This post is all about simplifying our code by using for / each loops. Rather than filling .tf files with module blocks calling for data from other files, I want us to be able to leave those .tf files static, and when we want a new resource, just add the data to the .tfvars file where it’ll be picked up and applied. Again it’s about abstracting the code from the data that little bit further, whilst also reducing the number of code lines we have to write or repeat.

This post aims to cover the subject of putting YAML pipelines into templates. This means separating out repeated and re-usable code into separate files that are project or client agnostic, just as we did with our Terraform modules.

In this post I want to cover the differences between directories and workspaces (I use directories, I’ll explain why, but there are arguments for both and people’s preferences differ – choose what works for you). I’ll try and give examples of how we can create separate environments using pipeline stages, and I’ll also start adding a little more structure to our repository’s root folder.

This time we’re going to be looking at Terraform modules to try and simplify things and reduce the amount of lines in our main deployment code. It’s another long one I’m afraid, but hopefully it will really help some things gel in your mind. We will discuss what modules are and how to use them, then we’ll make all our code re-usable by moving the data into a separate variables file.

In this episode I’m going to be looking at refining our pipeline code by adding formatting checks and putting some of our more sensitive variables into and Azure DevOps library. If you’ve been with me on the whole journey you now should have a relatively good understanding of the structure of pipelines, and be able to use them to deploy resources into Azure using basic Terraform code.