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Have you ever had an application that you wanted to automate the building, packing, and deployment for? In this article, I will show you how to can utilize Docker, Github Actions, and Azure App Services in just a few steps.

So you have a Kubernetes-cluster and a bunch of applications. You trigger deploys by manually pushing templated yaml to your cluster. The codebase is large and the manual processes time-consuming and error-prone. You need a better way. Well, let me help you with an opinionated suggestion.

A special year is coming to its end, we look back at the pandemic dominating most of the news (fake or not). Despite the fact that he apparently is immune, it is still a special year for Santa Claus. This year he began his journey towards the cloud for his on-north-pole infrastructure.

This blog post will not focus on how or even why you should write your infrastructure as code. Rather, it will focus on how you, a curious developer working with Azure Resource Manager (ARM), can modularize your infrastructure code and share it with others through linked ARM templates. I will also show you the basic parts of a self-made "repository" of templates which makes using shared templates a breeze.

The container paradigm is upon us, and some love hacking and writing code for Kubernetes - while others struggle, finding maintaining or releasing for it difficult. How do you even test a Kubernetes deployment on your own computer anyway? In this post we will have a look at how the stripped-down Kubernetes variant K3s can be used to take the new hot container continuous delivery tool Argo CD for a spin on your own laptop or personal server - without much of the complexity Kubernetes requires.

I first heard about using Kubernetes for Internet of Things (IoT) and edge computing less than a year ago. I was pretty new to Kubernetes, and didn't know a lot about IoT. So it seemed like a big pile of buzzwords. And even if it seems like a lot of buzzwords to you, you should still consider Kubernetes when deciding how to manage your IoT and edge applications. In this article I will discuss some of the features and frameworks that are especially important when running Kubernetes on the edge.

Kubernetes has become the de facto container orchestrator since it's initial release in 2014. It is a great tool for managing diverse workloads in clusters of machines, possibly spanning multiple availability zones. As the usage grows, new requirements for how to deploy and operate specialized software emerges. The Operator pattern is one of the more prominent responses to these new requirements.

You've got a Kubernetes cluster running your application on Google Cloud Platform (GCP), managed by Terraform. Metrics from your cluster, from your app or any other instance in our cluster - what to do with them? Sure, you've got Metrics Explorer in GCP that lets you play around with the metrics. Another option is to create a monitoring dashboard by manually selecting the metrics, aggregations, alignments, etc. to be shown. However, this can also be managed with Terraform, allowing a lot more control over your monitoring.

Most organizations eventually encounter the need to automate and schedule repetative tasks. A common approach to this is using shell scripts and cron jobs. This article is a quick introduction to an alternative way of doing this: By writing python code and using Cloud Composer.

Uffizzi (https://uffizzi.com) is a new cloud platform that helps developers deploy and host applications with zero cloud infrastructure knowledge. Uffizzi is similar to Heroku in many ways, but it is built on top of GKE, which means that it has a very solid and scalable foundation. This blog post is a quick guide to deploying applications to Uffizzi.

Azure has been growing rapidly in the enterprise in recent years. But its app services offering, which is the most important service for developers, is still mediocre. Kubernetes is, in my opinion, the only viable alternative for running applications in Azure. This blogpost explains how I came to that conclusion after roughly 6 years of working with Azure.

Cloud environments quickly grow in size. There’s tons of services and we start utilizing SaaS solutions for different problems. Solving problems through infrastructure and SaaS is after all one of the main reasons we're in the cloud in the first place.

If you're anything like me, you run all your code in managed services. But believe it or not, you might come across a problem that you can't solve with fully managed cloud services, and that's why Kelsey Hightower made Kubernetes... right?

I juli falt en dom i den europeiske domstolen som vil få store konsekvenser for bruken av skytjenester i Europa. Max Schrems vant frem i sitt søksmål mot Facebook, hvor han mente at overføring av hans personopplysninger til USA var ulovlig. Denne avgjørelsen endrer ikke bare hvordan Facebook opererer, men kan potensielt forby bruk av de amerikanske skyleverandørene, samt leverandører i andre land som ikke har godt nok personvern.