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Pass variables values inside terraform modules

In this article I will explain two different ways to pass variables values inside terraform modules. Modules let you separate your code into small units and help the engineer structure its project better.

https://www.terraform.io/language/modules/syntax

Modules in terraform (terraform files) can be placed on folders and their location should be provided on the module directive. Lets say for example that you host a main.tf on your current working directory which should call two modules. The first module would be a storage account and the second would be an app service. Your main.tf file should look like below.

module "app_service_test" {
  source                  = "./modules/appservice"
}
module "storage_account_test" {
  source                  = "./modules/storageaccount"
}

However you want to pass some variables inside the child modules for example the resource group name, location etc.

First method – Define variables on root module

The first way you can pass variables inside your child modules would be to define a variables.tf file on your main module and a terraform.tfvars. Then you should also define a variables.tf file inside each module and contain the definition of each module.

terraform.tfvars (root module)

app_service_plan_name   = "ger-plan-test"
app_service_name        = "ger-site-test"
resource_group_name     = "geralexgr-terraform-rg"
resource_group_location = "West Europe"
storage_account_name    = "geralexgrsgv2"

variables.tf (root module)

variable "storage_account_name" {
  type        = string
  description = "Storage account name"
  default     = ""
}

variable "resource_group_name" {
  type        = string
  description = "RG name in Azure"
}

variable "app_service_plan_name" {
  type        = string
  description = "App Service Plan name in Azure"
}

variable "app_service_name" {
  type        = string
  description = "Name for the app service"
}

variable "resource_group_location" {
  type        = string
  description = "RG location in Azure"
}

variables.tf (storageaccount module)

variable "storage_account_name" {
    type        = string
    description = "Storage account name"
}
variable "resource_group_name" {
    type        = string
    description = "RG name in Azure"
}

variable "resource_group_location" {
    type        = string
    description = "RG location in Azure"
}

variables.tf (appservice module)

variable "app_service_plan_name" {
    type        = string
    description = "App Service Plan name in Azure"
}

variable "app_service_name" {
    type = string
    description = "Name for the app service"
}
variable "resource_group_name" {
    type        = string
    description = "RG name in Azure"
}

variable "resource_group_location" {
    type        = string
    description = "RG location in Azure"
}

Then on your main module you should call your child modules as follows:

module "app_service_test" {
  source                  = "./modules/appservice"
  app_service_plan_name   = var.app_service_plan_name
  app_service_name        = var.app_service_name
  resource_group_name     = var.resource_group_name
  resource_group_location = var.resource_group_location
}

module "storage_account_test" {
  source                  = "./modules/storageaccount"
  storage_account_name    = var.storage_account_name
  resource_group_name     = var.resource_group_name
  resource_group_location = var.resource_group_location
}

Second method – Pass variables on module call

With this approach you do not need to have variables.tf file and terraform.tfvars file inside your root module. You only need the definition as described above inside appservice and storageaccount folders (variables.tf).

variables.tf (appservice module)

variable "app_service_plan_name" {
    type        = string
    description = "App Service Plan name in Azure"
}

variable "app_service_name" {
    type = string
    description = "Name for the app service"
}
variable "resource_group_name" {
    type        = string
    description = "RG name in Azure"
}

variable "resource_group_location" {
    type        = string
    description = "RG location in Azure"
}

variables.tf (storageaccount module)

variable "storage_account_name" {
    type        = string
    description = "Storage account name"
}
variable "resource_group_name" {
    type        = string
    description = "RG name in Azure"
}
variable "resource_group_location" {
    type        = string
    description = "RG location in Azure"
}

Then your main.tf file should be:

module "app_service_test" {
  source                  = "./modules/appservice"
  app_service_plan_name   = "ger-plan-test"
  app_service_name        = "ger-site-test"
  resource_group_location = "West Europe"
  resource_group_name     = "geralexgr-terraform-rg"
}

module "storage_account_test" {
  source                  = "./modules/storageaccount"
  storage_account_name    = "geralexgrsgv2"
  resource_group_name     = "geralexgr-terraform-rg"
  resource_group_location = "West Europe"
}
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Install linux azure devops agent on docker container

As we previously examined how we can create a containerized azure devops agent running on a windows machine, we will now go through the same procedure but with linux OS.

You can read the windows container azure devops agent article using the below link:

The first thing that you will need is a virtual machine that runs docker. When this requirement is fulfilled you can jump on the image building. In order to build your image you will need your Dockerfile and the instructions for the agent.

You can read the rest of the article on Medium using the link below:

A detailed deployment video can be found on my Udemy course:

https://www.udemy.com/course/mastering-azure-devops-cicd-pipelines-with-yaml/

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Install windows azure devops agent on docker container

On previous articles I have explained how you can install an azure devops agent on the operating system in order to create your self hosted agent pools for your projects.

Windows installation example:

Mac OS X installation example:

But what if you need to create multiple agents inside a virtual machine? The best solution would be to use docker virtualization and separate those agents from each other. We will now examine how we can host our azure devops agents on containers.

The first thing that you will need is a virtual machine that runs docker. When this requirement is fulfilled you can jump on the image building. In order to build your image you will need your Dockerfile and the instructions for the agent.

You can read the rest of the article on Medium using the link below:

A detailed deployment video can be found on my Udemy course:

https://www.udemy.com/course/mastering-azure-devops-cicd-pipelines-with-yaml/

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Containerize a .NET app with Docker and vs code

When you build your application with cloud native technologies you will build microservices on containers instead of monolithic applications. We will now examine how easy is to build a .NET application in a container and run this application on your local machine.

First we will need to create the visual studio solution. I will go through that with visual studio IDE and then I will use vs code. For my microservice I am using a ASP .NET Core web api with default code.

The target framework for the solution will be the latest .NET framework which is version 7. All other settings will be set to defaults.

When you run the app locally with IIsExpress you will be able to access the swagger interface through the port which you defined in the launchSettings.json. 

https://localhost:7057/swagger/index.html

This file can be located under Properties and there you can configure on which port the application will run. In the profiles section under https settings, you can find the default application URL and port. This will be needed in later steps.

Microsoft provides the below documentation in order to create a containerized application that runs on .NET

Build and run an ASP.NET Core app in a container
In this guide you will learn how to: Create a Dockerfile file describing a simple .NET Core service container. Build…code.visualstudio.com

In order to create a microservice based on our vs solution we will need a dockerfile. This can be created automatically with vs code.

In vs code command dialog search for docker add and select docker compose files to workspace.

Then select asp net core.

and after that your operating system. The next step will be to select the exposed port, or otherwise under which port your application will run. There we should provide the port that we found under our launchSettings.json or the one that we configured manually. In my case I will select the default one for the solution which was 7057.

When a popup window appears on the screen you should select add Dockerfile and automatically the build files will be generated.

Dockerfile

Based on my setup I altered two things in the generated Dockerfile. The first thing will be to change configuration to Debug instead of Release. For production environments you will consider using the release build directive. The second thing will be to add an environmental variable ASPNETCORE_ENVIRONMENT inside the container with the value Development.

FROM mcr.microsoft.com/dotnet/aspnet:7.0 AS base
WORKDIR /app
EXPOSE 7057

ENV ASPNETCORE_URLS=http://*:7057
ENV ASPNETCORE_ENVIRONMENT=Development

FROM mcr.microsoft.com/dotnet/sdk:7.0 AS build
WORKDIR /src
COPY ["AspNetWebApi.csproj", "./"]
RUN dotnet restore "AspNetWebApi.csproj"
COPY . .
WORKDIR "/src/."
RUN dotnet build "AspNetWebApi.csproj" -c Debug -o /app/build

FROM build AS publish
RUN dotnet publish "AspNetWebApi.csproj" -c Debug -o /app/publish /p:UseAppHost=false

FROM base AS final
WORKDIR /app
COPY --from=publish /app/publish .
ENTRYPOINT ["dotnet", "AspNetWebApi.dll"]

docker build command

after the build is completed and the image is created you can run a new container locally.

Keep in mind that in order to test your container you should create a port forward from the container to your host. I used the same port for the host so I added the -p 7057:7057

The logs of the container indicate a successful run of the application.

Our application now runs as a microservice container inside the host machine (my laptop). 

We can verify the access to our application using the URL with the swagger.

Youtube video: