Fast Iterative Java Development on OpenShift/Kubernetes Using Rsync

Fast Iterative Java Development on OpenShift/Kubernetes Using Rsync

The key to a good development environment almost always comes down to how long it takes for changes you make to take effect. With any compiled language, there is often a lot of setup work involved to optimize deployment speed. Thankfully, one of the promises of containers is it allows for patterns to be standardized and repackaged as reusable images that do a lot of the heavy lifting for you.

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Red Hat Announces Schedule and Speaker Line-Up for OpenShift Commons Gathering March 28th in Berlin

Red Hat Announces Schedule and Speaker Line-Up for OpenShift Commons Gathering March 28th in Berlin

The OpenShift Commons Gathering will bring together the brightest technical minds to discuss the future of OpenShift and its related upstream open source projects. With OpenShift Container Platform quickly gaining adoption around the world, the OpenShift Commons Gathering will feature talks from upstream project leads and case studies from users like Red Hat, Google, Microsoft Azure, Amadeus, T-Systems, Volvo, Weave, CNCF and more. This event will also include face-to-face meetings for all the OpenShift Commons Special Interest Groups and allow ample time for peer-to-peer networking.

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Announcing Easy Interactive OpenShift Tutorials for Developers

Announcing Easy Interactive OpenShift Tutorials for Developers

The OpenShift Developer Evangelist team is happy to release the first iteration of our work with Katacoda – interactive OpenShift tutorials! The idea with these tutorials is that you get your own individual OpenShift environment with instructions right next to it. You can work through the instructions at your own pace but you are using a fully-functioning OpenShift environment with working URLs and all.

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Performance Metrics (APM) for Spring Boot Microservices on OpenShift

Performance Metrics (APM) for Spring Boot Microservices on OpenShift

OpenShift provides a built-in monitoring tool called Hawkular. That tool is in charge of collecting metrics from Docker containers through the Kubernetes interface and storing, aggregating, and visualizing them. The metrics collected are CPU, Memory, Disk, and Network usage. Hawkular offers a “black-box” view of container performance but does not deal with application metrics like service performance or distribution of response time through application layers. For this specific case, the Hawkular community is working on another module called Hawkular APM that provides insight into the way an application executes across multiple (micro) services in a distributed (e.g. cloud) environment.

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Goodbye OpenShift All-In-One VM, Hello Minishift

Goodbye OpenShift All-In-One VM, Hello Minishift

After almost 100,000 downloads, the time has come to retire the OpenShift All-In-One VM. The intent of the VM was to give developers a simple and easy way to bring up OpenShift on their local machine for development purposes. In the meantime, there was movement within the Kubernetes community to create MiniKube – a means to run a Kubernetes “cluster” on your local machine. Jimmi Dyson saw this work and started MiniShift which built off MiniKube except for OpenShift. It fulfills all the original use cases we had for the All-In-One with the added bonus of actually having an engineering team maintaining it!

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Using Dynamic Provisioning and StorageClasses

Using Dynamic Provisioning and StorageClasses

OpenShift can integrate with underlying infrastructure, enabling OpenShift to dynamically interact with infrastructure and extend its functionality. Specifically, this can allow us to set up OpenShift to process a PersistentVolumeClaim and then allocate that storage dynamically.

I am going to cover what is needed to get started with dynamically provisioning storage, including cloud provider configuration, StorageClasses, and the Default StorageClass.

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Intro to Machine Learning using Tensorflow – Part 1

Intro to Machine Learning using Tensorflow - Part 1

Tensorflow is an open-source software library created by Google for Machine Intelligence. And Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text with others. Throughout this series, we’ll be using these two applications primarily, but we’ll also venture into other popular frameworks as well. By the end of this post, you’ll be able to run a linear regression (the “hello world” of ML) inside a container you built running in a cloud.

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Not Ready for Microservices? Evolutions and Alternatives

Not Ready for Microservices? Evolutions and Alternatives

Why did the chicken cross the road? As the old saying goes, to get the other side. Why did the company move to microservices? That answer isn’t nearly as simple. While the buzz around microservices continues to grow, it can be valuable to look at various paths that companies take to achieve their ultimate goals […]

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OpenShift for Developers: Set Up a Full Cluster in Under 30 Minutes

OpenShift for Developers: Set Up a Full Cluster in Under 30 Minutes

After you play around with OpenShift locally, you will come to the realization that you would enjoy having a 24/7 install of OpenShift that you can publicly host your projects on. This is where a lot of Developers stumble because they aren’t system administrators. For that reason, I took some time to create a video that shows how to install OpenShift Origin 1.4 from start to finish. This means that I create a bare virtual machine, install the operating system, install dependencies (like docker), and then use ansible to install OpenShift. After the install, I then show how to setup wildcard DNS for a public hostname. All in under 30 minutes.

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