If you’re moving (or have moved) to the cloud, you probably already know what Microsoft Azure is. This cloud platform offers a range of integrated cloud services for computing, analysis, data storage, mobile networks and databases. The Azure platform combines Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Sofware as a Service (SaaS). Want to know more about the latest Microsoft Azure developments? Our bloggers keep you informed.
In the previous blog post in our ‘6 steps to the cloud’ series, we discussed ARM templates and Kubernetes manifests. In this post, we’ll use templates to roll out the Kubernetes infrastructure and our applications in Azure.
Which templates do you use to roll out apps and infrastructure using code? We recommend templates which contain a desired state and which you can roll out idempotently (this means you can execute the template multiple times without impacting the current state). Think of ARM templates and Kubernetes manifests, for example.
Do you want to offer your end users reliable containers? A container orchestrator is just what you need. The most common one is Google’s open-source container orchestrator, Kubernetes. Since almost all public clouds work with it, it’s often considered the standard solution. Microsoft offers Kubernetes as a service through Azure Kubernetes Service (AKS).
Do you want to migrate your on-premises company workloads to the Azure cloud? In this blog, we’ll discuss how to use Azure Site Recovery to migrate your on-premises machines to Microsoft Azure.
In the previous blog post, we explained how to package an application in a container. To illustrate this, we used a simple web application that recognises images, which we executed on a PC and an Azure Container Instance (ACI). In this post, we’ll delve deeper into how to build and package the application.
Artificial intelligence (AI) is everywhere these days. It’s nothing short of a media hype: we read, write and talk about it – and we expect a lot from it. In this blog post, we’ll give you the basics of how you can roll out and implement an AI model.
How do you extend your on-premises datacenter to the public cloud in a secure way? It’s simple: by implementing an Azure Virtual Datacenter. How do you get started with this project? Step by step.