IaC is a de facto method that allows teams to define, provision, and manage infrastructure using code, utilizing tools such as Terraform, Pulumi, Ansible, Opentofu, and CloudFormation. IaC has replaced manual processes, such as using GUI, console, or a CLI to provision the infrastructure with configuration files. With IaC, you can deploy similar resources using the reusable code, reducing human error and enabling rapid deployment.

In this article, we will discuss different IaC tools used to deploy AWS Infrastructure-as-Code, with a focus on the following areas:

  • How does Infrastructure-as-Code work in AWS?
  • Overview of various IaC tools, such as Terraform, Pulumi, CDK, Ansible, and CloudFormation.
  • Understand different IaC services in AWS, such as AWS CloudFormation, AWS CDK, and AWS SAM, and their use cases.
  • How does Firefly Compose help in deploying the cloud infrastructure?
  • Using Firefly’s policies and frameworks to maintain a secure and governed cloud infrastructure.

What is Infrastructure-as-Code (IaC)? 

IaC automates the provisioning and de-provisioning of cloud infrastructure without any manual intervention. For example,with IaC, it's much simpler and faster to provision a new EC2 instance with the exact configurations you need by writing code rather than manually clicking through a cloud provider's interface. Choosing the right IaC tool for your use case is crucial, as each one comes with unique features and capabilities. The following section will introduce some of the most commonly used IaC tools, such as Pulumi, Terraform, CloudFormation, OpenTofu, and Ansible.

IaC Tools for AWS Infrastructure

AWS supports a variety of Infrastructure-as-Code (IaC) tools that cater to different needs and preferences. Let’s see some commonly used IaC tools for AWS:

Terraform

Terraform is a popular Infrastructure-as-Code (IaC) tool that adopts a declarative approach to managing infrastructure. It uses the HashiCorp Configuration Language (HCL), which is both human-readable and easy to learn. 

Terraform maintains a state file that records the current state of the infrastructure. This state file enables Terraform to query, build, maintain, and modify infrastructure as specified in the configuration files. Terraform also automatically handles resource dependencies, ensuring they are created in the correct order. Let’s see an example of creating an S3 bucket using Terraform:

provider "aws" { region = "ap-south-1" } resource "aws_s3_bucket" "firefly_demo" { bucket = "firefly-bucket-1"   acl    = "private" }

OpenTofu

It is an open-source version of Terraform that builds on its existing concepts and functionality. Since it is forked from Terraform version 1.5.6, OpenTofu retains all the features and capabilities that have made Terraform popular while introducing new improvements and works with existing Terraform state files, ensuring a smooth migrating for the teams who are moving to it.

OpenTofu has a similar syntax and functionality as Terraform. For example, configuration to create a S3 bucket. 

provider "aws" { region = "us-west-2" } resource "aws_s3_bucket" "firefly-demo-bucket" { bucket = "my-example-bucket" acl = "private" }

Pulumi

Pulumi is a declarative IaC tool that allows teams to use existing programming languages instead of proprietary languages. It supports TypeScript, JavaScript, Python, Go, and C#. Like Terraform, Pulumi supports multiple clouds, infrastructures, and providers.

However, Pulumi configuration files are written in common programming languages, so you can use the same testing tools for your infrastructure as you do for your application code, such as Jest for TypeScript. Additionally, existing Terraform or ARM configuration files can be converted into Pulumi files. Let’s see an example of creating an S3 bucket using Pulumi (TypeScript):

import * as aws from "@pulumi/aws"; const bucket = new aws.s3.Bucket("Firefly-bucket", { bucket: "my-Firefly-bucket", acl: "private", });

Ansible

Ansible is an automation tool that includes not only Infrastructure-as-Code (IaC) but also configuration management, application deployment, and task automation. Ansible uses a YAML file to define configurations that are easy to read.

Let’s see an example where we will create an S3 bucket using Ansible:

- name: Create S3 bucket hosts: localhost tasks: - name: Create a bucket in S3 amazon.aws.s3_bucket: name: my-example-bucket acl: private state: present

AWS native IaC Services: Overview and Use Cases

Now that we have discussed IaC tools like Ansible, Pulumi, Terraform, and OpenTofu which provide robust solutions for infrastructure management. Let’s discuss AWS native IaC services, such as AWS CloudFormation AWS Server Application, that can integrate directly with AWS to provide better support and simplify management.

AWS CloudFormation

AWS CloudFormation provides a robust way to define and provision your AWS infrastructure using templates. By describing your resources and their configurations in JSON or YAML,  you can automate infrastructure management. With CloudFormation, you can easily deploy AWS resources. Unlike tools such as Terraform and Pulumi, which are general-purpose, CloudFormation is tailored specifically for AWS, providing deep integration and native support.

For example, the following CloudFormation template provisions a single EC2 instance:

AWSTemplateFormatVersion: '2010-09-09' Resources: MyEC2Instance: Type: AWS::EC2::Instance Properties: InstanceType: t2.micro ImageId: ami-12345678

AWS Cloud Development Kit (CDK)

The AWS Cloud Development Kit (CDK) provides a higher-level abstraction for defining cloud infrastructure using familiar programming languages such as TypeScript, Python, Java, and C#. Using CDK, developers can create reusable components and deploy complex infrastructure with code that's both intuitive and maintainable. It is especially useful for automating serverless applications, providing quick replication and scaling across environments. A typical use case for CDK is quickly setting up and managing resources like S3 buckets, which are essential for a variety of applications such as web hosting and backup solutions. The CDK allows for easy replication and scaling of such resources across different environments.

For example, you can deploy S3 bucket using CDK code in Python:

from aws_cdk import core, aws_s3 as s3 class MyStack(core.Stack): def __init__(self, scope: core.Construct, id: str, **kwargs) -> None: super().__init__(scope, id, **kwargs) s3.Bucket(self, "MyBucket")

AWS Serverless Application Model (SAM)

The AWS Serverless Application Model (SAM) simplifies the development and deployment of serverless applications by providing a concise syntax for defining AWS Lambda functions, API Gateway endpoints, and other serverless resources. SAM builds on top of CloudFormation, offering an easier way to manage and deploy serverless architectures. A common use case for SAM is automating event-driven data processing, where serverless functions react to events like file uploads or database changes without the need for complex infrastructure.

For example, define a simple Lambda function using the SAM template:

AWSTemplateFormatVersion: '2010-09-09' Transform: AWS::Serverless-2016-10-31 Resources: MyFunction: Type: AWS::Serverless::Function Properties: Handler: index.handler Runtime: python3.9 CodeUri: s3://my-bucket/my-function.zip

This template automates the creation of a Lambda function, making it easier to deploy event-driven applications with minimal setup.

By now, we understand that using the right tools can significantly reduce human errors, save time, prevent drifts, and eliminate repetitive coding tasks. You might need to learn and manage various IaC tools to make the most out of them, which is impractical. One such tool that offers advanced features for managing IaC practices is Firefly. It not only helps with infrastructure management but also allows you to generate IaC code using AI for Terraform, Pulumi, and more, making it easier to create and deploy infrastructure efficiently. In the next section, we will introduce Firefly, explore its capabilities, and discuss how it integrates with IaC.

How does Firefly Compose Simplify Creating Cloud Infrastructure?

Firefly is a cloud management platform that assists DevOps, Platform Engineering, and SRE teams in effectively managing their cloud environments, such as  AWS environments, using IaC. It simplifies the complexity of cloud infrastructure, implements IaC practices, and establishes a reliable framework. 

One key component of Firefly is Compose, a tool designed to simplify the creation of cloud resources. You can use module calls specifically to work with Terraform modules, or alternatively, generate templates for other IaC tools like Pulumi using the 'Generate with Thinkerbell AI' feature, as shown in the image below. Let’s see how Firefly Compose helps you deploy your cloud infrastructure.

When you click the ‘Compose tab’, you'll see the Generate new configuration page. To generate the code, select ‘Generate with Thinkerbell AI’ with the IaC tool of your choice, such as Terraform, CloudFormation, CDK, or Pulumi. For this blog post, we will use CloudFormation to generate the template for the EC2 instance.

Firefly will create the cloudformation.yaml, and other variables.tf ,instance.tf with the EC2 resource deployment config.

You can merge these files into your Github using features like pull requests, export, and copy options to your local. We will use the ‘Pull requests’ option to easily collaborate with the team by reviewing and merging the changes to your IaC.

After creating a pull request for the Github repository, you can clone the repo to your local and deploy the AWS resource using the terminal or CI/CD workflow.

In the upcoming sections, we will discuss how to deploy AWS resources using various IaC tools provided by Firefly and showcase how Firefly integrates these tools into the IaC workflows. But first, let’s understand where Firefly fits in the IaC workflow while generating the IaC configurations.

Understanding IaC Workflow in AWS

The architecture diagram below shows the workflow for deploying AWS resources using Firefly’s Compose, Thinkerbell AI. DevOps engineers can utilize various IaC tools to build infrastructure, such as Terraform and CloudFormation, while Firefly simplifies the process by generating compliant infrastructure-as-code templates.

Let us discuss the key components of IaC workflow used in this architecture diagram:

  1. DevOps Engineer: The developer writes configurations to define the desired infrastructure using languages or templates supported by IaC tools, such as YAML or JSON.
  2. Version Control: The configurations are pushed in a version control system like Github to track changes and enable collaboration. Alternatively, you can create an empty repository and integrate it into Firefly to receive code from Firefly Compose via a pull request.
  3. Firefly Integration: Firefly generates templates and codes using Thinkerbell AI for various IaC tools like Pulumi, Terraform, and more. You can copy or export these to your local machine or merge it in your Git repository and run it locally.
  4. Execute with IaC Tool: An IaC tool, such as Terraform, Pulumi, or CDK, executes the code, deploying the cloud infrastructure. Additionally, tools like Terraform and Pulumi maintain a state file to track the current infrastructure configuration, ensuring accurate updates and preventing conflicts.
  5. Infrastructure: AWS cloud infrastructure is provisioned and managed according to the defined configurations, using Firefly, ensuring it aligns with best practices and maintains uniformity.

Deploying AWS Resources Using Different IaC Tools

Firefly allows you to use various IaC tools to deploy AWS resources. We will look at a step-by-step guide on how to use some of these tools, such as Pulumi, Terraform, and CloudFormation, to deploy cloud infrastructure.

Creating S3 bucket Using Pulumi and Firefly Compose

Let's see how to create an S3 bucket using Pulumi, integrated with Firefly Compose.

  1. Generate Configuration:
    • Select ‘Generate with Thinkerbell AI’ with Pulumi as your IaC tool.
    • Generate the Pulumi Yaml template that uses Python for the S3 bucket, as shown in the interface.
  1. Merge and Deploy:
    • Click on the ‘Pull request’ to merge the generated code into your GitHub repository, as shown in the image above.

Clone the Git repository containing __main__.py  and Pulumi.yaml files into your local machine and deploy the S3 bucket on AWS.

#main.py import pulumi from pulumi_aws import s3 bucket = s3.Bucket('my-bucket') pulumi.export('bucket_name', bucket.id) #pulumi.yaml name: X-PULUMI-1 runtime: name: python options: toolchain: pip virtualenv: venv description: pulumi simple project config: pulumi:tags: value: pulumi:template: aws-python

Run the pulumi up command to deploy the stack for creating an S3 bucket on AWS.

After the deployment is complete, Pulumi will output the name of the created S3 bucket. 

You can view the created bucket name on the pulumi dashboard by logging in to your pulumi account.

Also, you can see the S3 bucket in the AWS Management Console.

These steps highlight the ease and flexibility of using Pulumi with Firefly Compose to manage AWS resources. This approach not only simplifies deployment but also helps maintain a cohesive and well-governed cloud environment.

Creating S3 bucket Using AWS CloudFormation and Firefly Compose.

Let’s deploy an S3 bucket by generating an AWS CloudFormation configuration in Firefly.

Generate Configuration:

  1. Select Thinkerbell AI: Choose ‘Generate with Thinkerbell AI’ and select ‘CloudFormation’ as your Infrastructure-as-Code (IaC) tool.
  2. Generate Template: Create the template for the S3 bucket with bucket name ‘unique-bucket-name-1234567890’ as shown in the interface.

Merge and Deploy:

  1. Create Pull Request: Click ‘Pull Request’ to merge the generated code into your GitHub repository.

Clone the Git repo containing the cloudformation.yaml file into your local machine to deploy the S3 bucket on AWS:

Resources: MyS3Bucket: Type: "AWS::S3::Bucket" Properties: BucketName: "unique-bucket-name-1234567890"

Run the CloudFormation create-stack command to initiate the deployment of the infrastructure as defined in your CloudFormation template.

After the deployment, You can verify the creation of the bucket in the AWS Management Console under the S3 service.

Having discussed how AWS CloudFormation facilitates the deployment of resources, it’s valuable to explore other IaC tools that offer different approaches and capabilities. One such tool is Terraform, which is widely popular and versatile, making it a preferred choice for many organizations to manage infrastructure across multiple platforms.

Creating S3 bucket Using Terraform and Firefly Compose.

We will discuss how to generate Terraform configuration using Firefly Compose to simplify the creation of an S3 bucket.

Generate Configuration:

  1. Generate Template: Choose the ‘Generate with Thinkerbell AI’ and ‘Terraform’ to generate the Terraform code for the S3 bucket.

Merge and Deploy:

  1. Create Pull Request: Click ‘Pull Request’ to merge the generated code into your GitHub repository.

Clone the Git repository containing main.tf file into your local machine using the git clone command and deploy the S3 bucket on AWS.

provider "aws" { region = "ap-south-1" } resource "aws_s3_bucket" "Firefly-demo" { bucket = "firefly-demo-bucket" acl = "private" }

Deploy the S3 Bucket:

Run the terraform init and terraform apply commands to initialize and apply the Terraform configurations.

You can see the ‘firefly-demo-bucket’ created in the AWS Management Console under the S3 service.

Building Your Infrastructure on AWS? Browse Frequently Asked Questions (FAQ)

Q. What is infrastructure-as-code in AWS?

Infrastructure-as-Code (IaC) in AWS automates cloud resource management using code, not manual setup. IaC defines your infrastructure configuration in templates, enabling infrastructure automation for AWS services like EC2, S3, and VPC. This approach ensures consistency, reduces errors, and accelerates deployment, allowing you to version control and replicate your cloud architecture across environments. Integrating IaC solutions with DevOps practices and your preferred programming language enhances efficiency and scalability.

Q. Which is better, Terraform or CloudFormation?

The choice between Terraform and CloudFormation depends on your specific needs: Terraform is a versatile tool that supports multiple cloud providers, making it ideal for multi-cloud environments and uses HashiCorp Configuration Language (HCL) for easy readability and powerful state management. On the other hand, CloudFormation is deeply integrated with AWS, offering seamless integration with AWS services, automatic rollback on failures, and native support for AWS-specific resources. If you need multi-cloud support and flexibility, Terraform might be better, whereas if you prefer tight integration with AWS and its native features, CloudFormation is a strong choice.

Q. Why is infrastructure-as-code better?

Infrastructure-as-Code (IaC) is better because it automates infrastructure management, reducing human error. By using code to define infrastructure, IaC enables version control, making deployments repeatable and scalable. This approach speeds up provisioning, enhances collaboration through code reviews and tracking, and allows for easy rollback of changes.

Q. What is the difference between infrastructure as code and CI/CD?

Infrastructure-as-Code (IaC) automates the provisioning and management of infrastructure using code, ensuring consistency and repeatability across environments. In contrast, CI/CD (Continuous Integration/Continuous Deployment) automates the software development lifecycle, focusing on integrating, testing, and deploying application code quickly and reliably. While IaC manages infrastructure resources, CI/CD streamlines the development and deployment of software applications, enhancing delivery speed and quality.