Sarvar Nadaf

for AWS Community Builders

Posted on Apr 1 Edited on Jun 6

Terraform Variables and Outputs: Making Your Infrastructure Flexible

#terraform #aws #devops #infrastructure

👋 Hey there, tech enthusiasts!

I'm Sarvar, a Cloud Architect with a passion for transforming complex technological challenges into elegant solutions. With extensive experience spanning Cloud Operations (AWS & Azure), Data Operations, Analytics, DevOps, and Generative AI, I've had the privilege of architecting solutions for global enterprises that drive real business impact. Through this article series, I'm excited to share practical insights, best practices, and hands-on experiences from my journey in the tech world. Whether you're a seasoned professional or just starting out, I aim to break down complex concepts into digestible pieces that you can apply in your projects.

"The difference between a script and reusable infrastructure code is variables."

🎯 Welcome Back!

Remember in Article 3 when you created that S3 bucket? You hardcoded the bucket name directly in the code:

resource "aws_s3_bucket" "my_first_bucket" {
  bucket = "terraform-first-bucket-yourname-2026"  # Hardcoded!
}

That works... once. But what if you need:

10 buckets with different names?
Same code for dev, staging, and production?
To let your team customize configurations?
To reuse this code in different projects?

Today, you'll learn how to make your Terraform code flexible and reusable using variables and outputs.

By the end of this article, you'll:

✅ Convert hardcoded values to variables
✅ Use all variable types (string, number, bool, list, map)
✅ Work with terraform.tfvars files
✅ Create outputs to expose information
✅ Build dev/prod configurations from the same code
✅ Use variable validation and sensitive values

Time Required: 30 minutes

Cost: $0 (using free tier resources)

Difficulty: Beginner-friendly

Let's make your code reusable! 🚀

💔 The Problem: Hardcoded Hell

The Painful Reality

Scenario 1: Multiple Environments

# dev.tf
resource "aws_s3_bucket" "app" {
  bucket = "myapp-dev-bucket"
}

# staging.tf (copy-paste and change)
resource "aws_s3_bucket" "app" {
  bucket = "myapp-staging-bucket"
}

# prod.tf (copy-paste and change again)
resource "aws_s3_bucket" "app" {
  bucket = "myapp-prod-bucket"
}

Problems:

❌ Three copies of the same code
❌ Change one thing = update three files
❌ High risk of mistakes
❌ Nightmare to maintain

Scenario 2: Team Collaboration

Developer 1: "I need the bucket name to be X"
Developer 2: "I need it to be Y"
DevOps: "Production needs Z"

Everyone edits the same .tf file = merge conflicts and chaos!

There's a better way. Enter variables.

🌟 What Are Variables?

Simple Definition

Variables are like function parameters for your infrastructure code.

Think of it like this:

Without Variables (Hardcoded):

function createBucket() {
  return "my-hardcoded-bucket-name";
}

With Variables (Flexible):

function createBucket(bucketName) {
  return bucketName;
}

createBucket("dev-bucket");    // Different uses
createBucket("prod-bucket");   // Same code!

In Terraform:

# Define the variable
variable "bucket_name" {
  description = "Name of the S3 bucket"
  type        = string
}

# Use the variable
resource "aws_s3_bucket" "app" {
  bucket = var.bucket_name  # Reference with var.
}

Same code, different values! That's the power of variables.

Source Code

The complete source code and Terraform configuration used in this article can be found on GitHub:

simplynadaf / terraform-by-sarvar

Terraform Series

🚀 Terraform By Sarvar

Complete Terraform tutorial series from basics to advanced concepts

📖 Read the Series • 🌐 Portfolio • 💼 LinkedIn

📚 Series Overview

This repository contains ONLY Terraform code examples for the Terraform By Sarvar tutorial series.

⚠️ IMPORTANT: This repo contains only .tf files and infrastructure code. Articles are published on dev.to, not stored here.

📖 Read the series on dev.to: https://dev.to/sarvar_04/series/36963

🎯 What You'll Learn

✅ Infrastructure as Code (IaC) fundamentals
✅ Terraform basics to advanced concepts
✅ AWS resource provisioning
✅ Best practices and real-world patterns
✅ Production-ready configurations

📊 Series Progress

📖 Article Series

📘 Foundation (Articles 1-5) ✅ Complete

Introduction to Terraform & IaC - ✅ Published
Installation & Setup - ✅ Published
Your First AWS Resource - ✅ Published
Understanding Terraform State - ✅ Published
Variables and Outputs - ✅ Published

📗 Real Infrastructure (Articles 6-10) ✅ Complete

Building a VPC…

View on GitHub

Getting Started

Follow these steps to run the project on your local machine:

Clone the repository:

git clone https://github.com/simplynadaf/terraform-by-sarvar.git

Navigate to the project directory:

cd terraform-by-sarvar/articles/08-lambda-serverless

🛠️ Hands-On: Your First Variable

Let's convert our hardcoded S3 bucket to use variables.

Step 1: Create Project Directory

mkdir -p ~/terraform-variables-demo
cd ~/terraform-variables-demo

Step 2: Create variables.tf

Create a new file called variables.tf:

nano variables.tf

Add this code:

# String variable - for text values
variable "aws_region" {
  description = "AWS region where resources will be created"
  type        = string
  default     = "us-east-1"
}

variable "bucket_name" {
  description = "Name of the S3 bucket (must be globally unique)"
  type        = string
  # No default - user must provide this value
}

# Map variable - for key-value pairs like tags
variable "common_tags" {
  description = "Common tags to apply to all resources"
  type        = map(string)
  default = {
    Environment = "Development"
    ManagedBy   = "Terraform"
    Project     = "Learning"
  }
}

Understanding the syntax:

description - Explains what the variable is for (always add this!)
type - What kind of value (string, number, bool, list, map)
default - Optional default value (if not provided, user must supply it)

Step 3: Create main.tf

nano main.tf

Add this code:

terraform {
  required_version = ">= 1.0"
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }
}

# Use variable in provider
provider "aws" {
  region = var.aws_region  # Reference variable with var.
}

# Use variables in resource
resource "aws_s3_bucket" "example" {
  bucket = var.bucket_name  # Variable for bucket name

  # Merge common_tags with specific tags
  tags = merge(
    var.common_tags,
    {
      Name = var.bucket_name
    }
  )
}

Notice: We reference variables with var.variable_name

Step 4: Initialize and Test

terraform init
terraform plan

Terraform will prompt you:

var.bucket_name
  Name of the S3 bucket (must be globally unique)

  Enter a value:

Type: my-first-variable-bucket-yourname-2026 and press Enter.

You'll see the plan:

Terraform will perform the following actions:

  # aws_s3_bucket.example will be created
  + resource "aws_s3_bucket" "example" {
      + bucket = "my-first-variable-bucket-yourname-2026"
      + tags   = {
          + "Environment" = "Development"
          + "ManagedBy"   = "Terraform"
          + "Name"        = "my-first-variable-bucket-yourname-2026"
          + "Project"     = "Learning"
        }
    }

Plan: 1 to add, 0 to change, 0 to destroy.

Don't apply yet! Let's learn better ways to pass variables.

📝 Three Ways to Pass Variables

Method 1: Command Line (What We Just Did)

terraform plan
# Terraform prompts for bucket_name

Pros: Interactive

Cons: Tedious for multiple variables

Method 2: Command Line Flags

terraform plan -var="bucket_name=my-bucket-2026"

Pros: Good for CI/CD pipelines

Cons: Long commands with many variables

Method 3: terraform.tfvars File (Best for Most Cases)

Create terraform.tfvars:

nano terraform.tfvars

Add this:

bucket_name = "my-variable-bucket-yourname-2026"
aws_region  = "us-east-1"

common_tags = {
  Environment = "Development"
  ManagedBy   = "Terraform"
  Project     = "Variables Demo"
  Owner       = "YourName"
}

Now run:

terraform plan

No prompts! Terraform automatically loads terraform.tfvars.

Apply it:

terraform apply

Type yes when prompted.

🎉 Success! You just created infrastructure using variables!

🎨 Variable Types: The Complete Guide

Terraform supports multiple variable types. Let's explore them all!

Update variables.tf

Replace your variables.tf with this comprehensive version:

# 1. STRING - Text values
variable "aws_region" {
  description = "AWS region where resources will be created"
  type        = string
  default     = "us-east-1"
}

variable "bucket_name" {
  description = "Name of the S3 bucket (must be globally unique)"
  type        = string
}

variable "bucket_prefix" {
  description = "Prefix for multiple bucket names"
  type        = string
  default     = "terraform-demo"
}

# 2. NUMBER - Numeric values
variable "bucket_count" {
  description = "Number of S3 buckets to create"
  type        = number
  default     = 2

  # Validation rule
  validation {
    condition     = var.bucket_count >= 1 && var.bucket_count <= 5
    error_message = "Bucket count must be between 1 and 5."
  }
}

# 3. BOOLEAN - True/False values
variable "enable_versioning" {
  description = "Enable versioning on the S3 bucket"
  type        = bool
  default     = false
}

# 4. LIST - Ordered collection of values
variable "allowed_ips" {
  description = "List of IP addresses allowed to access the bucket"
  type        = list(string)
  default     = []
}

# 5. MAP - Key-value pairs
variable "common_tags" {
  description = "Common tags to apply to all resources"
  type        = map(string)
  default = {
    Environment = "Development"
    ManagedBy   = "Terraform"
    Project     = "Learning"
  }
}

# 6. ENVIRONMENT - With validation
variable "environment" {
  description = "Environment name (dev, staging, prod)"
  type        = string
  default     = "dev"

  validation {
    condition     = contains(["dev", "staging", "prod"], var.environment)
    error_message = "Environment must be dev, staging, or prod."
  }
}

Update main.tf to Use All Variable Types

terraform {
  required_version = ">= 1.0"
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }
}

provider "aws" {
  region = var.aws_region
}

# Main S3 bucket with variables
resource "aws_s3_bucket" "example" {
  bucket = var.bucket_name

  tags = merge(
    var.common_tags,
    {
      Name = var.bucket_name
    }
  )
}

# Conditional resource - only created if enable_versioning is true
resource "aws_s3_bucket_versioning" "example" {
  count  = var.enable_versioning ? 1 : 0  # Conditional creation
  bucket = aws_s3_bucket.example.id

  versioning_configuration {
    status = "Enabled"
  }
}

# Multiple buckets using count (number variable)
resource "aws_s3_bucket" "multiple" {
  count  = var.bucket_count
  bucket = "${var.bucket_prefix}-${count.index + 1}-yourname-2026"

  tags = var.common_tags
}

What's happening here:

var.enable_versioning ? 1 : 0 - Conditional: if true, create 1 resource; if false, create 0
count = var.bucket_count - Create multiple resources based on number
count.index - Access the current index (0, 1, 2...)
merge() - Combine two maps together

📤 Outputs: Exposing Information

Variables let data IN. Outputs let data OUT.

Why Outputs Matter

Use cases:

Display important information after terraform apply
Pass values to other Terraform modules
Use in scripts or CI/CD pipelines
Share information with team members

Create outputs.tf

nano outputs.tf

Add this code:

# Basic outputs
output "bucket_name" {
  description = "Name of the created S3 bucket"
  value       = aws_s3_bucket.example.id
}

output "bucket_arn" {
  description = "ARN of the S3 bucket"
  value       = aws_s3_bucket.example.arn
}

output "bucket_region" {
  description = "Region where the bucket was created"
  value       = aws_s3_bucket.example.region
}

output "bucket_domain_name" {
  description = "Domain name of the bucket"
  value       = aws_s3_bucket.example.bucket_domain_name
}

# Multiple buckets output
output "multiple_bucket_names" {
  description = "Names of all created buckets"
  value       = aws_s3_bucket.multiple[*].id
}

# Conditional output
output "versioning_enabled" {
  description = "Whether versioning is enabled"
  value       = var.enable_versioning
}

# Map output
output "bucket_tags" {
  description = "Tags applied to the bucket"
  value       = aws_s3_bucket.example.tags
}

# Sensitive output example
output "bucket_id_sensitive" {
  description = "Bucket ID (marked as sensitive)"
  value       = aws_s3_bucket.example.id
  sensitive   = true  # Won't display in plan/apply output
}

Update terraform.tfvars

bucket_name      = "my-variable-bucket-yourname-2026"
bucket_prefix    = "demo-bucket-yourname"
bucket_count     = 2
enable_versioning = true
aws_region       = "us-east-1"

common_tags = {
  Environment = "Development"
  ManagedBy   = "Terraform"
  Project     = "Variables Demo"
  Owner       = "YourName"
}

Apply and See Outputs

terraform apply

After applying, you'll see:

Apply complete! Resources: 4 added, 0 changed, 0 destroyed.

Outputs:

bucket_arn = "arn:aws:s3:::my-variable-bucket-yourname-2026"
bucket_domain_name = "my-variable-bucket-yourname-2026.s3.amazonaws.com"
bucket_id_sensitive = <sensitive>
bucket_name = "my-variable-bucket-yourname-2026"
bucket_region = "us-east-1"
bucket_tags = tomap({
  "Environment" = "Development"
  "ManagedBy" = "Terraform"
  "Name" = "my-variable-bucket-yourname-2026"
  "Owner" = "YourName"
  "Project" = "Variables Demo"
})
multiple_bucket_names = [
  "demo-bucket-yourname-1-yourname-2026",
  "demo-bucket-yourname-2-yourname-2026",
]
versioning_enabled = true

View Outputs Anytime

# View all outputs
terraform output

# View specific output
terraform output bucket_name

# View sensitive output (will reveal the value)
terraform output bucket_id_sensitive

# Output as JSON (useful for scripts)
terraform output -json

🌍 Real-World: Dev vs Prod Configurations

The real power of variables: same code, different configurations!

Create dev.tfvars

nano dev.tfvars

# Development environment configuration
environment       = "dev"
bucket_name       = "myapp-dev-yourname-2026"
bucket_prefix     = "myapp-dev-yourname"
bucket_count      = 2
enable_versioning = false  # Save costs in dev
aws_region        = "us-east-1"

common_tags = {
  Environment = "Development"
  ManagedBy   = "Terraform"
  Project     = "MyApp"
  CostCenter  = "Engineering"
}

Create prod.tfvars

nano prod.tfvars

# Production environment configuration
environment       = "prod"
bucket_name       = "myapp-prod-yourname-2026"
bucket_prefix     = "myapp-prod-yourname"
bucket_count      = 3
enable_versioning = true  # Important for prod!
aws_region        = "us-east-1"

common_tags = {
  Environment = "Production"
  ManagedBy   = "Terraform"
  Project     = "MyApp"
  CostCenter  = "Operations"
  Compliance  = "Required"
}

Deploy to Dev

terraform plan -var-file="dev.tfvars"
terraform apply -var-file="dev.tfvars"

Result: 3 buckets created (1 main + 2 multiple), no versioning

Deploy to Prod

# First destroy dev
terraform destroy -var-file="dev.tfvars"

# Then deploy prod
terraform plan -var-file="prod.tfvars"
terraform apply -var-file="prod.tfvars"

Result: 4 buckets created (1 main + 3 multiple), versioning enabled

Same code, different results! This is how professionals manage multiple environments.

✅ Best Practices

1. Always Add Descriptions

Bad:

variable "name" {
  type = string
}

Good:

variable "bucket_name" {
  description = "Name of the S3 bucket for application logs (must be globally unique)"
  type        = string
}

2. Use Validation Rules

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

  validation {
    condition     = contains(["t2.micro", "t2.small", "t3.micro"], var.instance_type)
    error_message = "Instance type must be t2.micro, t2.small, or t3.micro."
  }
}

3. Provide Sensible Defaults

variable "aws_region" {
  description = "AWS region"
  type        = string
  default     = "us-east-1"  # Most common region
}

4. Use Meaningful Variable Names

Bad: var.n, var.x, var.thing

Good: var.bucket_name, var.instance_count, var.enable_monitoring

5. Group Related Variables

# Network variables
variable "vpc_cidr" { }
variable "subnet_cidrs" { }

# Application variables
variable "app_name" { }
variable "app_version" { }

# Tags
variable "common_tags" { }

6. Never Commit Secrets to tfvars

Bad:

# terraform.tfvars
database_password = "super-secret-password"  # DON'T DO THIS!

Good:

# Use environment variables for secrets
export TF_VAR_database_password="super-secret-password"

Or use AWS Secrets Manager, HashiCorp Vault, etc.

7. Document Your Variables

Create a README.md:

## Required Variables

- `bucket_name` - Globally unique S3 bucket name

## Optional Variables

- `aws_region` - AWS region (default: us-east-1)
- `enable_versioning` - Enable bucket versioning (default: false)

🐛 Common Issues and Solutions

Issue 1: Variable Not Found

Error:

Error: Reference to undeclared input variable

Solution: Make sure variable is declared in variables.tf:

variable "bucket_name" {
  description = "Bucket name"
  type        = string
}

Issue 2: Type Mismatch

Error:

Error: Invalid value for input variable

Solution: Check your variable type matches the value:

variable "bucket_count" {
  type = number  # Not string!
}

In terraform.tfvars:

bucket_count = 2  # Not "2" (string)

Issue 3: Validation Failed

Error:

Error: Invalid value for variable
Bucket count must be between 1 and 5.

Solution: Provide a value that meets the validation condition:

bucket_count = 3  # Within 1-5 range

Issue 4: Forgot to Pass tfvars File

Problem: Terraform uses default values instead of your custom file

Solution: Always specify the file:

terraform apply -var-file="prod.tfvars"

Issue 5: Sensitive Output Not Hidden

Problem: Sensitive data showing in output

Solution: Mark output as sensitive:

output "database_password" {
  value     = var.db_password
  sensitive = true  # Add this
}

🎓 What You Just Learned

Let's recap your new superpowers:

✅ Variables:

Convert hardcoded values to flexible variables
Use all variable types (string, number, bool, list, map)
Add validation rules
Provide defaults

✅ terraform.tfvars:

Store variable values in files
Create environment-specific configs (dev.tfvars, prod.tfvars)
Auto-loading behavior

✅ Outputs:

Display important information
Mark sensitive data
Use in scripts and modules

✅ Real-World Patterns:

Same code, multiple environments
Conditional resource creation
Multiple resource creation with count

🎯 Challenge: Try It Yourself

Before moving to the next article, try these challenges:

Challenge 1: Add More Variables

Add variables for:

owner_email
cost_center
backup_retention_days

Challenge 2: Create staging.tfvars

Create a staging environment configuration between dev and prod.

Challenge 3: Use List Variable

Create a variable for multiple availability zones:

variable "availability_zones" {
  type    = list(string)
  default = ["us-east-1a", "us-east-1b"]
}

Challenge 4: Complex Map Variable

Create a variable for instance configurations:

variable "instance_configs" {
  type = map(object({
    instance_type = string
    volume_size   = number
  }))
}

Challenge 5: Output Formatting

Create an output that combines multiple values:

output "bucket_info" {
  value = "Bucket ${aws_s3_bucket.example.id} in ${var.aws_region}"
}

📚 Additional Variable Features

Variable Precedence (Order of Priority)

Terraform loads variables in this order (last wins):

Environment variables (TF_VAR_name)
terraform.tfvars file
terraform.tfvars.json file
*.auto.tfvars files (alphabetical order)
-var and -var-file command line flags

Example:

# All of these set the same variable
export TF_VAR_bucket_name="from-env"           # Priority 1
# terraform.tfvars: bucket_name = "from-file"  # Priority 2
terraform apply -var="bucket_name=from-cli"    # Priority 3 (wins!)

Environment Variables

# Set variable via environment
export TF_VAR_bucket_name="my-bucket-2026"
export TF_VAR_aws_region="us-west-2"

terraform plan  # Uses environment variables

Auto-Loading tfvars Files

Terraform automatically loads:

terraform.tfvars
terraform.tfvars.json
*.auto.tfvars
*.auto.tfvars.json

Example:

# These are auto-loaded
terraform.tfvars
common.auto.tfvars
secrets.auto.tfvars

# These need -var-file flag
dev.tfvars
prod.tfvars

🔍 Understanding Variable Interpolation

You can use variables in many ways:

String Interpolation

resource "aws_s3_bucket" "example" {
  bucket = "${var.environment}-${var.app_name}-bucket"
  # Result: "dev-myapp-bucket"
}

Conditional Expressions

resource "aws_instance" "web" {
  instance_type = var.environment == "prod" ? "t3.large" : "t3.micro"
  # prod = t3.large, anything else = t3.micro
}

For Expressions

locals {
  bucket_names = [for i in range(var.bucket_count) : "${var.prefix}-${i}"]
  # Result: ["app-0", "app-1", "app-2"]
}

🔗 Useful Resources

Terraform Variables Docs: https://developer.hashicorp.com/terraform/language/values/variables
Terraform Outputs Docs: https://developer.hashicorp.com/terraform/language/values/outputs
Variable Validation: https://developer.hashicorp.com/terraform/language/values/variables#custom-validation-rules
Type Constraints: https://developer.hashicorp.com/terraform/language/expressions/type-constraints

🎬 What's Next?

In Article 6: Building a VPC from Scratch, we'll:

Create a complete AWS VPC with subnets
Use variables for network configuration
Build public and private subnets
Configure route tables and internet gateways
Apply everything you learned about variables

You'll learn:

Real-world networking with Terraform
Complex resource dependencies
Advanced variable usage
Production-ready VPC architecture

📌 Wrapping Up

Thank you for reading. I hope this article provided practical insights and a clearer understanding of the topic.

If you found this useful:

❤️ Like if it added value
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💡 What’s Next

More deep dives are coming soon on:

Cloud Operations
GenAI & Agentic AI
DevOps Automation
Data & Platform Engineering

Follow along for weekly insights and hands-on guides.

🌐 Portfolio & Work

You can explore my full body of work, certifications, architecture projects, and technical articles here:

👉 Visit My Website

🛠️ Services I Offer

If you're looking for hands-on guidance or collaboration, I provide:

Cloud Architecture Consulting (AWS / Azure)
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🤝 Let’s Connect

I’d love to hear your thoughts. Feel free to drop a comment or connect with me on:

🔗 LinkedIn

For collaborations, consulting, or technical discussions, reach out at:

📧 simplynadaf@gmail.com

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Made by Sarvar Nadaf

🌐 https://sarvarnadaf.com