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Skills/aradotso/data-skills/terraform-iac-data-engineering
terraform-iac-data-engineering logo

terraform-iac-data-engineering

aradotso/data-skills
650 installs1 stars
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Installation

npx skills add https://github.com/aradotso/data-skills --skill terraform-iac-data-engineering

Summary

Infrastructure-as-Code with Terraform for data engineering on AWS (S3, EC2, IAM)

SKILL.md

Terraform IaC for Data Engineering

Skill by ara.so — Data Skills collection.

This project provides Infrastructure-as-Code (IaC) patterns using Terraform specifically for data engineering workloads on AWS. It demonstrates how to provision and manage AWS resources (S3, EC2, IAM) needed for data pipelines and processing.

What This Project Does

  • Provisions AWS S3 buckets for data storage
  • Creates EC2 instances for data processing workloads
  • Manages IAM users, roles, and policies
  • Demonstrates Terraform state management
  • Provides reusable IaC patterns for data engineering infrastructure

Installation

Prerequisites

  1. Terraform CLI
   # macOS
   brew install terraform
   
   # Linux
   wget https://releases.hashicorp.com/terraform/1.5.0/terraform_1.5.0_linux_amd64.zip
   unzip terraform_1.5.0_linux_amd64.zip
   sudo mv terraform /usr/local/bin/
  1. AWS CLI
   # macOS
   brew install awscli
   
   # Linux
   curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
   unzip awscliv2.zip
   sudo ./aws/install
  1. Configure AWS CLI
   aws configure
   # Enter your AWS Access Key ID
   # Enter your AWS Secret Access Key
   # Default region: us-east-1
   # Default output format: json

Project Setup

git clone https://github.com/josephmachado/iac-for-data-engineering-terraform-.git
cd iac-for-data-engineering-terraform-

Key Terraform Commands

Initialize Terraform

# Initialize terraform (downloads providers, sets up backend)
terraform -chdir=terraform init

# Validate configuration files
terraform -chdir=terraform validate

# Format configuration files
terraform -chdir=terraform fmt

Plan and Apply Infrastructure

# Preview changes before applying
terraform -chdir=terraform plan

# Apply infrastructure changes
terraform -chdir=terraform apply

# Auto-approve without confirmation (use with caution)
terraform -chdir=terraform apply -auto-approve

Inspect Infrastructure

# List all resources in state
terraform -chdir=terraform state list

# Show details of a specific resource
terraform -chdir=terraform state show aws_s3_bucket.data_bucket

# Output specific values
terraform -chdir=terraform output

# Show current state in JSON
terraform -chdir=terraform show -json

Destroy Infrastructure

# Destroy all managed infrastructure
terraform -chdir=terraform destroy

# Destroy specific resource
terraform -chdir=terraform destroy -target=aws_instance.data_processor

Configuration Structure

Basic Terraform Configuration for Data Engineering

main.tf - Core infrastructure definition:

terraform {
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }
}

provider "aws" {
  region = var.aws_region
}

# S3 bucket for data storage
resource "aws_s3_bucket" "data_lake" {
  bucket = "my-unique-data-lake-bucket-${var.environment}"
  
  tags = {
    Name        = "Data Lake Bucket"
    Environment = var.environment
    Project     = "DataEngineering"
  }
}

# Enable versioning for data protection
resource "aws_s3_bucket_versioning" "data_lake_versioning" {
  bucket = aws_s3_bucket.data_lake.id
  
  versioning_configuration {
    status = "Enabled"
  }
}

# Block public access
resource "aws_s3_bucket_public_access_block" "data_lake_public_access" {
  bucket = aws_s3_bucket.data_lake.id
  
  block_public_acls       = true
  block_public_policy     = true
  ignore_public_acls      = true
  restrict_public_buckets = true
}

# EC2 instance for data processing
resource "aws_instance" "data_processor" {
  ami           = var.ec2_ami
  instance_type = var.ec2_instance_type
  
  tags = {
    Name        = "DataProcessor"
    Environment = var.environment
  }
  
  user_data = <<-EOF
              #!/bin/bash
              sudo yum update -y
              sudo yum install -y python3 python3-pip
              pip3 install pandas boto3
              EOF
}

# IAM role for EC2 to access S3
resource "aws_iam_role" "ec2_s3_access_role" {
  name = "ec2-s3-access-role"
  
  assume_role_policy = jsonencode({
    Version = "2012-10-17"
    Statement = [
      {
        Action = "sts:AssumeRole"
        Effect = "Allow"
        Principal = {
          Service = "ec2.amazonaws.com"
        }
      }
    ]
  })
}

# IAM policy for S3 access
resource "aws_iam_role_policy" "ec2_s3_policy" {
  name = "ec2-s3-policy"
  role = aws_iam_role.ec2_s3_access_role.id
  
  policy = jsonencode({
    Version = "2012-10-17"
    Statement = [
      {
        Effect = "Allow"
        Action = [
          "s3:GetObject",
          "s3:PutObject",
          "s3:ListBucket"
        ]
        Resource = [
          aws_s3_bucket.data_lake.arn,
          "${aws_s3_bucket.data_lake.arn}/*"
        ]
      }
    ]
  })
}

# Attach IAM role to EC2 instance
resource "aws_iam_instance_profile" "ec2_profile" {
  name = "ec2-s3-profile"
  role = aws_iam_role.ec2_s3_access_role.name
}

variables.tf - Input variables:

variable "aws_region" {
  description = "AWS region for resources"
  type        = string
  default     = "us-east-1"
}

variable "environment" {
  description = "Environment name (dev, staging, prod)"
  type        = string
  default     = "dev"
}

variable "ec2_ami" {
  description = "AMI ID for EC2 instance"
  type        = string
  default     = "ami-0c55b159cbfafe1f0"  # Amazon Linux 2
}

variable "ec2_instance_type" {
  description = "EC2 instance type"
  type        = string
  default     = "t2.micro"
}

variable "bucket_prefix" {
  description = "Prefix for S3 bucket names"
  type        = string
  default     = "data-eng"
}

outputs.tf - Output values:

output "s3_bucket_name" {
  description = "Name of the S3 data lake bucket"
  value       = aws_s3_bucket.data_lake.id
}

output "s3_bucket_arn" {
  description = "ARN of the S3 bucket"
  value       = aws_s3_bucket.data_lake.arn
}

output "ec2_instance_id" {
  description = "ID of the EC2 data processor"
  value       = aws_instance.data_processor.id
}

output "ec2_public_ip" {
  description = "Public IP of EC2 instance"
  value       = aws_instance.data_processor.public_ip
}

terraform.tfvars - Variable values (gitignore this file):

aws_region         = "us-west-2"
environment        = "production"
ec2_instance_type  = "t3.medium"
bucket_prefix      = "my-company-data"

Common Data Engineering Patterns

Multi-Environment Setup

environments/dev/main.tf:

module "data_infrastructure" {
  source = "../../modules/data-infra"
  
  environment       = "dev"
  instance_type     = "t2.micro"
  enable_monitoring = false
}

environments/prod/main.tf:

module "data_infrastructure" {
  source = "../../modules/data-infra"
  
  environment       = "prod"
  instance_type     = "t3.xlarge"
  enable_monitoring = true
  backup_enabled    = true
}

S3 Bucket with Lifecycle Policies

resource "aws_s3_bucket" "data_archive" {
  bucket = "data-archive-${var.environment}"
}

resource "aws_s3_bucket_lifecycle_configuration" "data_archive_lifecycle" {
  bucket = aws_s3_bucket.data_archive.id
  
  rule {
    id     = "archive-old-data"
    status = "Enabled"
    
    transition {
      days          = 30
      storage_class = "STANDARD_IA"
    }
    
    transition {
      days          = 90
      storage_class = "GLACIER"
    }
    
    expiration {
      days = 365
    }
  }
  
  rule {
    id     = "delete-incomplete-uploads"
    status = "Enabled"
    
    abort_incomplete_multipart_upload {
      days_after_initiation = 7
    }
  }
}

VPC Setup for Data Processing

resource "aws_vpc" "data_vpc" {
  cidr_block           = "10.0.0.0/16"
  enable_dns_hostnames = true
  enable_dns_support   = true
  
  tags = {
    Name = "data-engineering-vpc"
  }
}

resource "aws_subnet" "private_subnet" {
  vpc_id            = aws_vpc.data_vpc.id
  cidr_block        = "10.0.1.0/24"
  availability_zone = "${var.aws_region}a"
  
  tags = {
    Name = "private-data-subnet"
  }
}

resource "aws_security_group" "data_processor_sg" {
  name        = "data-processor-sg"
  description = "Security group for data processing instances"
  vpc_id      = aws_vpc.data_vpc.id
  
  egress {
    from_port   = 0
    to_port     = 0
    protocol    = "-1"
    cidr_blocks = ["0.0.0.0/0"]
  }
  
  ingress {
    from_port   = 22
    to_port     = 22
    protocol    = "tcp"
    cidr_blocks = ["10.0.0.0/16"]
  }
}

Remote State Configuration

backend.tf:

terraform {
  backend "s3" {
    bucket         = "terraform-state-bucket-unique-name"
    key            = "data-engineering/terraform.tfstate"
    region         = "us-east-1"
    encrypt        = true
    dynamodb_table = "terraform-state-lock"
  }
}

Create state backend resources:

resource "aws_s3_bucket" "terraform_state" {
  bucket = "terraform-state-bucket-unique-name"
}

resource "aws_s3_bucket_versioning" "terraform_state_versioning" {
  bucket = aws_s3_bucket.terraform_state.id
  
  versioning_configuration {
    status = "Enabled"
  }
}

resource "aws_dynamodb_table" "terraform_locks" {
  name         = "terraform-state-lock"
  billing_mode = "PAY_PER_REQUEST"
  hash_key     = "LockID"
  
  attribute {
    name = "LockID"
    type = "S"
  }
}

Verification and Testing

Verify S3 Bucket Creation

# List all S3 buckets
aws s3 ls

# Check specific bucket
aws s3 ls s3://my-unique-data-lake-bucket-dev/

# Upload test file
echo "test data" > test.txt
aws s3 cp test.txt s3://my-unique-data-lake-bucket-dev/

Verify EC2 Instances

# List running instances
aws ec2 describe-instances \
  --filters "Name=instance-state-name,Values=running" \
  --query 'Reservations[].Instances[].{ID:InstanceId, Name:Tags[?Key==`Name`].Value, Type:InstanceType, State:State.Name, PublicIP:PublicIpAddress}' \
  --output table

# Get specific instance details
aws ec2 describe-instances \
  --instance-ids $(terraform -chdir=terraform output -raw ec2_instance_id)

Verify IAM Roles

# List IAM roles
aws iam list-roles --query 'Roles[?contains(RoleName, `ec2-s3-access`)].RoleName'

# Get role policy
aws iam get-role-policy \
  --role-name ec2-s3-access-role \
  --policy-name ec2-s3-policy

State Management

Inspect State

# View state file (formatted)
cat terraform/terraform.tfstate | jq -r '.resources[] | [.type, .name] | join(",")'

# List resources in state
terraform -chdir=terraform state list

# Show resource details
terraform -chdir=terraform state show aws_s3_bucket.data_lake

Import Existing Resources

# Import existing S3 bucket
terraform -chdir=terraform import aws_s3_bucket.data_lake my-existing-bucket

# Import existing EC2 instance
terraform -chdir=terraform import aws_instance.data_processor i-1234567890abcdef0

Move Resources in State

# Rename resource in state
terraform -chdir=terraform state mv aws_s3_bucket.old_name aws_s3_bucket.new_name

Troubleshooting

Common Issues

Issue: Bucket name already exists

# Solution: Use unique bucket name with random suffix
resource "random_id" "bucket_suffix" {
  byte_length = 4
}

resource "aws_s3_bucket" "data_lake" {
  bucket = "data-lake-${var.environment}-${random_id.bucket_suffix.hex}"
}

Issue: AWS credentials not found

# Check AWS configuration
aws configure list

# Use environment variables
export AWS_ACCESS_KEY_ID="${AWS_ACCESS_KEY_ID}"
export AWS_SECRET_ACCESS_KEY="${AWS_SECRET_ACCESS_KEY}"
export AWS_DEFAULT_REGION="us-east-1"

Issue: State file locked

# Force unlock (use with caution)
terraform -chdir=terraform force-unlock <LOCK_ID>

Issue: Resource already exists

# Import existing resource
terraform -chdir=terraform import <resource_type>.<resource_name> <resource_id>

# Or remove from state
terraform -chdir=terraform state rm <resource_type>.<resource_name>

Issue: Terraform version mismatch

# Specify required version in terraform block
terraform {
  required_version = ">= 1.5.0"
  
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }
}

Debugging

# Enable debug logging
export TF_LOG=DEBUG
terraform -chdir=terraform apply

# Log to file
export TF_LOG_PATH=terraform-debug.log
terraform -chdir=terraform apply

# Disable logging
unset TF_LOG
unset TF_LOG_PATH

Validate and Format

# Validate configuration
terraform -chdir=terraform validate

# Format all files
terraform -chdir=terraform fmt -recursive

# Check formatting without making changes
terraform -chdir=terraform fmt -check

Best Practices

  1. Always use variables for environment-specific values
  2. Enable S3 versioning for state files and data buckets
  3. Use remote state for team collaboration
  4. Tag all resources with environment, project, and owner
  5. Implement lifecycle policies for cost optimization
  6. Use modules for reusable infrastructure patterns
  7. Store secrets in AWS Secrets Manager, reference via data sources
  8. Run terraform plan before apply
  9. Use workspaces for multiple environments
  10. Document your infrastructure with comments and README files

Score

0–100
63/ 100

Grade

C

Popularity15/30

650 installs — growing adoption.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Terraform Iac Data Engineering skill score badge previewScore badge

Markdown

[![Terraform Iac Data Engineering skill](https://www.claudemarket.ai/skills/aradotso/data-skills/terraform-iac-data-engineering/badges/score.svg)](https://www.claudemarket.ai/skills/aradotso/data-skills/terraform-iac-data-engineering)

HTML

<a href="https://www.claudemarket.ai/skills/aradotso/data-skills/terraform-iac-data-engineering"><img src="https://www.claudemarket.ai/skills/aradotso/data-skills/terraform-iac-data-engineering/badges/score.svg" alt="Terraform Iac Data Engineering skill"/></a>

Terraform Iac Data Engineering FAQ

How do I install the Terraform Iac Data Engineering skill?

Run “npx skills add https://github.com/aradotso/data-skills --skill terraform-iac-data-engineering” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Terraform Iac Data Engineering skill do?

Infrastructure-as-Code with Terraform for data engineering on AWS (S3, EC2, IAM) The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Terraform Iac Data Engineering skill free?

Yes. Terraform Iac Data Engineering is a free, open-source skill published from aradotso/data-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Terraform Iac Data Engineering work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Terraform Iac Data Engineering works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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