ChatGPT vs DeepSeek vs Mistral: Terraform
Sure! Here's a step-by-step Terraform AWS tutorial updated for 2025, which will help you get started with provisioning AWS infrastructure using Terraform.
Terraform AWS Tutorial 2025
Prerequisites
- Terraform installed (v1.5+ recommended)
- Download: https://www.terraform.io/downloads.html
- AWS Account
- AWS CLI installed and configured (optional but recommended)
- Install: https://aws.amazon.com/cli/
- Configure:
aws configure
Step 1: Set up your project
Create a new directory for your Terraform project and initiate Terraform.
mkdir terraform-aws-demo
cd terraform-aws-demo
Create a file named main.tf
:
terraform {
required_providers {
aws = {
source = "hashicorp/aws"
version = "~> 5.0"
}
}
required_version = ">= 1.5.0"
}provider "aws" {
region = "us-east-1"
}
Step 2: Create an AWS EC2 instance
Add this resource to your main.tf
to provision a simple EC2 instance:
resource "aws_instance" "example" {
ami = "ami-08c40ec9ead489470" # Amazon Linux 2 AMI in us-east-1 (confirm latest in your region)
instance_type = "t2.micro" tags = {
Name = "TerraformExampleInstance"
}
}
Note: Always verify the latest AMI ID for your region from AWS Console or CLI.
Step 3: Initialize Terraform
Run:
terraform init
This downloads the AWS provider plugin and prepares your project.
Step 4: Plan the deployment
Check what Terraform will do:
terraform plan
Review the output to verify resources to be created.
Step 5: Apply the configuration
Create the resources in AWS:
terraform apply
Type yes
to confirm.
Terraform will provision your EC2 instance.
Step 6: Verify your infrastructure
Log into AWS Console -> EC2 dashboard to verify the instance is running.
Step 7: Clean up (optional)
When done, destroy the resources to prevent costs:
terraform destroy
Type yes
to confirm.
Additional Tips
- State Management: Terraform stores state locally by default (
terraform.tfstate
). For team collaboration, consider remote state storage (e.g., S3 backend with DynamoDB lock). - Security: Never commit AWS credentials or sensitive info to version control.
- Variable Usage: Use variables to parametrize your configurations (see
variables.tf
):
variable "region" {
description = "AWS region"
type = string
default = "us-east-1"
}
And reference it:
provider "aws" {
region = var.region
}
- Modules: Break your infrastructure into reusable modules for larger projects.
If you want, I can provide sample code for those advanced topics or help set up VPCs, IAM roles, S3 buckets, etc. Just ask!
I'll provide you with a comprehensive Terraform AWS tutorial for 2025, covering modern best practices and the latest features.
Prerequisites
- Terraform 1.7+ (latest version)
- AWS CLI configured with credentials
- Basic AWS knowledge
1. Setup and Installation
Install Terraform
# On macOS
brew tap hashicorp/tap
brew install hashicorp/tap/terraform# On Windows (Chocolatey)
choco install terraform
# On Linux
wget -O- https://apt.releases.hashicorp.com/gpg | sudo gpg --dearmor -o /usr/share/keyrings/hashicorp-archive-keyring.gpg
echo "deb [signed-by=/usr/share/keyrings/hashicorp-archive-keyring.gpg] https://apt.releases.hashicorp.com $(lsb_release -cs) main" | sudo tee /etc/apt/sources.list.d/hashicorp.list
sudo apt update && sudo apt install terraform
Configure AWS CLI
aws configure
# Enter your AWS Access Key, Secret Key, region (us-east-1), and output format (json)
2. Project Structure
Create the following directory structure:
terraform-aws-project/
├── main.tf
├── variables.tf
├── outputs.tf
├── terraform.tfvars
└── providers.tf
3. Basic Configuration
providers.tf
terraform {
required_version = ">= 1.7.0"
required_providers {
aws = {
source = "hashicorp/aws"
version = "~> 5.0"
}
} # Optional: Remote State Backend (S3 recommended)
backend "s3" {
bucket = "my-terraform-state-2025"
key = "terraform.tfstate"
region = "us-east-1"
# For state locking
dynamodb_table = "terraform-state-locking"
}
}
provider "aws" {
region = var.aws_region
default_tags {
tags = {
Environment = var.environment
Project = "terraform-tutorial-2025"
ManagedBy = "terraform"
}
}
}
variables.tf
variable "aws_region" {
description = "AWS region"
type = string
default = "us-east-1"
}variable "environment" {
description = "Deployment environment"
type = string
default = "dev"
validation {
condition = contains(["dev", "staging", "prod"], var.environment)
error_message = "Environment must be dev, staging, or prod."
}
}
variable "vpc_cidr" {
description = "CIDR block for VPC"
type = string
default = "10.0.0.0/16"
}
variable "instance_type" {
description = "EC2 instance type"
type = string
default = "t3.micro"
}
variable "enable_monitoring" {
description = "Enable CloudWatch monitoring"
type = bool
default = true
}
4. Core Infrastructure
main.tf
```hcl
VPC Module (using community module for best practices)
module "vpc" {
source = "terraform-aws-modules/vpc/aws"
version = "~> 5.0"
name = "main-vpc-${var.environment}"
cidr = var.vpc_cidr
azs = ["us-east-1a", "us-east-1b"]
private_subnets = ["10.0.1.0/24", "10.0.2.0/24"]
public_subnets = ["10.0.101.0/24", "10.0.102.0/24"]
enablenatgateway = true
enablevpngateway = false
singlenatgateway = var.environment == "dev" ? true : false
tags = {
Environment = var.environment
Terraform = "true"
}
}
Security Group
resource "awssecuritygroup" "web_sg" {
name = "web-sg-${var.environment}"
description = "Security group for web servers"
vpcid = module.vpc.vpcid
ingress {
description = "HTTP"
from_port = 80
to_port = 80
protocol = "tcp"
cidr_blocks = ["0.0.0.0/0"]
}
ingress {
description = "HTTPS"
from_port = 443
to_port = 443
protocol = "tcp"
cidr_blocks = ["0.0.0.0/0"]
}
ingress {
description = "SSH"
from_port = 22
to_port = 22
protocol = "tcp"
cidr_blocks = ["0.0.0.0/0"]
}
egress {
from_port = 0
to_port = 0
protocol = "-1"
cidr_blocks = ["0.0.0.0/0"]
}
tags = {
Name = "web-sg-${var.environment}"
}
}
EC2 Instance with latest Amazon Linux 2023
data "awsami" "amazonlinux_2023" {
most_recent = true
owners = ["amazon"]
filter {
name = "name"
values = ["al2023-ami-2023.*-x86_64"]
}
filter {
name = "virtualization-type"
values = ["hvm"]
}
}
IAM Role for EC2
resource "awsiamrole" "ec2_role" {
name = "ec2-role-${var.environment}"
assumerolepolicy = jsonencode({
Version = "2012-10-17"
Statement = [
{
Action = "sts:AssumeRole"
Effect = "Allow"
Principal = {
Service = "ec2.amazonaws.com"
}
}
]
})
}
resource "awsiamrolepolicyattachment" "ssmmanagedinstance" {
role = awsiamrole.ec2_role.name
policy_arn = "arn:aws:iam::aws:policy/AmazonSSMManagedInstanceCore"
}
resource "awsiaminstanceprofile" "ec2profile" {
name = "ec2-profile-${var.environment}"
role = awsiamrole.ec2_role.name
}
EC2 Instance
resource "awsinstance" "webserver" {
ami = data.awsami.amazonlinux_2023.id
instancetype = var.instancetype
subnetid = module.vpc.publicsubnets[0]
vpcsecuritygroupids = [awssecuritygroup.websg.id]
iaminstanceprofile = awsiaminstanceprofile.ec2profile.name
user_data = base64encode(<<-EOF
#!/bin/bash
dnf update -y
dnf install -y nginx
systemctl start nginx
systemctl enable nginx
echo "
Hello from Terraform AWS 2025!
" > /usr/share/nginx/html/index.htmlEOF
)
metadata_options {
http_endpoint = "enabled"
http_tokens = "required"
}
monitoring = var.enable_monitoring
tags = {
Name = "web-server-${var.environment}"
}
lifecycle {
createbeforedestroy = true
ignore_changes = [ami]
}
}
Application Load Balancer
resource "awslb" "webalb" {
name = "web-alb-${var.environment}"
internal = false
loadbalancertype = "application"
securitygroups = [awssecuritygroup.websg.id]
subnets = module.vpc.public_subnets
enabledeletionprotection = var.environment == "prod" ? true : false
tags = {
Environment = var.environment
}
}
resource "awslbtargetgroup" "webtg" {
name = "web-tg-${var.environment}"
port = 80
protocol = "HTTP"
vpcid = module.vpc.vpcid
health_check {
enabled = true
interval = 30
path = "/"
port = "traffic-port"
protocol = "HTTP"
timeout = 5
healthy_threshold = 2
unhealthy_threshold = 2
}
}
resource "awslbtargetgroupattachment" "webtgattachment" {
targetgrouparn = awslbtargetgroup.webtg.arn
targetid = awsinstance.web_server.id
Creating a Terraform tutorial for AWS in 2025 involves setting up and managing AWS resources using Terraform, an open-source infrastructure as code (IaC) tool. Below is a step-by-step guide to help you get started with Terraform on AWS. This tutorial assumes you have basic knowledge of AWS and Terraform.
Prerequisites
- AWS Account: Ensure you have an AWS account.
- Terraform Installed: Install Terraform on your local machine. You can download it from the Terraform website.
- AWS CLI Installed: Install the AWS Command Line Interface (CLI) and configure it with your AWS credentials.
Step 1: Set Up Your Environment
- Install Terraform:
# For macOS
brew tap hashicorp/tap
brew install hashicorp/tap/terraform # For Linux
sudo apt-get update && sudo apt-get install -y gnupg software-properties-common curl
curl -fsSL https://apt.releases.hashicorp.com/gpg | sudo apt-key add -
sudo apt-add-repository "deb [arch=amd64] https://apt.releases.hashicorp.com $(lsb_release -cs) main"
sudo apt-get update && sudo apt-get install terraform
- Install AWS CLI:
# For macOS
brew install awscli # For Linux
sudo apt-get update && sudo apt-get install -y awscli
- Configure AWS CLI:
aws configure
Follow the prompts to enter your AWS Access Key, Secret Key, region, and output format.
Step 2: Create a Terraform Configuration
- Create a Directory for Your Project:
mkdir terraform-aws-tutorial
cd terraform-aws-tutorial
- Create a
main.tf
File:
provider "aws" {
region = "us-west-2"
} resource "aws_instance" "example" {
ami = "ami-0c55b159cbfafe1f0" # Amazon Linux 2 AMI (HVM), SSD Volume Type
instance_type = "t2.micro"
tags = {
Name = "TerraformExampleInstance"
}
}
Step 3: Initialize Terraform
- Initialize the Configuration:
terraform init
Step 4: Plan and Apply the Configuration
- Plan the Infrastructure:
terraform plan
This command will show you the actions Terraform will take to create the infrastructure.
- Apply the Configuration:
terraform apply
Confirm the action by typing
yes
when prompted.Step 5: Verify the Resources
- Check AWS Console:
- Use AWS CLI:
aws ec2 describe-instances --instance-ids <instance-id>
Step 6: Modify the Configuration
- Update
main.tf
:
resource "aws_instance" "example" {
ami = "ami-0c55b159cbfafe1f0"
instance_type = "t2.micro" tags = {
Name = "TerraformExampleInstance"
Environment = "Dev"
}
}
- Plan and Apply the Changes:
terraform plan
terraform apply
Step 7: Destroy the Resources
- Destroy the Infrastructure:
terraform destroy
Confirm the action by typing
yes
when prompted.Additional Tips
- State Management: Use remote backends like AWS S3 and DynamoDB for state management in a team environment.
- Modules: Break down your configuration into reusable modules.
- Variables: Use variables to make your configuration more flexible.
- Outputs: Use outputs to expose information about your infrastructure.
Example with Variables and Outputs
- Create
variables.tf
:
variable "instance_type" {
description = "The type of instance to start"
type = string
default = "t2.micro"
} variable "ami" {
description = "The AMI to use for the instance"
type = string
default = "ami-0c55b159cbfafe1f0"
}
- Update
main.tf
:
provider "aws" {
region = "us-west-2"
} resource "aws_instance" "example" {
ami = var.ami
instance_type = var.instance_type
tags = {
Name = "TerraformExampleInstance"
}
}
- Create
outputs.tf
:
output "instance_id" {
description = "The ID of the EC2 instance"
value = aws_instance.example.id
} output "instance_public_ip" {
description = "The public IP of the EC2 instance"
value = aws_instance.example.public_ip
}
- Plan and Apply:
terraform plan
terraform apply
Conclusion
This tutorial provides a basic introduction to using Terraform with AWS. As you become more comfortable with Terraform, you can explore more advanced features such as modules, state management, and remote backends. Happy coding!
💡 Try this comparison yourself:Compare AI models side-by-side on SNEOS
Analysis
This comparison demonstrates the different approaches each AI model takes when responding to the same prompt. Here are the key differences observed:
Response Characteristics
ChatGPT: Provides a direct response with 36 sentences.
DeepSeek: Provides a direct response with 110 sentences.
Mistral: Provides a direct response with 62 sentences.
Key Takeaways
- Each model brings unique strengths to this type of query
- Response styles vary significantly between models
- Consider your specific use case when choosing between these models
Try This Comparison Yourself
Want to test these models with your own prompts? Visit SNEOS.com to compare AI responses side-by-side in real-time.
This comparison was generated using the SNEOS AI Comparison ToolPublished: October 01, 2025 | Models: ChatGPT, DeepSeek, Mistral