Java is one of the most popular programming languages in the world. It has been among the top three languages used over the past two decades. Java powers millions of applications across many verticals and platforms. Linux is widely deployed in data centers, edge networks, and the cloud.
Continue reading Deploy Quarkus everywhere with Red Hat Enterprise Linux (RHEL)
Edge computing continues to gain force as ever more companies increase their investments in edge, even if they’re only dipping their toes in with small-scale pilot deployments. Emerging use cases like Internet-of-Things (IoT), augmented reality, and virtual reality (AR/VR), robotics, and telecommunications-network functions are often cited as key drivers for companies moving computing to the edge. Traditional enterprises are also looking at edge computing to better support their remote offices, retail locations, manufacturing plants, and more. At the network edge, service providers can deploy an entirely new class of services to take advantage of their proximity to customers.
Continue reading Developing at the edge: Best practices for edge computing
In the first part of this series, we saw how effective a platform as a service (PaaS) such as Red Hat OpenShift is for developing IoT edge applications and distributing them to remote sites, thanks to containers and Red Hat Ansible Automation technologies.
Usually, we think about IoT applications as something specially designed for low power devices with limited capabilities. IoT devices might use a different CPU architectures or platform. For this reason, we tend to use completely different technologies for IoT application development than for services that run in a data center.
In part two, we explore some techniques that allow you to build and test contains for alternate architectures such as ARM64 on an x86_64 host. The goal we are working towards is to enable you to use the same language, framework, and development tools for code that runs in your datacenter or all the way out to IoT edge devices. In this article, I’ll show building and running an AArch64 container image on an x86_64 host and then building an RPI3 image to run it on physical hardware using Fedora and Podman.
Continue reading “IoT edge development and deployment with containers through OpenShift: Part 2”
Usually, we think about IoT applications as something very special made for low power devices that have limited capabilities. For this reason, we tend to use completely different technologies for IoT application development than the technology we use for creating a datacenter’s services.
This article is part 1 of a two-part series. In it, we’ll explore some techniques that may give you a chance to use containers as a medium for application builds—techniques that enable the portability of containers across different environments. Through these techniques, you may be able to use the same language, framework, or tool used in your datacenter straight to the “edge,” even with different CPU architectures!
We usually use “edge” to refer to the geographic distribution of computing nodes in a network of IoT devices that are at the “edge” of an enterprise. The “edge” could be a remote datacenter or maybe multiple geo-distributed factories, ships, oil plants, and so on.
Continue reading “IoT edge development and deployment with containers through OpenShift: Part 1”