When you deploy on Azure using terraform you may encounter the below error.
The subscription is not registered to use namespace ‘Microsoft.ContainerService’. See https://aka.ms/rps-not-found for how to register subscriptions.
In order to resolve issue you should go inside azure portal and under your subscription you should navigate into Resource Providers. Then you should search for the specific provider that is not registered (in my example in was ContainerService) and click register.
When you press register you will see that the provider is going to be in Registering state.
Finally the deployment will succeed after the above change.
If you work everywhere as a code you will probably need to check Azure DevOps terraform provider. It is created and maintained from Microsoft and you can use it in order to have your DevOps tool as a code.
In order to getting started you will need to create a PAT token and give it the access based on the actions that you need to do.
When the token is ready you will need to set two environmental variables on the machine that you work. The first one is AZDO_PERSONAL_ACCESS_TOKEN which should be your token. The second one will be your org URL AZDO_ORG_SERVICE_URL
Finally you are ready to deploy your IAC Azure DevOps configurations.
Lets see the below example.
# Make sure to set the following environment variables:
# AZDO_PERSONAL_ACCESS_TOKEN
# AZDO_ORG_SERVICE_URL
terraform {
required_providers {
azuredevops = {
source = "microsoft/azuredevops"
version = ">=0.1.0"
}
}
}
resource "azuredevops_project" "project" {
name = "My Awesome Project"
description = "All of my awesomee things"
}
resource "azuredevops_git_repository" "repository" {
project_id = azuredevops_project.project.id
name = "My Awesome Repo"
initialization {
init_type = "Clean"
}
}
resource "azuredevops_build_definition" "build_definition" {
project_id = azuredevops_project.project.id
name = "My Awesome Build Pipeline"
path = "\\"
repository {
repo_type = "TfsGit"
repo_id = azuredevops_git_repository.repository.id
branch_name = azuredevops_git_repository.repository.default_branch
yml_path = "azure-pipelines.yml"
}
}
When above code runs it will create a new project with the name My Awesome Project. Inside the project a new git repo will be initialized and a new pipeline will be created inside this repository.
A common challenge for developers is the management of secrets, credentials, certificates, and keys used to secure communication between services. Managed identities eliminate the need for developers to manage these credentials.
There are two types of managed identities:
System Assigned
User assigned
You can learn more about how managed identity works from the below guide.
On a previous article I have documented how managed identity can be used inside an azure web app.
In this demonstration we will examine how we can use managed identity to authenticate with a storage account from a .NET application. This is very useful when dealing with security as we eliminate access to specific resources and we do not have to manage passwords in the code.
In order to implement Managed Identity it should be supported for the specific resource. This example is an ASP .NET web app that is deployed on a app service and uses managed Identity to communicate with a storage account and get blob data or information.
Firstly the managed identity object should be enabled on the web app. This means that you enable the web app to request when needed managed identity authentication from Azure AD.
Then you will need to enable the specific role that is required on the identity resource. As you can see from the image, I assigned the Storage Blob Data Reader, as I only need to perform read actions (least privilege) on the dotnet-testmi identity which is identified by azure with the App Service Label. When you enable the managed identity on a resource it will connect with an object ID which is then the identified on the whole azure portal. You can search later on with this ID or the name of the resource from the IAM of the destination resource. This means that you have to assign the permissions on the Blob Container of the Storage account that you need to access through code.
Finally you you will need to use Managed Identity Authentication in your code.
In this example two libraries are needed in order to interact with the storage account using managed identity. First the Azure.identity which includes Managed Identity Authentication and also Azure.Storage library.
Authenticate using Managed Identity instead of a connection string
BlobContainerClient client = new BlobContainerClient(new Uri($"https://NAME.blob.core.windows.net/testing"), new ManagedIdentityCredential());
Authentication using connection string
BlobContainerClient client = new BlobContainerClient("connectionString","testing");
When creating a blank ASP .NET application you will have a WeatherController built by default to start experimenting. The code for this example is added there for the case of simplicity and you can find it below.
using Azure.Storage.Blobs.Models;
using Azure.Storage.Blobs;
using Azure;
using Microsoft.AspNetCore.Mvc;
using Azure.Identity;
namespace WebApplication1.Controllers
{
[ApiController]
[Route("[controller]")]
public class WeatherForecastController : ControllerBase
{
private readonly ILogger<WeatherForecastController> _logger;
private static List<string> _blobList;
public WeatherForecastController(ILogger<WeatherForecastController> logger)
{
_logger = logger;
}
[HttpGet(Name = "GetWeatherForecast")]
public IEnumerable<string> Get()
{
BlobContainerClient client = new BlobContainerClient(new Uri($"https://NAME.blob.core.windows.net/testing"), new ManagedIdentityCredential());
ListBlobsFlatListing(client, 1).GetAwaiter().GetResult();
return _blobList.ToArray();
}
private static async Task ListBlobsFlatListing(BlobContainerClient blobContainerClient,
int? segmentSize)
{
try
{
_blobList = new List<string>();
// Call the listing operation and return pages of the specified size.
var resultSegment = blobContainerClient.GetBlobsAsync()
.AsPages(default, segmentSize);
// Enumerate the blobs returned for each page.
await foreach (Page<BlobItem> blobPage in resultSegment)
{
foreach (BlobItem blobItem in blobPage.Values)
{
Console.WriteLine("Blob name: {0}", blobItem.Name);
_blobList.Add(blobItem.Name);
}
Console.WriteLine();
}
}
catch (RequestFailedException e)
{
Console.WriteLine(e.Message);
Console.ReadLine();
throw;
}
}
}
}
Microsoft Advisor can be a powerful tool for your Azure subscription because it automatically suggest you various changes in your infrastructure based on specific pillars like Cost, Security, Reliability, Performance etc. This means that you can easily eliminate costs by following some of the findings that are automatically generated.
A sample scenario is my virtual machine that I created some time ago with SKU E2as_v5. I selected the specific type because the application that I had to install inside the server was requesting such specs but this is not the case at all. As I was looking at the recommendations, I saw a note to downscale my virtual server as it seems under utilized.
Specifically it was mentioned to downscale for D2as_v5 SKU which used 8GB RAM instead of 16GB it is cheaper and it is a general purpose VM and not Memory Optimized.
In order to downscale one should go in the virtual machine and under size select the new SKU and press resize.
But how can I be sure that the performance will be adequate and the virtual machine will perform as needed? By looking at the statistics below, I noticed that the CPU was steady and the available memory was constantly at 9GB. This means that it was heavily under utilized and the application although having minimum specs of 16GB in reality that was not accurate.
By monitoring the virtual machine after the change I can conclude that it is performing well and the original SKU was not calculated correctly.
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