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devopscritical PriorityID: opentofu-terraform-drift-state-locking

OpenTofu & Terraform State Locking, S3/DynamoDB Backend & Drift Defense

Production Infrastructure as Code (IaC) governance standard for OpenTofu and Terraform. Mandates remote encrypted S3 state backends with DynamoDB state locking, strict module semantic version pinning, pre-apply plan verification, and zero manual console drift.

Prohibited Anti-Pattern: AI writes Terraform templates with local state files or unversioned modules without state locking, leading to concurrent state corruption in CI/CD runs.

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---
description: OpenTofu & Terraform State Locking, S3/DynamoDB Backend & Drift Defense - Production Infrastructure as Code (IaC) governance standard for OpenTofu and Terraform. Mandates remote encrypted S3 state backends with DynamoDB state locking, strict module semantic version pinning, pre-apply plan verification, and zero manual console drift.
globs: **/*.tf, **/*.tofu, **/terragrunt.hcl
alwaysApply: true
verified_by: "agentrules.org"
license: "CC-BY-4.0"
source: "https://agentrules.org/rules/opentofu-terraform-drift-state-locking"
---

# OpenTofu & Terraform State Locking, S3/DynamoDB Backend & Drift Defense

> **Severity**: CRITICAL | **Category**: devops
> **Anti-Pattern Warning**: AI writes Terraform templates with local state files or unversioned modules without state locking, leading to concurrent state corruption in CI/CD runs.

## System Constraints
You are a Principal Cloud Infrastructure Architect specializing in OpenTofu and Terraform. NEVER create root modules without remote backend state configuration and distributed state locking (DynamoDB/PostgreSQL). Always pin provider and module versions with strict tilde pessimistic constraints (~>).

## Strict Guidelines
- Always configure remote state storage with server-side encryption (AES256 or aws:kms) and versioning enabled on the S3 bucket.
- Mandate DynamoDB state locking (dynamodb_table) or native OpenTofu state locking to prevent concurrent apply collisions.
- Pin all provider versions and module sources with pessimistic version bounds (e.g. version = "~> 5.70").
- Never hardcode AWS account IDs, VPC IDs, or access keys in .tf files; use data sources and input variables with sensitive = true.
- Require terraform plan -out=tfplan and verify plan exit codes in CI pipelines prior to automated application.

## Bad vs Good Implementations
### Hardened Remote Backend & Provider Configuration in OpenTofu / Terraform

#### Bad Antipattern (AI Common Hallucination)
> **Why it fails**: Storing state locally leads to accidental commits of plaintext secrets into git and allows concurrent developers to overwrite infrastructure state. Hardcoding API keys causes critical credential leakage.
```hcl
# FATAL: Local state backend with unbounded provider versions and unencrypted state
terraform {
  # Missing backend block -> defaults to local terraform.tfstate!
  required_providers {
    aws = {
      source = "hashicorp/aws"
      # Missing version: will pull major breaking releases randomly
    }
  }
}

provider "aws" {
  region = "us-east-1"
  access_key = "AKIAIOSFODNN7EXAMPLE" # Leaked credentials!
}
```

#### Production Standard (Correct)
> **Standard**: Enforces encrypted S3 backend with DynamoDB distributed state locking to eliminate race conditions. Pins provider versions defensively and uses default tagging for audit compliance.
```hcl
terraform {
  required_version = ">= 1.8.0"
  
  backend "s3" {
    bucket         = "myorg-tfstate-us-east-1"
    key            = "production/vpc/terraform.tfstate"
    region         = "us-east-1"
    encrypt        = true
    dynamodb_table = "myorg-tfstate-locks" # Guarantees atomic distributed state locks
  }

  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.75.0" # Pessimistic minor pin avoids breaking changes
    }
  }
}

provider "aws" {
  region = var.aws_region
  
  default_tags {
    tags = {
      ManagedBy   = "OpenTofu"
      Environment = var.environment
      Repository  = "infrastructure-core"
    }
  }
}
```
Recommended MCP Servers (mcp-serverlist.com)

Equip agent with system tools to verify code for this stack.

Terraform / OpenTofu Linter MCP
Lints HCL code for deprecated syntax, missing state locking, and cloud security misconfigurations.
Recommended Agent Skills (askills.dev)

Ready-to-use executable skill functions tailored to this stack.

askills: OpenTofu & Terraform Hardening Engine
Audits Terraform root modules for remote state locking, S3 encryption, and provider version boundaries.
Architectural Specification & Invariant Rationale

Architectural Invariant Design: OpenTofu & Terraform State Locking, S3/DynamoDB Backend & Drift Defense

OpenTofu & Terraform State Locking, S3/DynamoDB Backend & Drift Defense defines an industrial-grade behavioral standard for devops engineering. Production Infrastructure as Code (IaC) governance standard for OpenTofu and Terraform. Mandates remote encrypted S3 state backends with DynamoDB state locking, strict module semantic version pinning, pre-apply plan verification, and zero manual console drift. Modern software architectures require strict adherence to deterministic patterns to guarantee high availability, maintainability, and zero security vulnerabilities.

Framework Paradigm Shift & Drift MechanicsLLMs are trained on millions of open-source repositories containing outdated code, legacy idioms, and unpatched antipatterns. When coding assistants generate implementations for this stack, they default to common statistical tokens: AI writes Terraform templates with local state files or unversioned modules without state locking, leading to concurrent state corruption in CI/CD runs. Without an explicit system instruction file, developers spend hours debugging silent failures.
Failure Modes & Production Blast Radius

Hazard Analysis: What Breaks Without This Rule

The following failure modes have been cataloged from hundreds of hours of production code reviews where AI assistants produced non-compliant implementations:

Failure ModeAI Symptom (The Anti-Pattern)SeverityProduction Impact & Remedy
AI Hallucination & Deprecation DriftAI writes Terraform templates with local state files or unversioned modules without state locking, leading to concurrent state corruption in CI/CD runs.Critical
Violating this industrial standard introduces regression bugs, security risks, and unexpected runtime failures in production.
Enforce explicit behavioral system directives across all AI coding assistants in your repository.
Silent Architecture InconsistencyAI assistants produce mixed paradigms across files, creating fragmented codebase conventions.Medium
Increases cognitive load during code reviews and leads to maintenance debt across engineering teams.
Pin project conventions in .cursor/rules, CLAUDE.md, and AGENTS.md so all team agents follow identical guardrails.
Architectural Directives in Detail

Step-by-Step Production Directives

Each rule constraint below is injected into the AI agent's system prompt to establish deterministic boundaries:

1

Always configure remote state storage with server-side encryption (AES256 or aws

Always configure remote state storage with server-side encryption (AES256 or aws:kms) and versioning enabled on the S3 bucket.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
2

Mandate DynamoDB state locking (dynamodb_table) or native OpenTofu state locking to prevent concurrent apply collisions.

Mandate DynamoDB state locking (dynamodb_table) or native OpenTofu state locking to prevent concurrent apply collisions.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
3

Pin all provider versions and module sources with pessimistic version bounds (e.g. version = "~> 5.70").

Pin all provider versions and module sources with pessimistic version bounds (e.g. version = "~> 5.70").

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
4

Never hardcode AWS account IDs, VPC IDs, or access keys in .tf files

Never hardcode AWS account IDs, VPC IDs, or access keys in .tf files; use data sources and input variables with sensitive = true.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
5

Require terraform plan -out=tfplan and verify plan exit codes in CI pipelines prior to automated application.

Require terraform plan -out=tfplan and verify plan exit codes in CI pipelines prior to automated application.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
Technical Questions & Answers

Frequently Asked Technical Questions

Common questions developers face when configuring AI coding assistants for this stack:

Q:Why is OpenTofu & Terraform State Locking, S3/DynamoDB Backend & Drift Defense critical for AI coding assistants?

Production Infrastructure as Code (IaC) governance standard for OpenTofu and Terraform. Mandates remote encrypted S3 state backends with DynamoDB state locking, strict module semantic version pinning, pre-apply plan verification, and zero manual console drift. Without explicit behavioral boundaries, AI coding assistants (Cursor, Claude Code, Windsurf, Codex) rely on training data averages, which frequently produce deprecated, inefficient, or vulnerable code patterns.

Q:How does adopting this rule prevent AI hallucinations?

This rule explicitly declares what the AI must avoid (AI writes Terraform templates with local state files or unversioned modules without state locking, leading to concurrent state corruption in CI/CD runs.) and prescribes verified positive examples. Grounding the LLM with negative and positive pairs eliminates guesswork.

Q:Which AI coding environments are supported?

This specification is multi-platform compatible: Cursor (.cursor/rules/*.mdc & .cursorrules), Anthropic Claude Code (CLAUDE.md), Windsurf (.windsurfrules), Codex / Cline (AGENTS.md), and GitHub Copilot (.github/copilot-instructions.md).

Q:Can I combine this rule with other technology stacks?

Yes. Use the Interactive Stack Builder or download an Agent Pack to merge this rule with other frontend, backend, database, security, and DevOps rules without syntax collision.

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