If you prefer to watch videos over reading, check out this video on my YouTube channel: About a year ago I got back into skateboarding. Probably not the safest midlife crisis ever, but I can travel from my house to the gym, I can kickturn, and even manage a nose stall 1 out of 10 times. Look at this footage for an example ...
I run various Container Apps as part of my personal health project. I want this project to be as low maintenance as possible, so I decided to take a look at Azure SRE Agent to see how it could help me reduce the operational toil required to operate my side project. As I’m writing this blog post (8th January 2026), Azure SRE Agent is still in Preview. There’s no mechanism to provision SRE Agents using Bicep, or any IaC for that matter, and I’m expecting to see things break or not quite work as nicely as they should, so consider everything that I’m writing here experimental, and expect that features will change as time goes by. ...
Determining how Azure AI Foundry Agents makes decisions is important for troubleshooting and debugging purposes. However, it can get a little complicated when our agents perform complex workflows. Our agents could perform numerous executions, making it difficult to track decisions made by all or them, or some agents may invoke tools, that invoke other tools, which invoke more tools! (And so on and so forth). Tracing our agents helps us see the inputs and outputs involved in a particular agent run, as well as the order in which those agents were invoked. In this blog post, I’ll talk about how tracing agents works, how we can do some simple tracing using the Azure AI Foundry Agents playground, and how we can implement tracing in our pro-code agents using OpenTelemetry. ...
As the technology advances, Generative AI models are becoming powerful enough to operate autonomously to automate tasks. This is improvement on being able to perform simple tasks in “chat” like applications. This allows us to build AI Agents, which are applications that can use generative AI models with contextual data to automate tasks based on user input and the context that they can perceive. In this article, I’ll talk about how we can build AI Agents using Azure AI Agent service. ...
In this article, I’m going to show you how to deploy an AKS Automatic Cluster within your own custom virtual network using Bicep. An Azure Subscription A code editor - I’m using Visual Studio Code! The AZ CLI kubectl A bash shell (VS Code has an integrated terminal, Windows terminal is also pretty neat) If you don’t know what AKS Automatic is, we’ll cover that before we start. We’ll then work through the Bicep code that we need to provision a cluster with our own virtual network. ...