Table of Contents

Introduction

Automate your Terraform CI/CD pipelines with OpenClaw AI — from plan review to apply approval and drift detection in GitLab and GitHub Actions. This guide covers practical techniques and real-world examples for integrating OpenClaw AI into your Terraform workflow.

Why Use OpenClaw for This?

Traditional Terraform workflows require deep expertise and manual effort. OpenClaw AI brings:

  • Contextual understanding of your infrastructure code
  • Automated analysis that catches issues humans might miss
  • Natural language interaction — describe what you need, get results
  • Continuous learning from best practices across thousands of Terraform projects

Getting Started

Prerequisites

  • Terraform >= 1.5 installed
  • OpenClaw installed and running (openclaw status)
  • A Terraform project to work with

Basic Setup

# Ensure OpenClaw is running
openclaw gateway start

# Navigate to your Terraform project
cd /path/to/terraform-project

# OpenClaw automatically detects your Terraform configuration

Practical Examples

Example 1: Quick Analysis

Ask OpenClaw to analyze your current configuration:

"Review my Terraform code for best practices and security issues"

OpenClaw will scan your .tf files and provide actionable feedback on:

  • Security misconfigurations
  • Missing tags and metadata
  • Resource sizing recommendations
  • State management improvements

Example 2: Automated Operations

OpenClaw can execute Terraform operations with safety checks:

# OpenClaw runs plan, shows changes, asks for confirmation
terraform plan -out=tfplan

# Review the plan output with AI explanation
terraform show tfplan

Example 3: Configuration Generation

Describe what you need:

"Add monitoring and alerting for all EC2 instances in my configuration"

OpenClaw generates CloudWatch alarms, SNS topics, and dashboard configurations that integrate with your existing resources.

Advanced Usage

Integration with CI/CD

OpenClaw integrates with popular CI/CD platforms:

# .gitlab-ci.yml example
terraform_review:
  stage: review
  script:
    - terraform init
    - terraform plan -out=tfplan
    - terraform show -json tfplan > plan.json
  artifacts:
    paths:
      - plan.json

Team Collaboration

When working in teams, OpenClaw helps maintain consistency by:

  • Enforcing naming conventions across modules
  • Ensuring variable descriptions are present
  • Validating output definitions match documentation
  • Checking for duplicate or conflicting resources

Best Practices

  1. Always review AI suggestions before applying to production
  2. Use version control for all Terraform changes
  3. Test in lower environments before promoting to production
  4. Document decisions — OpenClaw can generate commit messages and PR descriptions
  5. Keep modules small and focused on single responsibilities
  6. Use remote state with proper locking for team environments

Common Pitfalls to Avoid

  • Blindly applying AI suggestions without understanding the changes
  • Skipping plan review even when OpenClaw generates the code
  • Ignoring state management when working across environments
  • Not tagging resources — OpenClaw can add tags automatically but needs your standards

Conclusion

OpenClaw AI transforms how you work with Terraform by handling the repetitive, error-prone aspects of infrastructure management while keeping you in control of critical decisions. Whether you’re managing a small project or enterprise-scale infrastructure, the combination of Terraform’s declarative approach and OpenClaw’s AI assistance delivers faster, more reliable infrastructure deployments.