Provision Infrastructure with Terraform

Implement infrastructure as code using Terraform to provision, version, and manage cloud resources across AWS, Azure, GCP, and other providers.

When to Use

• Provisioning new cloud infrastructure (VPCs, compute, storage, databases)
• Migrating from ClickOps or CloudFormation to declarative IaC
• Managing multi-environment infrastructure (dev, staging, production)
• Implementing reproducible infrastructure patterns across teams
• Versioning infrastructure changes alongside application code
• Enforcing infrastructure standards through reusable modules

Inputs

• Required: Terraform CLI installed (terraform --version)
• Required: Cloud provider credentials (AWS, Azure, GCP service accounts)
• Required: Remote state backend configuration (S3, Azure Storage, Terraform Cloud)
• Optional: Existing infrastructure to import or migrate
• Optional: Terraform Cloud/Enterprise for team collaboration
• Optional: Pre-commit hooks for validation and formatting

Procedure

See Extended Examples for complete configuration files and templates.

Step 1: Initialize Terraform Project Structure

Create organized directory structure with backend configuration and provider setup.

# Create project structure
mkdir -p terraform/{modules,environments/{dev,staging,prod}}
cd terraform

# Create backend configuration
cat > backend.tf <<'EOF'
terraform {
  required_version = ">= 1.6"

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

  backend "s3" {
    bucket         = "my-terraform-state"
    key            = "infrastructure/terraform.tfstate"
    region         = "us-east-1"
    encrypt        = true
    dynamodb_table = "terraform-lock"

    # Workspace-specific state files
    workspace_key_prefix = "env"
  }
}

provider "aws" {
  region = var.aws_region

  default_tags {
    tags = {
      ManagedBy   = "Terraform"
      Environment = terraform.workspace
      Project     = var.project_name
    }
  }
}
EOF

# Create variables file
cat > variables.tf <<'EOF'
variable "aws_region" {
  description = "AWS region for resources"
  type        = string
  default     = "us-east-1"
}

variable "project_name" {
  description = "Project name for resource naming and tagging"
  type        = string
  validation {
    condition     = length(var.project_name) > 0 && length(var.project_name) <= 32
    error_message = "Project name must be 1-32 characters"
  }
}

variable "environment" {
  description = "Environment name (dev, staging, prod)"
  type        = string
  validation {
    condition     = contains(["dev", "staging", "prod"], var.environment)
    error_message = "Environment must be dev, staging, or prod"
  }
}
EOF

# Initialize Terraform
terraform init

Expected: Terraform initializes successfully, downloads provider plugins, configures remote backend. .terraform/ directory created with provider binaries. State backend connection verified.

On failure: If backend initialization fails, verify S3 bucket exists and IAM permissions allow s3:GetObject, s3:PutObject, dynamodb:GetItem, dynamodb:PutItem. For provider download failures, check network connectivity and corporate proxy settings. Run terraform init -upgrade to update providers.

Step 2: Create Reusable Infrastructure Modules

Build composable modules for VPC, compute, and data infrastructure with input validation.

# modules/vpc/main.tf
variable "vpc_cidr" {
  description = "CIDR block for VPC"
  type        = string
  default     = "10.0.0.0/16"
}

variable "availability_zones" {
  description = "List of AZs to use"
  type        = list(string)
}

variable "project_name" {
  description = "Project name for resource naming"
  type        = string
}

variable "environment" {
  description = "Environment name"
  type        = string
}

locals {
  common_tags = {
    Project     = var.project_name
    Environment = var.environment
    Module      = "vpc"
  }
}

resource "aws_vpc" "main" {
  cidr_block           = var.vpc_cidr
  enable_dns_hostnames = true
  enable_dns_support   = true

  tags = merge(local.common_tags, {
    Name = "${var.project_name}-${var.environment}-vpc"
  })
}

resource "aws_subnet" "public" {
  count             = length(var.availability_zones)
  vpc_id            = aws_vpc.main.id
  cidr_block        = cidrsubnet(var.vpc_cidr, 8, count.index)
  availability_zone = var.availability_zones[count.index]

  map_public_ip_on_launch = true

  tags = merge(local.common_tags, {
    Name = "${var.project_name}-${var.environment}-public-${var.availability_zones[count.index]}"
    Type = "public"
  })
}

resource "aws_subnet" "private" {
  count             = length(var.availability_zones)
  vpc_id            = aws_vpc.main.id
  cidr_block        = cidrsubnet(var.vpc_cidr, 8, count.index + 100)
  availability_zone = var.availability_zones[count.index]

  tags = merge(local.common_tags, {
    Name = "${var.project_name}-${var.environment}-private-${var.availability_zones[count.index]}"
    Type = "private"
  })
}

resource "aws_internet_gateway" "main" {
  vpc_id = aws_vpc.main.id

  tags = merge(local.common_tags, {
    Name = "${var.project_name}-${var.environment}-igw"
  })
}

resource "aws_eip" "nat" {
  count  = length(var.availability_zones)
  domain = "vpc"

  tags = merge(local.common_tags, {
    Name = "${var.project_name}-${var.environment}-nat-eip-${var.availability_zones[count.index]}"
  })

  depends_on = [aws_internet_gateway.main]
}

resource "aws_nat_gateway" "main" {
  count         = length(var.availability_zones)
  allocation_id = aws_eip.nat[count.index].id
  subnet_id     = aws_subnet.public[count.index].id

  tags = merge(local.common_tags, {
    Name = "${var.project_name}-${var.environment}-nat-${var.availability_zones[count.index]}"
  })

  depends_on = [aws_internet_gateway.main]
}

# modules/vpc/outputs.tf
output "vpc_id" {
  description = "VPC ID"
  value       = aws_vpc.main.id
}

output "public_subnet_ids" {
  description = "List of public subnet IDs"
  value       = aws_subnet.public[*].id
}

output "private_subnet_ids" {
  description = "List of private subnet IDs"
  value       = aws_subnet.private[*].id
}

output "nat_gateway_ips" {
  description = "List of NAT Gateway public IPs"
  value       = aws_eip.nat[*].public_ip
}

Expected: Module creates VPC with public/private subnets across multiple AZs, internet gateway, NAT gateways with EIPs. Output values expose resource IDs for downstream modules.

On failure: For CIDR overlap errors, adjust cidrsubnet() calculation or validate VPC CIDR doesn’t conflict with existing networks. For dependency errors, verify depends_on blocks ensure proper resource creation order. Use terraform graph | dot -Tpng > graph.png to visualize dependencies.

Step 3: Implement Environment-Specific Configurations

Create environment workspaces with variable overrides and data sources.

# environments/prod/main.tf
terraform {
  required_version = ">= 1.6"
}

# Import shared backend and provider config
# ... (see EXAMPLES.md for complete configuration)

Expected: Environment-specific configuration creates production-sized infrastructure with 3 AZs, larger instance types, and production security settings. Data sources resolve latest AMI. Template files render with environment variables.

On failure: For workspace errors, create workspace with terraform workspace new prod. For data source failures, verify AWS credentials have ec2:DescribeImages permissions. For template rendering errors, validate variable types match template expectations.

Step 4: Execute Plan and Apply Workflow

Run Terraform plan, review changes, and apply with approval workflow.

# Format code
terraform fmt -recursive

# Validate configuration
terraform validate

# ... (see EXAMPLES.md for complete configuration)

For automated CI/CD integration:

# .github/workflows/terraform.yml
name: Terraform

on:
  pull_request:
    paths:
# ... (see EXAMPLES.md for complete configuration)

Expected: Plan shows resource additions/changes/deletions. No drift detected. Apply creates/updates resources without errors. Outputs contain expected values. CI workflow comments plan on PRs, auto-applies on main branch merges.

On failure: For plan failures, run terraform validate to catch syntax errors. For state lock errors, identify lock holder with aws dynamodb get-item --table-name terraform-lock --key '{"LockID":{"S":"terraform-state-bucket/key"}}' and force-unlock if stale. For apply failures, check CloudWatch logs for provider-specific errors. Use terraform show to inspect current state.

Step 5: Manage State and Implement Drift Detection

Configure state locking, backup, and automated drift detection.

# Create DynamoDB table for state locking
cat > state-backend.tf <<'EOF'
resource "aws_dynamodb_table" "terraform_lock" {
  name           = "terraform-lock"
  billing_mode   = "PAY_PER_REQUEST"
  hash_key       = "LockID"
# ... (see EXAMPLES.md for complete configuration)

For automated drift detection:

# Create drift detection script
cat > scripts/detect-drift.sh <<'EOF'
#!/bin/bash
set -euo pipefail

cd terraform
# ... (see EXAMPLES.md for complete configuration)

Expected: State backend configured with versioning and encryption. Drift detection identifies out-of-band changes. State operations (list, show, mv, import) execute without errors. Automated drift checks run on schedule and send alerts.

On failure: For state lock timeouts, verify DynamoDB table exists and has correct key schema. For versioning issues, check S3 bucket versioning status with aws s3api get-bucket-versioning --bucket bucket-name. For import failures, verify resource exists and Terraform configuration matches actual resource attributes.

Step 6: Implement Module Testing and Documentation

Add automated tests with Terratest and generate documentation.

// test/vpc_test.go
package test

import (
    "testing"

# ... (see EXAMPLES.md for complete configuration)

Generate documentation:

# Install terraform-docs
go install github.com/terraform-docs/terraform-docs@latest

# Generate module documentation
terraform-docs markdown table modules/vpc > modules/vpc/README.md

# ... (see EXAMPLES.md for complete configuration)

Expected: Terratest validates module creates expected resources with correct configuration. Documentation auto-generates from variable descriptions and output definitions. Pre-commit hooks enforce formatting and validation before commits.

On failure: For Terratest failures, check AWS credentials and quotas. For long-running tests, implement parallel execution with t.Parallel(). For documentation generation errors, verify all variables have description attributes. For pre-commit failures, manually run terraform fmt and fix validation errors.

Validation

• Backend configured with encryption, versioning, and state locking
• All modules have input validation and output values
• Workspaces isolate environment-specific state
• terraform plan shows no unexpected changes after apply
• Drift detection runs automatically and alerts on changes
• Modules tested with Terratest or similar framework
• Documentation auto-generated and kept up-to-date
• Secrets managed via AWS Secrets Manager, not hardcoded
• Cost estimation integrated (Infracost or similar)
• Blast radius minimized with separate state per environment

Common Pitfalls

• Hardcoded values: Avoid hardcoding AMI IDs, AZs, or account-specific values. Use data sources and variables.

• Missing lifecycle blocks: Resources recreate unexpectedly. Add lifecycle { create_before_destroy = true } to prevent downtime during updates.

• No state locking: Concurrent applies corrupt state. Always use DynamoDB table for locking with S3 backend.

• Overly permissive IAM: Terraform service account has full admin access. Implement least-privilege policies scoped to managed resources.

• No version constraints: Provider updates break infrastructure. Pin provider versions with version = "~> 5.0" constraints.

• Secrets in state: Sensitive values stored in plaintext state file. Use sensitive = true on outputs, store secrets in AWS Secrets Manager, reference via data sources.

• No backup strategy: State file lost or corrupted with no recovery plan. Enable S3 versioning, implement regular state backups, test recovery procedures.

• Monolithic configuration: Single state file manages entire infrastructure. Split into logical boundaries (networking, compute, data) to reduce blast radius.

Related Skills

• configure-git-repository – Version control for Terraform code
• build-ci-cd-pipeline – Automated Terraform workflows with GitHub Actions
• implement-gitops-workflow – ArgoCD/Flux integration with Terraform
• manage-kubernetes-secrets – Secrets management in Terraform-provisioned clusters
• deploy-to-kubernetes – Terraform Kubernetes provider usage