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Terraform Patterns

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Streamline your Terraform infrastructure code with best practices.

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What Terraform Patterns does

Terraform Patterns is a skill designed to enhance your Terraform infrastructure-as-code practices by providing structured workflows and best practices for module design, state management, and security. This skill is particularly useful for developers and DevOps engineers who want to ensure their Terraform code is not only functional but also secure and maintainable. By leveraging this skill, users can transform sprawling HCL configurations into well-organized, production-ready code that adheres to industry standards.

The skill offers three primary commands: /terraform:review, /terraform:module, and /terraform:security. The review command analyzes existing Terraform code for anti-patterns and security vulnerabilities, ensuring that the codebase follows best practices for module structure and state management. The module command assists in designing or refactoring Terraform modules, focusing on proper inputs, outputs, and composition to promote reusability and clarity. The security command audits Terraform code for potential security issues, helping users to identify and remediate risks such as hardcoded secrets or overly permissive IAM policies.

This skill is not a tutorial; instead, it provides actionable insights and concrete decisions that developers can apply directly to their Terraform projects. It is ideal for teams looking to implement Infrastructure as Code (IaC) best practices and maintain a secure and efficient deployment process. By integrating this skill into your workflow, you can reduce the risk of errors and improve the overall quality of your infrastructure code, ultimately leading to more reliable deployments and a smoother development experience.

When to use it

Use this skill when you need to design Terraform modules, review existing code for best practices, or conduct security audits on your infrastructure code.

When not to use it

This skill may not be suitable for users who are unfamiliar with Terraform or those seeking a basic introduction to the tool, as it focuses on advanced practices and workflows.

What you can build with it

Reviewing Terraform Code

Use the `/terraform:review` command to analyze your existing Terraform code for best practices and security vulnerabilities.

Designing a New Module

Leverage the `/terraform:module` command to create a well-structured Terraform module with clear inputs and outputs.

Conducting a Security Audit

Run the `/terraform:security` command to identify and remediate security risks in your Terraform configurations.

How to install Terraform Patterns

View source

1. Install with the skills CLI

npx skills add alirezarezvani/claude-skills/terraform-patterns --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by alirezarezvani

Terraform Patterns

Predictable infrastructure. Secure state. Modules that compose. No drift.

Opinionated Terraform workflow that turns sprawling HCL into well-structured, secure, production-grade infrastructure code. Covers module design, state management, provider patterns, security hardening, and CI/CD integration.

Not a Terraform tutorial — a set of concrete decisions about how to write infrastructure code that doesn't break at 3 AM.


Slash Commands

CommandWhat it does
/terraform:reviewAnalyze Terraform code for anti-patterns, security issues, and structure problems
/terraform:moduleDesign or refactor a Terraform module with proper inputs, outputs, and composition
/terraform:securityAudit Terraform code for security vulnerabilities, secrets exposure, and IAM misconfigurations

When This Skill Activates

Recognize these patterns from the user:

  • "Review this Terraform code"
  • "Design a Terraform module for..."
  • "My Terraform state is..."
  • "Set up remote state backend"
  • "Multi-region Terraform deployment"
  • "Terraform security review"
  • "Module structure best practices"
  • "Terraform CI/CD pipeline"
  • Any request involving: .tf files, HCL, Terraform modules, state management, provider configuration, infrastructure-as-code

If the user has .tf files or wants to provision infrastructure with Terraform → this skill applies.


Workflow

/terraform:review — Terraform Code Review

  1. Analyze current state

    • Read all .tf files in the target directory
    • Identify module structure (flat vs nested)
    • Count resources, data sources, variables, outputs
    • Check naming conventions
  2. Apply review checklist

    MODULE STRUCTURE
    ├── Variables have descriptions and type constraints
    ├── Outputs expose only what consumers need
    ├── Resources use consistent naming: {provider}_{type}_{purpose}
    ├── Locals used for computed values and DRY expressions
    └── No hardcoded values — everything parameterized or in locals
    
    STATE & BACKEND
    ├── Remote backend configured (S3, GCS, Azure Blob, Terraform Cloud)
    ├── State locking enabled (DynamoDB for S3, native for others)
    ├── State encryption at rest enabled
    ├── No secrets stored in state (or state access is restricted)
    └── Workspaces or directory isolation for environments
    
    PROVIDERS
    ├── Version constraints use pessimistic operator: ~> 5.0
    ├── Required providers block in terraform {} block
    ├── Provider aliases for multi-region or multi-account
    └── No provider configuration in child modules
    
    SECURITY
    ├── No hardcoded secrets, keys, or passwords
    ├── IAM follows least-privilege principle
    ├── Encryption enabled for storage, databases, secrets
    ├── Security groups are not overly permissive (no 0.0.0.0/0 ingress on sensitive ports)
    └── Sensitive variables marked with sensitive = true
    
  3. Generate report

    python3 scripts/tf_module_analyzer.py ./terraform
    
  4. Run security scan

    python3 scripts/tf_security_scanner.py ./terraform
    

/terraform:module — Module Design

  1. Identify module scope

    • Single responsibility: one module = one logical grouping
    • Determine inputs (variables), outputs, and resource boundaries
    • Decide: flat module (single directory) vs nested (calling child modules)
  2. Apply module design checklist

    STRUCTURE
    ├── main.tf        — Primary resources
    ├── variables.tf   — All input variables with descriptions and types
    ├── outputs.tf     — All outputs with descriptions
    ├── versions.tf    — terraform {} block with required_providers
    ├── locals.tf      — Computed values and naming conventions
    ├── data.tf        — Data sources (if any)
    └── README.md      — Usage examples and variable documentation
    
    VARIABLES
    ├── Every variable has: description, type, validation (where applicable)
    ├── Sensitive values marked: sensitive = true
    ├── Defaults provided for optional settings
    ├── Use object types for related settings: variable "config" { type = object({...}) }
    └── Validate with: validation { condition = ... }
    
    OUTPUTS
    ├── Output IDs, ARNs, endpoints — things consumers need
    ├── Include description on every output
    ├── Mark sensitive outputs: sensitive = true
    └── Don't output entire resources — only specific attributes
    
    COMPOSITION
    ├── Root module calls child modules
    ├── Child modules never call other child modules
    ├── Pass values explicitly — no hidden data source lookups in child modules
    ├── Provider configuration only in root module
    └── Use module "name" { source = "./modules/name" }
    
  3. Generate module scaffold

    • Output file structure with boilerplate
    • Include variable validation blocks
    • Add lifecycle rules where appropriate

/terraform:security — Security Audit

  1. Code-level audit

    CheckSeverityFix
    Hardcoded secrets in .tf filesCriticalUse variables with sensitive = true or vault
    IAM policy with * actionsCriticalScope to specific actions and resources
    Security group with 0.0.0.0/0 on port 22/3389CriticalRestrict to known CIDR blocks or use SSM/bastion
    S3 bucket without encryptionHighAdd server_side_encryption_configuration block
    S3 bucket with public accessHighAdd aws_s3_bucket_public_access_block
    RDS without encryptionHighSet storage_encrypted = true
    RDS publicly accessibleHighSet publicly_accessible = false
    CloudTrail not enabledMediumAdd aws_cloudtrail resource
    Missing prevent_destroy on stateful resourcesMediumAdd lifecycle { prevent_destroy = true }
    Variables without sensitive = true for secretsMediumAdd sensitive = true to secret variables
  2. State security audit

    CheckSeverityFix
    Local state fileCriticalMigrate to remote backend with encryption
    Remote state without encryptionHighEnable encryption on backend (SSE-S3, KMS)
    No state lockingHighEnable DynamoDB for S3, native for TF Cloud
    State accessible to all team membersMediumRestrict via IAM policies or TF Cloud teams
  3. Generate security report

    python3 scripts/tf_security_scanner.py ./terraform
    python3 scripts/tf_security_scanner.py ./terraform --output json
    

Tooling

scripts/tf_module_analyzer.py

CLI utility for analyzing Terraform directory structure and module quality.

Features:

  • Resource and data source counting
  • Variable and output analysis (missing descriptions, types, validation)
  • Naming convention checks
  • Module composition detection
  • File structure validation
  • JSON and text output

Usage:

# Analyze a Terraform directory
python3 scripts/tf_module_analyzer.py ./terraform

# JSON output
python3 scripts/tf_module_analyzer.py ./terraform --output json

# Analyze a specific module
python3 scripts/tf_module_analyzer.py ./modules/vpc

scripts/tf_security_scanner.py

CLI utility for scanning .tf files for common security issues.

Features:

  • Hardcoded secret detection (AWS keys, passwords, tokens)
  • Overly permissive IAM policy detection
  • Open security group detection (0.0.0.0/0 on sensitive ports)
  • Missing encryption checks (S3, RDS, EBS)
  • Public access detection (S3, RDS, EC2)
  • Sensitive variable audit
  • JSON and text output

Usage:

# Scan a Terraform directory
python3 scripts/tf_security_scanner.py ./terraform

# JSON output
python3 scripts/tf_security_scanner.py ./terraform --output json

# Strict mode (elevate warnings)
python3 scripts/tf_security_scanner.py ./terraform --strict

Module Design Patterns

Pattern 1: Flat Module (Small/Medium Projects)

infrastructure/
├── main.tf          # All resources
├── variables.tf     # All inputs
├── outputs.tf       # All outputs
├── versions.tf      # Provider requirements
├── terraform.tfvars # Environment values (not committed)
└── backend.tf       # Remote state configuration

Best for: Single application, < 20 resources, one team owns everything.

Pattern 2: Nested Modules (Medium/Large Projects)

infrastructure/
├── environments/
│   ├── dev/
│   │   ├── main.tf          # Calls modules with dev params
│   │   ├── backend.tf       # Dev state backend
│   │   └── terraform.tfvars
│   ├── staging/
│   │   └── ...
│   └── prod/
│       └── ...
├── modules/
│   ├── networking/
│   │   ├── main.tf
│   │   ├── variables.tf
│   │   └── outputs.tf
│   ├── compute/
│   │   └── ...
│   └── database/
│       └── ...
└── versions.tf

Best for: Multiple environments, shared infrastructure patterns, team collaboration.

Pattern 3: Mono-Repo with Terragrunt

infrastructure/
├── terragrunt.hcl           # Root config
├── modules/                  # Reusable modules
│   ├── vpc/
│   ├── eks/
│   └── rds/
├── dev/
│   ├── terragrunt.hcl       # Dev overrides
│   ├── vpc/
│   │   └── terragrunt.hcl   # Module invocation
│   └── eks/
│       └── terragrunt.hcl
└── prod/
    ├── terragrunt.hcl
    └── ...

Best for: Large-scale, many environments, DRY configuration, team-level isolation.


Provider Configuration Patterns

Version Pinning

terraform {
  required_version = ">= 1.5.0"

  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"    # Allow 5.x, block 6.0
    }
    random = {
      source  = "hashicorp/random"
      version = "~> 3.5"
    }
  }
}

Multi-Region with Aliases

provider "aws" {
  region = "us-east-1"
}

provider "aws" {
  alias  = "west"
  region = "us-west-2"
}

resource "aws_s3_bucket" "primary" {
  bucket = "my-app-primary"
}

resource "aws_s3_bucket" "replica" {
  provider = aws.west
  bucket   = "my-app-replica"
}

Multi-Account with Assume Role

provider "aws" {
  alias  = "production"
  region = "us-east-1"

  assume_role {
    role_arn = "arn:aws:iam::PROD_ACCOUNT_ID:role/TerraformRole"
  }
}

State Management Decision Tree

Single developer, small project?
├── Yes → Local state (but migrate to remote ASAP)
└── No
    ├── Using Terraform Cloud/Enterprise?
    │   └── Yes → TF Cloud native backend (built-in locking, encryption, RBAC)
    └── No
        ├── AWS?
        │   └── S3 + DynamoDB (encryption, locking, versioning)
        ├── GCP?
        │   └── GCS bucket (native locking, encryption)
        ├── Azure?
        │   └── Azure Blob Storage (native locking, encryption)
        └── Other?
            └── Consul or PostgreSQL backend

Environment isolation strategy:
├── Separate state files per environment (recommended)
│   ├── Option A: Separate directories (dev/, staging/, prod/)
│   └── Option B: Terraform workspaces (simpler but less isolation)
└── Single state file for all environments (never do this)

CI/CD Integration Patterns

GitHub Actions Plan/Apply

# .github/workflows/terraform.yml
name: Terraform
on:
  pull_request:
    paths: ['terraform/**']
  push:
    branches: [main]
    paths: ['terraform/**']

jobs:
  plan:
    runs-on: ubuntu-latest
    if: github.event_name == 'pull_request'
    steps:
      - uses: actions/checkout@v4
      - uses: hashicorp/setup-terraform@v3
      - run: terraform init
      - run: terraform validate
      - run: terraform plan -out=tfplan
      - run: terraform show -json tfplan > plan.json
      # Post plan as PR comment

  apply:
    runs-on: ubuntu-latest
    if: github.ref == 'refs/heads/main' && github.event_name == 'push'
    environment: production
    steps:
      - uses: actions/checkout@v4
      - uses: hashicorp/setup-terraform@v3
      - run: terraform init
      - run: terraform apply -auto-approve

Drift Detection

# Run on schedule to detect drift
name: Drift Detection
on:
  schedule:
    - cron: '0 6 * * 1-5'  # Weekdays at 6 AM

jobs:
  detect:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: hashicorp/setup-terraform@v3
      - run: terraform init
      - run: |
          terraform plan -detailed-exitcode -out=drift.tfplan 2>&1 | tee drift.log
          EXIT_CODE=$?
          if [ $EXIT_CODE -eq 2 ]; then
            echo "DRIFT DETECTED — review drift.log"
            # Send alert (Slack, PagerDuty, etc.)
          fi

Proactive Triggers

Flag these without being asked:

  • No remote backend configured → Migrate to S3/GCS/Azure Blob with locking and encryption.
  • Provider without version constraint → Add version = "~> X.0" to prevent breaking upgrades.
  • Hardcoded secrets in .tf files → Use variables with sensitive = true, or integrate Vault/SSM.
  • IAM policy with "Action": "*" → Scope to specific actions. No wildcard actions in production.
  • Security group open to 0.0.0.0/0 on SSH/RDP → Restrict to bastion CIDR or use SSM Session Manager.
  • No state locking → Enable DynamoDB table for S3 backend, or use TF Cloud.
  • Resources without tags → Add default_tags in provider block. Tags are mandatory for cost tracking.
  • Missing prevent_destroy on databases/storage → Add lifecycle block to prevent accidental deletion.

Multi-Cloud Provider Configuration

When a single root module must provision across AWS, Azure, and GCP simultaneously.

Provider Aliasing Pattern

terraform {
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "~> 3.0"
    }
    google = {
      source  = "hashicorp/google"
      version = "~> 5.0"
    }
  }
}

provider "aws" {
  region = var.aws_region
}

provider "azurerm" {
  features {}
  subscription_id = var.azure_subscription_id
}

provider "google" {
  project = var.gcp_project_id
  region  = var.gcp_region
}

Shared Variables Across Providers

variable "environment" {
  description = "Environment name used across all providers"
  type        = string
  validation {
    condition     = contains(["dev", "staging", "prod"], var.environment)
    error_message = "Must be dev, staging, or prod."
  }
}

locals {
  common_tags = {
    environment = var.environment
    managed_by  = "terraform"
    project     = var.project_name
  }
}

When to Use Multi-Cloud

  • Yes: Regulatory requirements mandate data residency across providers, or the org has existing workloads on multiple clouds.
  • No: "Avoiding vendor lock-in" alone is not sufficient justification. Multi-cloud doubles operational complexity. Prefer single-cloud unless there is a concrete business requirement.

OpenTofu Compatibility

OpenTofu is an open-source fork of Terraform maintained by the Linux Foundation under the MPL 2.0 license.

Migration from Terraform to OpenTofu

# 1. Install OpenTofu
brew install opentofu        # macOS
snap install --classic tofu  # Linux

# 2. Replace the binary — state files are compatible
tofu init                    # Re-initializes with OpenTofu
tofu plan                    # Identical plan output
tofu apply                   # Same apply workflow

License Considerations

Terraform (1.6+)OpenTofu
LicenseBSL 1.1 (source-available)MPL 2.0 (open-source)
Commercial useRestricted for competing productsUnrestricted
Community governanceHashiCorpLinux Foundation

Feature Parity

OpenTofu tracks Terraform 1.6.x features. Key additions unique to OpenTofu:

  • Client-side state encryption (tofu init -encryption)
  • Early variable/locals evaluation
  • Provider-defined functions

When to Choose OpenTofu

  • You need a fully open-source license for your supply chain.
  • You want client-side state encryption without Terraform Cloud.
  • Otherwise, either tool works — the HCL syntax and provider ecosystem are identical.

Infracost Integration

Infracost estimates cloud costs from Terraform code before resources are provisioned.

PR Workflow

# Show cost breakdown for current code
infracost breakdown --path .

# Compare cost difference between current branch and main
infracost diff --path . --compare-to infracost-base.json

GitHub Actions Cost Comment

# .github/workflows/infracost.yml
name: Infracost
on: [pull_request]

jobs:
  cost:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: infracost/actions/setup@v3
        with:
          api-key: ${{ secrets.INFRACOST_API_KEY }}
      - run: infracost breakdown --path ./terraform --format json --out-file /tmp/infracost.json
      - run: infracost comment github --path /tmp/infracost.json --repo $GITHUB_REPOSITORY --pull-request ${{ github.event.pull_request.number }} --github-token ${{ secrets.GITHUB_TOKEN }} --behavior update

Budget Thresholds and Cost Policy

# infracost.yml — policy file
version: 2.9.0
policies:
  - path: "*"
    max_monthly_cost: "5000"    # Fail PR if estimated cost exceeds $5,000/month
    max_cost_increase: "500"    # Fail PR if cost increase exceeds $500/month

Import Existing Infrastructure

Bring manually-created resources under Terraform management.

terraform import Workflow

# 1. Write the resource block first (empty body is fine)
# main.tf:
# resource "aws_s3_bucket" "legacy" {}

# 2. Import the resource into state
terraform import aws_s3_bucket.legacy my-existing-bucket-name

# 3. Run plan to see attribute diff
terraform plan

# 4. Fill in the resource block until plan shows no changes

Bulk Import with Config Generation (Terraform 1.5+)

# Generate HCL for imported resources
terraform plan -generate-config-out=generated.tf

# Review generated.tf, then move resources into proper files

Common Pitfalls

  • Resource drift after import: The imported resource may have attributes Terraform does not manage. Run terraform plan immediately and resolve every diff.
  • State manipulation: Use terraform state mv to rename or reorganize. Use terraform state rm to remove without destroying. Always back up state before manipulation: terraform state pull > backup.tfstate.
  • Sensitive defaults: Imported resources may expose secrets in state. Restrict state access and enable encryption.

Terragrunt Patterns

Terragrunt is a thin wrapper around Terraform that provides DRY configuration for multi-environment setups.

Root terragrunt.hcl (Shared Config)

# terragrunt.hcl (root)
remote_state {
  backend = "s3"
  generate = {
    path      = "backend.tf"
    if_exists = "overwrite_terragrunt"
  }
  config = {
    bucket         = "my-org-terraform-state"
    key            = "${path_relative_to_include()}/terraform.tfstate"
    region         = "us-east-1"
    encrypt        = true
    dynamodb_table = "terraform-locks"
  }
}

Child terragrunt.hcl (Environment Override)

# prod/vpc/terragrunt.hcl
include "root" {
  path = find_in_parent_folders()
}

terraform {
  source = "../../modules/vpc"
}

inputs = {
  environment = "prod"
  cidr_block  = "10.0.0.0/16"
}

Dependencies Between Modules

# prod/eks/terragrunt.hcl
dependency "vpc" {
  config_path = "../vpc"
}

inputs = {
  vpc_id     = dependency.vpc.outputs.vpc_id
  subnet_ids = dependency.vpc.outputs.private_subnet_ids
}

When Terragrunt Adds Value

  • Yes: 3+ environments with identical module structure, shared backend config, or cross-module dependencies.
  • No: Single environment, small team, or simple directory-based isolation already works. Terragrunt adds a learning curve and another binary to manage.

Installation

One-liner (any tool)

git clone https://github.com/alirezarezvani/claude-skills.git
cp -r claude-skills/engineering/terraform-patterns ~/.claude/skills/

Multi-tool install

./scripts/convert.sh --skill terraform-patterns --tool codex|gemini|cursor|windsurf|openclaw

OpenClaw

clawhub install terraform-patterns

Related Skills

  • senior-devops — Broader DevOps scope (CI/CD, monitoring, containerization). Complementary — use terraform-patterns for IaC-specific work, senior-devops for pipeline and infrastructure operations.
  • aws-solution-architect — AWS architecture design. Complementary — terraform-patterns implements the infrastructure, aws-solution-architect designs it.
  • senior-security — Application security. Complementary — terraform-patterns covers infrastructure security posture, senior-security covers application-level threats.
  • ci-cd-pipeline-builder — Pipeline construction. Complementary — terraform-patterns defines infrastructure, ci-cd-pipeline-builder automates deployment.

Frequently asked questions about Terraform Patterns

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