ASP.NET on OpenShift part 5: Models in the MVC

ASP.NET on OpenShift part 5: Models in the MVC

PART 5 – Models: As we’ve been seeing in this series so far, MVC stands for Model-View-Controller. In the first two parts, I talked about the Controller. In the last two parts, we went over Views and putting your project on OpenShift. In this fifth and final part of the MVC series, I’m going to write about Models.

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[Video Tour] Openshift Monitoring Tools with Sysdig

[Video Tour] Openshift Monitoring Tools with Sysdig

In previous blog posts we dove into the specifics of how to monitor OpenShift – so now it’s time to sit back and enjoy the show. We wanted to show you what a state-of-the art OpenShift monitoring tool looks like, using Sysdig OpenShift Monitoring as an example. In this short video, we’re going to answer a few key questions by demonstrating using this tool for monitoring of a container application platform built on OpenShift.

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Kubernetes deep dive: API Server – part 1

Kubernetes deep dive: API Server - part 1

Welcome to the Kubernetes deep dive blog post series. We, that is, Stefan Schimanski (Engineering) and Michael Hausenblas (Advocacy), will dive into specific aspects of Kubernetes and how they’re utilized within OpenShift. If you’re interested in the inner workings of Kubernetes and how to debug it, this blog post series is for you. Also, if you want to extend Kubernetes or start contributing to the project, you might benefit from it. Familiarity with Go is an advantage but not a hard requirement to follow along.

In this installment we start with a general introduction of the Kubernetes API Server, provide some terminology and explain the API request flow. Future posts will cover storage-related topics and extensibility points of the API Server.

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Jupyter on OpenShift Part 7: Adding the Image to the Catalog

Jupyter on OpenShift Part 7: Adding the Image to the Catalog

When you are deploying an application from the OpenShift web console you have the choice of deploying an image hosted on an external image registry, or an existing image which was built within the OpenShift cluster using either the Docker or Source build strategies. This is done from Deploy Image after having selected Add to project in the web console.

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Jupyter on OpenShift Part 6: Running as an Assigned User ID

Jupyter on OpenShift Part 6: Running as an Assigned User ID

When you deploy an application to OpenShift, by default it will be run with an assigned user ID unique to the project the application is running in. This user ID will override whatever user ID a Docker-formatted image may declare as the user it should be run as.

Running applications under a project as a user ID different to applications running in any other project is part of the multi-layered approach to security used in OpenShift. In this post, we will delve more into the topic of user IDs, as well as what changes would need to be made to the Jupyter Notebook image being used to enable it to run as the user ID OpenShift assigns to it.

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Managing the Lifecycle of OpenShift Clusters: Vetting OpenShift Installations

Managing the Lifecycle of OpenShift Clusters: Vetting OpenShift Installations

Whether installing a new release of a software package or just installing an update (such as a bug fix), it is wise to perform tests against the newly installed software in order to confirm that it is performing correctly in the target environment. This is especially true with OpenShift since it contains a number of open source components and can be deployed to a variety of environments, such as an on-prem datacenter, or a public or private cloud.

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Kubernetes Services By Example

Kubernetes Services By Example

When explaining Kubernetes to people new in the space I noticed that the concept of services is often not well understood. To help you better understand what services are and how you can troubleshoot them, we will have a look at a concrete setup and discuss the inner workings of services in this post.

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Enhancing your Builds on OpenShift: Chaining Builds

Enhancing your Builds on OpenShift: Chaining Builds

In addition to the typical scenario of using source code as the input to a build, OpenShift build capabilities provides another build input type called “Image source”, that will stream content from one image (source) into another (destination).

Using this, we can combine source from one or multiple source images. And we can pass one or multiple files and/or folders from a source image to a destination image. Once the destination image has been built it will be pushed into the registry (or an external registry), and will be ready to be deployed.

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Jupyter on OpenShift Part 5: Ad-hoc Package Installation

Jupyter on OpenShift Part 5: Ad-hoc Package Installation

The main reason persistent volumes are used is to store any application data. This is so that if a container running an application is restarted, that data is preserved and available to the new instance of the application.

When using an interactive coding environment such as Jupyter Notebooks, what you may want to persist can extend beyond just the notebooks and data files you are working with. Because it is an interactive environment using the dynamic scripting language Python, a user may want to install additional Python packages at the point they are creating a notebook.

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