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Terraform vs Cloudformation

Terraform-vs-Cloudformation

Difference between Terraform vs Cloudformation

Infrastructure as a Code software developed by HashiCorp in July 2014 where users can deploy HashiCorp configuration language or JSON to employ datacenter infrastructure is called Terraform. Users can give version numbers to the infrastructure and build or modify the infrastructure using Terraform where low-level and high-level components are involved for this purpose. A service provided by AWS where users can build any third-party resource groups and make a collection of all the applications is called CloudFormation. A template is provided by AWS where we can update or create resources of CloudFormation by updating or creating the stacks.

Head to Head Comparison Terraform vs Cloudformation (Infographics)

Below are the top differences between Terraform vs Cloudformation:

Terraform-vs-Cloudformation-info

Key Differences

  • Built-in functions and string interpolations are present in Terraform making it more available with conditional statements. The conditional loops present to make the application design the infrastructure based on the service providers making it visually appealing while in the execution phase. The functions help in customizing the application based on customers’ needs and can add any number of providers as support to the application. The built-in functions and strings are less in CloudFormation that it always must depend on AWS to build any feature or to get support from other cloud providers.
  • We can use the information for Terraform either inside the configuration setup or we can import from outside. This makes the data to be flexible in any form in Terraform for updating and provisioning the infrastructure with new or existing IP addresses. The data sources from where the information is fetched is taken from the provider and the criteria for the source setup should be satisfied. Regarding CloudFormation, there are parameters in the application which is unique and the datatype is migrated into CloudFormation that is being supported. Parameters must be defined in the stack initially which helps in managing the datatypes. Users can do the custom configuration for the required data types by adding dynamic content to the parameters in the stack.
  • The state file of Terraform must be saved and stored in a separate entity and care should be on the file that it should not be corrupted in any form. It is very important for Terraform to work with this file. Users should take care of the state file and when updates happen the file will be replaced with a newer file. But in CloudFormation, AWS will take care of the state file where the updates will be done automatically.
  • Creating the state file and folder is the difficult part in Terraform configuration as it is the most important file in Terraform working. We can store it in the source control system but then it will not be easy to make changes to the files easily. Here, we can use AWS to manage the state files and folder for Terraform.
  • Terraform codes can be reused for different projects after storing them in Git repository or Terraform folders. This helps users to write and reuse codes when the project works in a similar fashion. This is not possible in CloudFormation as the codes for individual projects are stored in Stacks that cannot be reused for any other projects. Users should write the codes and use it for individual projects.

It depends on the flexibility of the user to use any of these cloud applications. If the user is already into AWS and is entitled to use the same, CloudFormation is the answer but if he/she has the flexibility to use any application with third-party support, Terraform is the better idea.

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Comparison Table

Now let’s see the comparison between Terraform and Cloudformation as follows:

Terraform CloudFormation
Modules are provided to users where resources can be stored in containers and can be used. These modules are shareable among team members so that the speed of the deployment and infrastructure development can be increased while using the same module. Reusable code can be saved in modules. Stacks are provided by CloudFormation which can easily produce templates in a reusable format. Nested stacks and StackSets can be used in CloudFormation so that templates can be created from templates themselves. StackSets are more secure and hence more permissions are required for the same.
Terraform is more flexible that we can use in any cloud provider’s platform and any operating system without any modification. This flexibility makes Terraform popular in many cases. In one system, we can use Terraform in different cloud platforms.

 

 CloudFormation is not flexible as Terraform that we cannot use CloudFormation in any Cloud platforms as such. Though custom resources and applications are available making it possible to use in other cloud platforms, CloudFormation works well with AWS and its related technical components.
HashiCorp Configuration language is used along with JSON as it is compatible with Terraform which makes users understand and interpret machine level and human languages easily in the resource groups. JSON or YAML language is used in CloudFormation making users be more comfortable with YAML in interpretation. If the data size is huge, it is better to use multiple resources in the StackSets of the application.
Terraform has an execution plan where users can execute Terraform plans in which resources will be either created or modified by themselves. This plan can be visually seen through the graph and the user can make necessary changes before it turns into execution. This planning and execution phase helps users to decide about Terraform infrastructure. There is no execution and planning phase for CloudFormation in AWS and hence if there are any changes to be executed during execution, it must be decided in the beginning so that the infrastructure will reflect the changes. We cannot visualize the execution mode and change the infrastructure.
Multiple providers are available for Terraform so that different clusters can be managed at a time. If one cluster is not available, it can manage with other clusters or any third-party providers. Supporting services are available and a single syntax is used in all the supporting services to make it appear unique. AWS is the only provider available for CloudFormation so that only the AWS cluster helps CloudFormation in setting up the infrastructure. If this cluster is not available, users should wait till it becomes available and other providers cannot be used here.

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