge of managing hybrid multicluster environments across the public cloud and on-premises infrastructure. While this approach brings flexibility and scalability to managing applications, the ability to ensure configuration consistency across these clusters, and the ability to roll out applications to multiple clusters in a consistent manner becomes a necessity. Enter the Argo CD GitOps Kubernetes Operator.
Continue reading OpenShift joins the Argo CD community (KubeCon Europe 2020)
Open Data Hub (ODH) is a blueprint for building an AI-as-a-Service (AIaaS) platform on Red Hat OpenShift 4. Version 0.7 of Open Data Hub includes support for deploying Kubeflow 1.0 on OpenShift, as well as increased component testing on the OpenShift continuous integration (CI) system. This article explores the recent updates.
Continue reading Open Data Hub 0.7 adds support for Kubeflow 1.0
Prometheus is an open source monitoring solution that collects metrics from the system and its applications. As a developer, you can query these metrics and use them to create alerts, which you can use as a source for dashboards. One example would be using Prometheus metrics with Grafana.
Continue reading Monitoring .NET Core applications on Kubernetes
Red Hat Advanced Cluster Management (ACM) for Kubernetes offers end-to-end visibility and control for managing your cluster and application lifecycle. Among other features, it ensures security and compliance for your entire Kubernetes domain across multiple data centers and public clouds.
Continue reading Installing Red Hat Advanced Cluster Management (ACM) for Kubernetes
The main goal of Kubernetes is to reach the desired state: to deploy our pods, set up the network, and provide storage. This paradigm extends to Operators, which use custom resources to define the state. When the Operator picks up the custom resource, it will always try to get to the state defined by it. That means that if we modify a resource that is managed by the Operator, it will quickly replace it to match the desired state.
Continue reading Open Data Hub and Kubeflow installation customization
Each new release of Red Hat OpenShift includes usability improvements and features to help developers meet their goals. In OpenShift 4.5, we’ve improved navigation and added a mechanism for customizing navigation and accessing frequently used resources from the Developer perspective.
Continue reading What’s new in the OpenShift 4.5 console developer experience
Red Hat CodeReady Workspaces 2.2 is now available. For the improvements in this release, we focused on performance and configuration, plus updating CodeReady Workspaces 2.2 to use newer versions of the most popular runtimes and stacks. We also added the ability to allocate only the CPU that you need for IDE plugins, and we introduced a new diagnostic feature that lets you start up a workspace in debug mode.
CodeReady Workspaces 2.2 is available on OpenShift 3.11 and OpenShift 4.3 and higher, including tech-preview support for OpenShift 4.5.
Note: Based on Eclipse Che, CodeReady Workspaces is a Red Hat OpenShift-native developer environment that supports cloud-native development.
Continue reading “Performance and usability enhancements in Red Hat CodeReady Workspaces 2.2”