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terraform-style-guide

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Generate Terraform HCL code following HashiCorp's official style conventions and best practices. Use when writing, reviewing, or generating Terraform configurations.

SKILL.md

Terraform Style Guide

Generate and maintain Terraform code following HashiCorp's official style conventions and best practices.

Reference: HashiCorp Terraform Style Guide

Code Generation Strategy

When generating Terraform code:

  1. Start with provider configuration and version constraints
  2. Create data sources before dependent resources
  3. Build resources in dependency order
  4. Add outputs for key resource attributes
  5. Use variables for all configurable values

File Organization

File Purpose
terraform.tf Terraform and provider version requirements
providers.tf Provider configurations
main.tf Primary resources and data sources
variables.tf Input variable declarations (alphabetical)
outputs.tf Output value declarations (alphabetical)
locals.tf Local value declarations

Example Structure

# terraform.tf
terraform {
  required_version = ">= 1.14"

  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 6.0"
    }
  }
}

# variables.tf
variable "environment" {
  description = "Target deployment environment"
  type        = string

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

# locals.tf
locals {
  common_tags = {
    Environment = var.environment
    ManagedBy   = "Terraform"
  }
}

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

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

# outputs.tf
output "vpc_id" {
  description = "ID of the created VPC"
  value       = aws_vpc.main.id
}

Code Formatting

Indentation and Alignment

  • Use two spaces per nesting level (no tabs)
  • Align equals signs for consecutive arguments
resource "aws_instance" "web" {
  ami           = "ami-0c55b159cbfafe1f0"
  instance_type = "t2.micro"
  subnet_id     = "subnet-12345678"

  tags = {
    Name        = "web-server"
    Environment = "production"
  }
}

Block Organization

Arguments precede blocks, with meta-arguments first:

resource "aws_instance" "example" {
  # Meta-arguments
  count = 3

  # Arguments
  ami           = "ami-0c55b159cbfafe1f0"
  instance_type = "t2.micro"

  # Blocks
  root_block_device {
    volume_size = 20
  }

  # Lifecycle last
  lifecycle {
    create_before_destroy = true
  }
}

Naming Conventions

  • Use lowercase with underscores for all names
  • Use descriptive nouns excluding the resource type
  • Be specific and meaningful
  • Resource names must be singular, not plural
  • Default to main for resources where a specific descriptive name is redundant or unavailable, provided only one instance exists
# Bad
resource "aws_instance" "webAPI-aws-instance" {}
resource "aws_instance" "web_apis" {}
variable "name" {}

# Good
resource "aws_instance" "web_api" {}
resource "aws_vpc" "main" {}
variable "application_name" {}

Variables

Every variable must include type and description:

variable "instance_type" {
  description = "EC2 instance type for the web server"
  type        = string
  default     = "t2.micro"

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

variable "database_password" {
  description = "Password for the database admin user"
  type        = string
  sensitive   = true
}

Outputs

Every output must include description:

output "instance_id" {
  description = "ID of the EC2 instance"
  value       = aws_instance.web.id
}

output "database_password" {
  description = "Database administrator password"
  value       = aws_db_instance.main.password
  sensitive   = true
}

Dynamic Resource Creation

Prefer for_each over count

# Bad - count for multiple resources
resource "aws_instance" "web" {
  count = var.instance_count
  tags  = { Name = "web-${count.index}" }
}

# Good - for_each with named instances
variable "instance_names" {
  type    = set(string)
  default = ["web-1", "web-2", "web-3"]
}

resource "aws_instance" "web" {
  for_each = var.instance_names
  tags     = { Name = each.key }
}

count for Conditional Creation

resource "aws_cloudwatch_metric_alarm" "cpu" {
  count = var.enable_monitoring ? 1 : 0

  alarm_name = "high-cpu-usage"
  threshold  = 80
}

Security Best Practices

Refer to SECURITY.md. It includes guidance on encrypting resources, preventing sensitive data in state, and secure configurations.

Version Pinning

terraform {
  required_version = ">= 1.14"

  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 6.0"
    }
  }
}

Use the latest major version of each provider and the latest minor version of Terraform, unless otherwise constrained by a dependency lock file or by other modules used by the configuration.

Version constraint operators:

  • = 1.0.0 - Exact version
  • >= 1.0.0 - Greater than or equal
  • ~> 1.0 - Allow rightmost component to increment
  • >= 1.0, < 2.0 - Version range

Provider Configuration

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

  default_tags {
    tags = {
      ManagedBy = "Terraform"
      Project   = var.project_name
    }
  }
}

# Aliased provider for multi-region
provider "aws" {
  alias  = "east"
  region = "us-east-1"
}

Version Control

Never commit:

  • terraform.tfstate, terraform.tfstate.backup
  • .terraform/ directory
  • *.tfplan
  • .tfvars files with sensitive data

Always commit:

  • All .tf configuration files
  • .terraform.lock.hcl (dependency lock file)

Validation Tools

Run before committing:

terraform fmt -recursive
terraform validate

Additional tools:

  • tflint - Linting and best practices
  • checkov / tfsec - Security scanning

Code Review Checklist

  • Code formatted with terraform fmt
  • Configuration validated with terraform validate
  • Files organized according to standard structure
  • All variables have type and description
  • All outputs have descriptions
  • Resource names use descriptive nouns with underscores
  • Version constraints pinned explicitly
  • Sensitive values marked with sensitive = true
  • No hardcoded credentials or secrets
  • Security best practices applied

Based on: HashiCorp Terraform Style Guide

SKILL.md

SKILL.md holds the skill's instructions; it is edited on the Instructions tab.

SECURITY.md

name: terraform-style-guide-security
description: Generate Terraform HCL code following HashiCorp's security practices

Terraform Style Guide - Security

When generating code, apply security hardening:

  • Enable encryption at rest by default
  • Configure private networking where applicable
  • Apply principle of least privilege for security groups
  • Enable logging and monitoring
  • Never hardcode credentials or secrets
  • Mark sensitive outputs with sensitive = true
  • Use ephemeral resources and write-only attributes for sensitive data when possible

Example: Secure S3 Bucket

resource "aws_s3_bucket" "data" {
  bucket = "${var.project}-${var.environment}-data"
  tags   = local.common_tags
}

resource "aws_s3_bucket_versioning" "data" {
  bucket = aws_s3_bucket.data.id

  versioning_configuration {
    status = "Enabled"
  }
}

resource "aws_s3_bucket_server_side_encryption_configuration" "data" {
  bucket = aws_s3_bucket.data.id

  rule {
    apply_server_side_encryption_by_default {
      sse_algorithm     = "aws:kms"
      kms_master_key_id = aws_kms_key.s3.arn
    }
  }
}

resource "aws_s3_bucket_public_access_block" "data" {
  bucket = aws_s3_bucket.data.id

  block_public_acls       = true
  block_public_policy     = true
  ignore_public_acls      = true
  restrict_public_buckets = true
}

Ephemeral resources

Ephemeral resources prevent sensitive data being stored in state. For more information on ephemeral resources, see the Terraform documentation.

Before you generate code for an ephemeral resource, check that the Terraform version is greater than or equal to 1.11.0.

Then, follow this priority order for managing sensitive attributes:

  1. First priority: Native secrets manager integration If a resource has the ability to automatically manage a sensitive attribute by storing it in a secrets manager (e.g., AWS Secrets Manager, Azure Key Vault), use that configuration. This is the preferred approach.

    # Bad
    resource "aws_rds_cluster" "example" {
      cluster_identifier = "example"
      database_name      = "test"
      master_username    = "test"
      master_password    = var.db_master_password
    }
    
    # Good, managed by AWS Secrets Manager by default
    resource "aws_rds_cluster" "test" {
      cluster_identifier          = "example"
      database_name               = "test"
      manage_master_user_password = true
      master_username             = "test"
    }
  2. Second priority: Write-only attributes with ephemeral resources If a resource has a write-only attribute but no native secrets manager integration, use an ephemeral resource for the sensitive data and pass that to the write-only attribute. Default the write-only version to 1.

    # Bad
    resource "random_password" "password" {
      length           = 16
      special          = true
      override_special = "!#$%&*()-_=+[]{}<>:?"
    }
    
    resource "vault_kv_secret_v2" "example" {
      mount               = vault_mount.kvv2.path
      name                = "secret"
    
      data_json = jsonencode(
        {
          password = "${random_password.password.result}",
        }
      )
    }
    
    # Good
    ephemeral "random_password" "password" {
      length           = 16
      special          = true
      override_special = "!#$%&*()-_=+[]{}<>:?"
    }
    
    resource "vault_kv_secret_v2" "example" {
      mount               = vault_mount.kvv2.path
      name                = "secret"
    
      data_json_wo = jsonencode(
        {
          password = "${ephemeral.random_password.password.result}",
        }
      )
      data_json_wo_version = 1
    }

    If you need to retrieve a secret from a secrets manager to pass to a resource, use the ephemeral version of the resource to retrieve the secret and pass it to another resource.

    # Good
    ephemeral "vault_kv_secret_v2" "db_secret" {
      mount = vault_mount.kvv2.path
      mount_id = vault_mount.kvv2.id
      name = vault_kv_secret_v2.db_root.name
    }
    
    resource "vault_database_secret_backend_connection" "postgres" {
      backend       = vault_mount.db.path
      name          = "postrgres-db"
      allowed_roles = ["*"]
    
      postgresql {
        connection_url = "postgresql://{{username}}:{{password}}@localhost:5432/postgres"
        password_authentication = ""
        username = "postgres"
        password_wo = tostring(ephemeral.vault_kv_secret_v2.db_secret.data.password)
        password_wo_version = 1
      }
    }
  3. Last resort: Regular resources Only use a regular resource that has sensitive data written to state if neither of the above options are available, resource does not offer a write-only attribute or ephemeral resource alternative, or the Terraform version is less than 1.11.0.

Frontmatter written into each target's SKILL.md.

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