terraform-patterns

name	terraform-patterns
description	Implement — Terraform infrastructure-as-code agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Covers module design patterns, state management strategies, provider c
license	MIT
metadata	{"version":"1.0.0","author":"Alireza Rezvani","category":"engineering","updated":"2026-03-15T00:00:00.000Z"}
executor	HYBRID
skill_id	engineering.cs-engineering.terraform-patterns
status	ADOPTED
security	{"level":"high","pii":false,"approval_required":true}
anchors	["engineering","infrastructure","llm","agent","design"]
tier	2
input_schema	[{"name":"code_or_task","type":"string","description":"Code snippet, script, or task description to process","required":true}]
output_schema	[{"name":"result","type":"string","description":"Generated or refactored code output"},{"name":"explanation","type":"string","description":"Explanation of changes or implementation decisions"}]

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

Command	What it does
/terraform:review	Analyze Terraform code for anti-patterns, security issues, and structure problems
/terraform:module	Design or refactor a Terraform module with proper inputs, outputs, and composition
/terraform:security	Audit 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

   Check	Severity	Fix
   Hardcoded secrets in .tf files	Critical	Use variables with sensitive = true or vault
   IAM policy with * actions	Critical	Scope to specific actions and resources
   Security group with 0.0.0.0/0 on port 22/3389	Critical	Restrict to known CIDR blocks or use SSM/bastion
   S3 bucket without encryption	High	Add server_side_encryption_configuration block
   S3 bucket with public access	High	Add aws_s3_bucket_public_access_block
   RDS without encryption	High	Set storage_encrypted = true
   RDS publicly accessible	High	Set publicly_accessible = false
   CloudTrail not enabled	Medium	Add aws_cloudtrail resource
   Missing prevent_destroy on stateful resources	Medium	Add lifecycle { prevent_destroy = true }
   Variables without sensitive = true for secrets	Medium	Add sensitive = true to secret variables

2. State security audit

   Check	Severity	Fix
   Local state file	Critical	Migrate to remote backend with encryption
   Remote state without encryption	High	Enable encryption on backend (SSE-S3, KMS)
   No state locking	High	Enable DynamoDB for S3, native for TF Cloud
   State accessible to all team members	Medium	Restrict 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.