When Software Attacks!

Using PagerDuty Orchestration with Azure Alerts

Configuring Azure alert action groups with the PagerDuty v2 api

Configuring diagnostic settings for Azure services using bicep

If you’re hosting your application infrastructure in Azure and consolidate the diagnostic and audit information from your services into Log Analytics or elsewhere, it’s pretty easy to do using Bicep. It’s not very well documented, however, which is the reason for this post.

Deploying an Azure Container App Environment within a virtual network using bicep

When working on a project recently I needed to deploy a Container App Environment within a virtual network in Azure. Thanks to the joys of internet search, I started off reading the wrong bits of the official documention and got incredibly confused, and much of the community content about this uses out of date schemas and code. This article is so I don’t need to go through that again, and hopefully it will help others, too.

Using bicep to define Service Bus scaling rules for Azure Container Apps

I recently needed to set KEDA scaling rules on an Azure Container app that used the number of messages in a Service Bus queue. There’s plenty of info out there on the internet about scaling rules, but not when it comes to Service Bus, so I’m writing up what I learned here.

Importing bicep lint output as test results in Azure DevOps pipelines

Bicep is a great improvement over ARM Templates but doesn’t remove the need to validate our code at build time. I could continue to use the ARM-TTK and validate the generated template, but bicep has it’s own built in rules. Getting build errors in a way that can provide meaningful information in my CI/CD tooling is an interesting challenge.

Define Once, Deploy Everywhere (Sort of...)

Using Lability, DSC and ARM to define and deploy multi-VM environments Configuration as code crops up a lot in conversation these days. We are searching for that DevOps Nirvana of a single definition of our environment that we can deploy anywhere. The solution adopted at Black Marble by myself and my colleagues is not quite that, but it comes close enough to satisfy our needs. This document details the technologies and techniques we adopted to achieve our goal, which sounds simple, right?

Creating Website Slots and SQL Elastic Pools using Azure Resource Templates

Recently I have been helping a number of organisations automate the deployment of their applications to Azure and came across a couple of scenarios that were not documented: Deploying an App Services web site with slots and SQL connection string settings, and the creation of a SQL Elastic Pool. Of those, the SQL Elastic Pool I found to be written up already by Vincent-Philipe Lauzon and all credit to him - my template draws on his excellent article.

My Resource Templates from demos are now on GitHub

I’ve had a number of people ask me if I can share the templates I use in my Resource Template sessions at conferences. It’s taken me a while to find the time, but I have created a repo on GitHub and there is a new Visual Studio solution and deployment project with my code. One very nice feature that this has enabled me to provide is the same ‘Deploy to Azure’ button as you’ll find in the Azure Quickstart Templates.

Convert new VM’s dynamic IP address to static with Azure Resource Templates

Over the past few posts on this blog I’ve been documenting the templates I have been working on for Black Marble. In a previous sequence I showed how you can use nested deployments to keep your templates simple and still push out complex environments. The problem with those examples is that they are very fixed in what they do. The templates create a number of virtual machines on a virtual network, with static IP addresses for each machine.

Optimising IaaS deployments in Azure Resource Templates

Unlike most of my recent posts this one won’t have code in it. Instead I want to talk about concepts and how you should look long and hard at your templates to optimise deployment. In my previous articles I’ve talked about how nested deployments can help apply sensible structure to your deployments. I’ve also talked about things I’ve learned around what will successfully deploy and what will give errors. Nested deployments are still key, but the continuous cycle of improvements in Azure means I can change my information somewhat around what works well and what is likely to fail.