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  1. Stackups
  2. DevOps
  3. Build Automation
  4. Infrastructure Build Tools
  5. AWS CloudFormation vs Terraform

AWS CloudFormation vs Terraform

OverviewDecisionsComparisonAlternatives

Overview

AWS CloudFormation
AWS CloudFormation
Stacks1.6K
Followers1.3K
Votes88
Terraform
Terraform
Stacks22.9K
Followers14.7K
Votes344
GitHub Stars47.0K
Forks10.1K

AWS CloudFormation vs Terraform: What are the differences?

Introduction: In this article, we will compare AWS CloudFormation and Terraform, two widely used infrastructure as code (IaC) tools. Both tools enable users to define and provision infrastructure resources in a declarative manner, but there are key differences between them that set them apart.

  1. Language and Syntax: AWS CloudFormation uses JSON or YAML templates to define infrastructure resources and their dependencies. On the other hand, Terraform uses its own domain-specific language (HCL) to define infrastructure as code. While both are human-readable, HCL provides a more concise and expressive syntax compared to JSON or YAML.

  2. Provider Support: AWS CloudFormation is an AWS-native tool and exclusively supports resources provided by AWS services. In contrast, Terraform is cloud-agnostic and supports a wide range of cloud providers such as AWS, Azure, Google Cloud Platform, and many others. This makes Terraform a more flexible choice when working with a multi-cloud or hybrid cloud environment.

  3. State Management: AWS CloudFormation manages the state of resources provisioned by storing it within the AWS service itself. This simplifies state management for users as there is no need to handle the state externally. On the other hand, Terraform uses a separate backend such as a database or a file system to store its state. This allows for more control and flexibility over state management but requires additional configuration and handling.

  4. Resource Lifecycle Management: AWS CloudFormation provides built-in functionality for managing the lifecycle of resources, including creating, updating, and deleting resources. Terraform, on the other hand, requires users to explicitly define resource lifecycles using its own syntax. While this provides more fine-grained control over resource management, it also adds complexity to the configuration.

  5. Community and Ecosystem: AWS CloudFormation has a large community and an extensive ecosystem of pre-built templates and resources available for use. This makes it easy to find and leverage existing templates and configurations. Terraform also has a growing community and ecosystem, but it may not have the same breadth and depth as AWS CloudFormation in terms of ready-to-use resources.

  6. Integration with External Tools: Due to its cloud-agnostic nature, Terraform can integrate with various external tools and providers, enabling it to be part of a larger toolchain or workflow. This flexibility allows users to integrate Terraform with Continuous Integration/Continuous Deployment (CI/CD) pipelines, configuration management tools, and other infrastructure automation tools. AWS CloudFormation, being AWS-native, is tightly integrated with other AWS services, making it easier to use within the AWS ecosystem.

In Summary, AWS CloudFormation and Terraform are both powerful infrastructure as code tools, but they have distinct differences. AWS CloudFormation is tightly integrated with AWS services and simplifies state management, while Terraform offers a more flexible and cloud-agnostic approach with support for multiple cloud providers and a greater degree of control. Your choice between the two will depend on your specific requirements and the cloud environment you are working with.

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Advice on AWS CloudFormation, Terraform

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

AWS CloudFormation
AWS CloudFormation
Terraform
Terraform

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.

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.

AWS CloudFormation comes with the following ready-to-run sample templates: WordPress (blog),Tracks (project tracking), Gollum (wiki used by GitHub), Drupal (content management), Joomla (content management), Insoshi (social apps), Redmine (project mgmt);No Need to Reinvent the Wheel – A template can be used repeatedly to create identical copies of the same stack (or to use as a foundation to start a new stack);Transparent and Open – Templates are simple JSON formatted text files that can be placed under your normal source control mechanisms, stored in private or public locations such as Amazon S3 and exchanged via email.;Declarative and Flexible – To create the infrastructure you want, you enumerate what AWS resources, configuration values and interconnections you need in a template and then let AWS CloudFormation do the rest with a few simple clicks in the AWS Management Console, via the command line tools or by calling the APIs.
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
Statistics
GitHub Stars
-
GitHub Stars
47.0K
GitHub Forks
-
GitHub Forks
10.1K
Stacks
1.6K
Stacks
22.9K
Followers
1.3K
Followers
14.7K
Votes
88
Votes
344
Pros & Cons
Pros
  • 43
    Automates infrastructure deployments
  • 21
    Declarative infrastructure and deployment
  • 13
    No more clicking around
  • 3
    Atomic
  • 3
    Any Operative System you want
Cons
  • 4
    Brittle
  • 2
    No RBAC and policies in templates
Pros
  • 121
    Infrastructure as code
  • 73
    Declarative syntax
  • 45
    Planning
  • 28
    Simple
  • 24
    Parallelism
Cons
  • 1
    Doesn't have full support to GKE
Integrations
No integrations available
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

What are some alternatives to AWS CloudFormation, Terraform?

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.

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.

Pulumi

Pulumi

Pulumi is a cloud development platform that makes creating cloud programs easy and productive. Skip the YAML and just write code. Pulumi is multi-language, multi-cloud and fully extensible in both its engine and ecosystem of packages.

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