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  1. Stackups
  2. DevOps
  3. Continuous Deployment
  4. Server Configuration And Automation
  5. Azure Resource Manager vs Terraform

Azure Resource Manager vs Terraform

OverviewDecisionsComparisonAlternatives

Overview

Terraform
Terraform
Stacks22.9K
Followers14.7K
Votes344
GitHub Stars47.0K
Forks10.1K
Azure Resource Manager
Azure Resource Manager
Stacks40
Followers93
Votes11
GitHub Stars64
Forks47

Azure Resource Manager vs Terraform: What are the differences?

Introduction

In this article, we will discuss the key differences between Azure Resource Manager (ARM) and Terraform. Both ARM and Terraform are widely used Infrastructure as Code (IaC) tools that enable the provisioning and management of cloud resources. However, there are several distinct differences between the two.

  1. Management Framework: Azure Resource Manager is a native management framework provided by Microsoft Azure for deploying resources and managing infrastructure. It is tightly integrated with Azure services and provides a unified API and control plane for resource provisioning and orchestration. On the other hand, Terraform is a multi-cloud infrastructure provisioning tool that is independent of any specific cloud provider. It uses a declarative language to define infrastructure configurations and can deploy resources across different cloud platforms, including Azure.

  2. Declarative vs. Imperative: Azure Resource Manager uses a declarative approach, where you define the desired state of the infrastructure and let the platform handle the implementation details. You specify the desired configuration in ARM templates, which are JSON files describing the resources and their properties. Terraform, on the other hand, takes an imperative approach. You define the sequence of steps required to reach the desired state, and Terraform handles the execution. It uses a declarative language called HashiCorp Configuration Language (HCL) to define infrastructure configurations.

  3. Community and Ecosystem: Azure Resource Manager has a rich ecosystem and a vast collection of pre-built templates and artifacts available in the Azure Marketplace. It also integrates well with other Azure services and tools. Terraform, on the other hand, has an active and growing community with contributions from various cloud providers and users. It has a wide range of community-maintained providers and modules that extend its capabilities beyond just Azure, enabling users to provision and manage resources across different cloud platforms.

  4. Versioning and State Management: Azure Resource Manager provides built-in version control for templates, allowing you to track and manage changes over time. It also integrates with Azure DevOps for continuous integration and delivery (CI/CD) pipelines. Terraform, on the other hand, uses its own state management system to keep track of the deployed resources and their dependencies. This state is stored locally by default, but it can also be stored remotely in a backend system, enabling collaboration and sharing of the infrastructure state across a team.

  5. Resource Granularity and Customization: Azure Resource Manager allows you to manage resources at a high level of abstraction, such as virtual networks, storage accounts, or virtual machines. It provides a wide range of built-in resource types and properties that can be customized using ARM templates. Terraform, on the other hand, provides more granular control over resources. It supports a broad spectrum of resource types and allows you to define and manage resources with fine-grained configuration options.

  6. Vendor Lock-In and Multi-Cloud Support: While Azure Resource Manager is tightly integrated with Azure and provides a seamless experience for managing Azure resources, it may introduce vendor lock-in if you want to switch to a different cloud provider. Terraform, being a multi-cloud tool, offers greater flexibility and portability. It allows you to provision and manage resources across different cloud providers, reducing the risk of vendor lock-in and enabling multi-cloud and hybrid cloud deployments.

In summary, Azure Resource Manager is a native management framework tightly integrated with Azure, providing a unified API for managing Azure resources using declarative ARM templates. Terraform, on the other hand, is an infrastructure provisioning tool that is cloud-agnostic and supports multiple cloud providers using a declarative language called HCL. Terraform offers more granular control, a vibrant community, and multi-cloud support, making it a popular choice for managing infrastructure-as-code across various cloud platforms.

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Advice on Terraform, Azure Resource Manager

Sung Won
Sung Won

Nov 4, 2019

DecidedonGoogle Cloud IoT CoreGoogle Cloud IoT CoreTerraformTerraformPythonPython

Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.

Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!

Check Out My Architecture: CLICK ME

Check out the GitHub repo attached

2.25M views2.25M
Comments
Timothy
Timothy

SRE

Mar 20, 2020

Decided

I personally am not a huge fan of vendor lock in for multiple reasons:

  • I've seen cost saving moves to the cloud end up costing a fortune and trapping companies due to over utilization of cloud specific features.
  • I've seen S3 failures nearly take down half the internet.
  • I've seen companies get stuck in the cloud because they aren't built cloud agnostic.

I choose to use terraform for my cloud provisioning for these reasons:

  • It's cloud agnostic so I can use it no matter where I am.
  • It isn't difficult to use and uses a relatively easy to read language.
  • It tests infrastructure before running it, and enables me to see and keep changes up to date.
  • It runs from the same CLI I do most of my CM work from.
385k views385k
Comments
Daniel
Daniel

May 4, 2020

Decided

Because Pulumi uses real programming languages, you can actually write abstractions for your infrastructure code, which is incredibly empowering. You still 'describe' your desired state, but by having a programming language at your fingers, you can factor out patterns, and package it up for easier consumption.

426k views426k
Comments

Detailed Comparison

Terraform
Terraform
Azure Resource Manager
Azure Resource Manager

With Terraform, you describe your complete infrastructure as code, even as it spans multiple service providers. Your servers may come from AWS, your DNS may come from CloudFlare, and your database may come from Heroku. Terraform will build all these resources across all these providers in parallel.

It is the deployment and management service for Azure. It provides a management layer that enables you to create, update, and delete resources in your Azure subscription. You use management features, like access control, locks, and tags, to secure and organize your resources after deployment.

Infrastructure as Code: Infrastructure is described using a high-level configuration syntax. This allows a blueprint of your datacenter to be versioned and treated as you would any other code. Additionally, infrastructure can be shared and re-used.;Execution Plans: Terraform has a "planning" step where it generates an execution plan. The execution plan shows what Terraform will do when you call apply. This lets you avoid any surprises when Terraform manipulates infrastructure.;Resource Graph: Terraform builds a graph of all your resources, and parallelizes the creation and modification of any non-dependent resources. Because of this, Terraform builds infrastructure as efficiently as possible, and operators get insight into dependencies in their infrastructure.;Change Automation: Complex changesets can be applied to your infrastructure with minimal human interaction. With the previously mentioned execution plan and resource graph, you know exactly what Terraform will change and in what order, avoiding many possible human errors
Deploy app resources; Organize resources; Control access to resources
Statistics
GitHub Stars
47.0K
GitHub Stars
64
GitHub Forks
10.1K
GitHub Forks
47
Stacks
22.9K
Stacks
40
Followers
14.7K
Followers
93
Votes
344
Votes
11
Pros & Cons
Pros
  • 121
    Infrastructure as code
  • 73
    Declarative syntax
  • 45
    Planning
  • 28
    Simple
  • 24
    Parallelism
Cons
  • 1
    Doesn't have full support to GKE
Pros
  • 4
    Bicep - Simple Declarative Language
  • 2
    RBAC and Policies in templates
  • 1
    Day 1 resource support
  • 1
    Infrastructure-as-Code
  • 1
    Versioned deployment via Blueprints
Integrations
Heroku
Heroku
Amazon EC2
Amazon EC2
CloudFlare
CloudFlare
DNSimple
DNSimple
Microsoft Azure
Microsoft Azure
Consul
Consul
Equinix Metal
Equinix Metal
DigitalOcean
DigitalOcean
OpenStack
OpenStack
Google Compute Engine
Google Compute Engine
Kubernetes
Kubernetes
Docker
Docker
Ruby
Ruby
rkt
rkt

What are some alternatives to Terraform, Azure Resource Manager?

Ansible

Ansible

Ansible is an IT automation tool. It can configure systems, deploy software, and orchestrate more advanced IT tasks such as continuous deployments or zero downtime rolling updates. Ansible’s goals are foremost those of simplicity and maximum ease of use.

Chef

Chef

Chef enables you to manage and scale cloud infrastructure with no downtime or interruptions. Freely move applications and configurations from one cloud to another. Chef is integrated with all major cloud providers including Amazon EC2, VMWare, IBM Smartcloud, Rackspace, OpenStack, Windows Azure, HP Cloud, Google Compute Engine, Joyent Cloud and others.

Capistrano

Capistrano

Capistrano is a remote server automation tool. It supports the scripting and execution of arbitrary tasks, and includes a set of sane-default deployment workflows.

Puppet Labs

Puppet Labs

Puppet is an automated administrative engine for your Linux, Unix, and Windows systems and performs administrative tasks (such as adding users, installing packages, and updating server configurations) based on a centralized specification.

Salt

Salt

Salt is a new approach to infrastructure management. Easy enough to get running in minutes, scalable enough to manage tens of thousands of servers, and fast enough to communicate with them in seconds. Salt delivers a dynamic communication bus for infrastructures that can be used for orchestration, remote execution, configuration management and much more.

AWS CloudFormation

AWS CloudFormation

You can use AWS CloudFormation’s sample templates or create your own templates to describe the AWS resources, and any associated dependencies or runtime parameters, required to run your application. You don’t need to figure out the order in which AWS services need to be provisioned or the subtleties of how to make those dependencies work.

Fabric

Fabric

Fabric is a Python (2.5-2.7) library and command-line tool for streamlining the use of SSH for application deployment or systems administration tasks. It provides a basic suite of operations for executing local or remote shell commands (normally or via sudo) and uploading/downloading files, as well as auxiliary functionality such as prompting the running user for input, or aborting execution.

AWS OpsWorks

AWS OpsWorks

Start from templates for common technologies like Ruby, Node.JS, PHP, and Java, or build your own using Chef recipes to install software packages and perform any task that you can script. AWS OpsWorks can scale your application using automatic load-based or time-based scaling and maintain the health of your application by detecting failed instances and replacing them. You have full control of deployments and automation of each component

Packer

Packer

Packer automates the creation of any type of machine image. It embraces modern configuration management by encouraging you to use automated scripts to install and configure the software within your Packer-made images.

Scalr

Scalr

Scalr is a remote state & operations backend for Terraform with access controls, policy as code, and many quality of life features.

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