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【Introduction to Azure】Firm and Think IaC Strategy for Azure - PrismScaler

1. Introduction

Hello! We are a writer team from Definer Inc. Infrastructure as Code (IaC) is a methodology that allows developers and operations teams to manage and provision cloud infrastructure using code and configuration files. Instead of manually setting up resources, IaC enables automation and consistency, making it easier to deploy, update, and scale infrastructure across cloud environments. In the context of Azure, IaC provides a systematic approach to manage Azure resources, reduce manual errors, and improve collaboration between development and operations teams. In this issue, you are wondering about the use of Azure's Infrastructure as Code (IaC) strategy. Let's take a look at the actual screens and resources to explain in detail.

2. Purpose/Use Cases

The purpose of adopting a firm and thoughtful IaC strategy for Azure is to streamline the process of managing cloud infrastructure, increase efficiency, and promote best practices in resource management. By using IaC tools and methodologies, organizations can achieve the following objectives:
  1. Consistency and Reproducibility
  2. Version Control and Collaboration
  3. Automated Deployment and Scaling
  4. Resource Dependency Management
  5. Security and Compliance
  6. Infrastructure Monitoring and Logging
  7. Cost Optimization
  8. Infrastructure Testing

3. Azure's IaC options

In a firm and thoughtful IaC strategy for Azure, it is essential to consider best practices and choose the right IaC tool based on the specific needs of the project. Let's explore the key aspects of each IaC tool, Azure Resource Manager (ARM) templates, and Terraform: (1) Azure Resource Manager (ARM) Template: ARM templates are written in JSON format and are specific to the Azure ecosystem. They allow you to define the desired state of Azure resources and their configurations, making it easier to automate the deployment and management of infrastructure. The advantage of ARM templates is that they are officially supported by Azure, and there is extensive documentation and community knowledge available for troubleshooting and learning. ARM templates are well-integrated with Azure services, providing seamless resource deployment and management within the Azure portal. However, the JSON format of ARM templates can be complex and less readable, especially for large and complex infrastructures. Additionally, managing large ARM templates can become challenging, and version control may require careful consideration. (2) Terraform: Terraform is an open-source IaC tool developed by HashiCorp, and it uses a proprietary language called HashiCorp Configuration Language (HCL). One of the main advantages of Terraform is its support for multi-cloud environments, including AWS and GCP, in addition to Azure. This allows for a consistent approach to managing infrastructure across different cloud providers. Terraform offers a more human-readable configuration language compared to JSON, making it easier to understand and maintain infrastructure code. The declarative nature of Terraform allows users to define the desired state of resources, and Terraform handles the provisioning and configuration changes required to reach that state. Terraform supports state management, which helps in tracking the current state of deployed resources and managing changes safely. One potential disadvantage is that Terraform is not officially provided by Azure, so it may not always be as closely aligned with new Azure features and services immediately upon their release. Managing authentication and secrets in Terraform can be more complex, and proper care must be taken to secure sensitive information.

4. ARM template vs Terraform actual code comparison

We will now compare what actually happens when the same resource is described in the ARM template and Terraform. Let's create a Vnet with the ARM template and Terraform.   Let's look at the ARM template first. In which: $schema: This specifies the URL of the JSON schema that defines the structure and allowed properties for the ARM template. The URL points to the Azure API version that the template follows, in this case, "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#". contentVersion: This field represents the version of the template itself. It is used to track changes and ensure compatibility when making updates to the template in the future. parameters: This section is used to define input parameters for the template. Parameters allow users to provide values at deployment time, making the template more flexible and reusable across different scenarios. In the provided template, no parameters are defined. resources: This section is the core of the template, where the Azure resources to be deployed are specified. In this example, there is one resource defined:     type: Specifies the resource type, "Microsoft.Network/virtualNetworks," which indicates the deployment of a virtual network.     apiVersion: Specifies the version of the Azure API to use for this resource. In this case, it is "2021-05-01".     name: This is the name of the virtual network resource to be created, set as "test-vnet".     location: Specifies the Azure region where the virtual network will be deployed. In this example, "japaneast" is the location.     properties: This section contains specific properties for the virtual network. In this case, it defines the address space for the VNet.         addressSpace: This property represents the IP address space that the virtual network will use. It is specified as an array of address prefixes, and in this example, there is one address prefix "172.16.0.0/16", which means the VNet will have IP addresses in the range of 172.16.0.0 to 172.16.255.255.
{
  "$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
  "contentVersion": "1.0.0.0",
  "parameters": {},
  "resources": [
    {
      "type": "Microsoft.Network/virtualNetworks",
      "apiVersion": "2021-05-01",
      "name": "test-vnet",
      "location": "japaneast",
      "properties": {
        "addressSpace": {
          "addressPrefixes": [
            "172.16.0.0/16"
          ]
        }
      }
    }
  ]
}                
 

Next is Terraform.

This one has a little more visibility.
provider "azurerm" {
  features {}
}

resource "azurerm_virtual_network" "example" {
  name                = "test-vnet"
  location            = ”japaneast”
  resource_group_name = "${Resource Group Name}"
  address_space       = ["172.16.0.0/16"]
}                  

5. Cited/Referenced Articles

6. About the proprietary solution "PrismScaler"

・PrismScaler is a web service that enables the construction of multi-cloud infrastructures such as AWS, Azure, and GCP in just three steps, without requiring development and operation. ・PrismScaler is a web service that enables multi-cloud infrastructure construction such as AWS, Azure, GCP, etc. in just 3 steps without development and operation. ・The solution is designed for a wide range of usage scenarios such as cloud infrastructure construction/cloud migration, cloud maintenance and operation, and cost optimization, and can easily realize more than several hundred high-quality general-purpose cloud infrastructures by appropriately combining IaaS and PaaS.  

7. Contact us

This article provides useful introductory information free of charge. For consultation and inquiries, please contact "Definer Inc".

8. Regarding Definer

・Definer Inc. provides one-stop solutions from upstream to downstream of IT. ・We are committed to providing integrated support for advanced IT technologies such as AI and cloud IT infrastructure, from consulting to requirement definition/design development/implementation, and maintenance and operation. ・We are committed to providing integrated support for advanced IT technologies such as AI and cloud IT infrastructure, from consulting to requirement definition, design development, implementation, maintenance, and operation. ・PrismScaler is a high-quality, rapid, "auto-configuration," "auto-monitoring," "problem detection," and "configuration visualization" for multi-cloud/IT infrastructure such as AWS, Azure, and GCP.