Microsoft Azure Cloud Services
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Being Owner of an Azure subscription does not let you read a single secret in a Key Vault you just created. The fix is one role assignment — and once you understand its three parts, you can grant exactly the access you mean, to a person or to an app, in about a minute.
You added API permissions to an Azure app registration, requested a token, and got back AADSTS65001 instead. The token endpoint is telling you something simple: the permissions are configured, but nobody has actually consented to them yet.
The command is az group list. Add --output table and you get a clean, readable list instead of a wall of JSON. Everything else on this page is a variation on that one command.
Getting an app deployed is the easy half. This final part covers what you actually do with a running app: read its logs, understand how it scales, know what it costs — and take it all down again.
This is the part where it becomes real. Four tabs in the Azure portal and your container gets a public HTTPS address that anyone in the world can open.
This is the shortest part of the series and the one most likely to save you an afternoon. Pushing an image is three commands — but if you're on an Apple Silicon Mac, one missing flag produces a container that builds perfectly, pushes perfectly, and then refuses to start on Azure.
Your container image is stuck on your laptop, and Azure can't reach your laptop. In this part you'll create the two Azure resources that fix that: a resource group to hold everything, and a container registry to store the image.
Your app works on your machine because your machine happens to have .NET 10 installed. A container removes that "happens to" — it packages the app and the runtime into one box that behaves identically everywhere.
Most "deploy to the cloud" tutorials skip the part where you actually understand what you built. This series does the opposite: six short parts that take you from an empty folder to a real, public URL on Azure, explaining every command along the way.
If you are about to create an Azure OpenAI resource, stop. Microsoft's own guidance is that most use cases should use a Foundry resource instead — it speaks every Azure OpenAI API you already use, and adds the rest of the model catalog, agents and tools on top. This guide creates one from scratch and deploys a model.
