GitOps Beyond Kubernetes: Applying GitOps Principles to Infrastructure as Code

A growing number of DevOps teams now use GitOps practices for Kubernetes deployments, treating Git repositories as the single source of truth for application configuration. These teams enjoy automated deployments, clear audit trails, and enforced change approval processes through pull requests. Yet many of these same organizations still manage their core infrastructure through manual Terraform operations, creating a disconnect in their delivery workflows.

This fragmented approach leads to real operational problems. Infrastructure changes often drift from their documented state when engineers apply manual updates. Environment inconsistencies appear when different team members run Terraform with varying parameters. Knowledge becomes siloed when only certain individuals understand the correct sequence for infrastructure modifications.

Extending GitOps principles to Terraform-managed infrastructure resolves these challenges by bringing the same declarative, Git-centric practices to your foundational resources. By implementing GitOps workflows for infrastructure code, teams gain consistent deployment patterns across both applications and the platforms they run on.

In this article, we'll explore practical implementation patterns for GitOps with Terraform, examine key tooling options, and address common challenges when transitioning to fully automated infrastructure workflows.

GitOps Principles Applied to Infrastructure

Terraform's declarative language (HCL) is a natural fit for GitOps. Unlike imperative scripts that define step-by-step resource creation, Terraform configurations specify the target state, letting the tool determine the necessary operations to reach that state.

When teams store Terraform configurations in Git repositories, they create a version-controlled record of infrastructure changes. Engineers submit pull requests against these repositories instead of applying changes directly, enabling standardized review processes for infrastructure modifications.

A common integration is embedding Terraform plan outputs in pull request comments. This approach lets reviewers see the specific resources that will change before approving the PR:

Plan: 2 to add, 1 to change, 1 to destroy.

+ aws_security_group.allow_internal
+ aws_security_group_rule.ingress_api
~ aws_iam_role.api_execution_role
- aws_s3_bucket_policy.logs

This setup lets reviewers see the actual changes that will happen; which S3 buckets will be removed, which IAM permissions will be added, and which security groups will change. It helps catch issues like accidental resource deletion or security misconfigurations before they cause problems in live environments.

Regular comparison jobs detect discrepancies between the applied infrastructure and Git-defined configuration. These jobs typically run on a schedule (such as nightly) or after configuration changes, generating alerts when detecting unauthorized modifications or manual overrides.

Infrastructure GitOps requires special handling for stateful resources. While something like a Kubernetes Pod can generally be recreated without data loss, resources like databases and storage volumes need protection mechanisms. You can implement these safeguards through:

• Change classification that flags state-destroying operations
• Automated pre-change backups for critical resources
• Progressive change application starting with lower environments
• Temporary state locks during sensitive operations

By applying these patterns, teams extend GitOps benefits to their core infrastructure while accommodating the stateful nature of many Terraform-managed resources.

Implementing GitOps Workflows for Terraform

Organizing Terraform code effectively is necessary for a successful GitOps implementation. Most teams adopt either a mono-repo approach with directory separation for environments, or a multi-repo strategy that isolates production configurations. The mono-repo pattern simplifies module sharing and cross-environment promotion, while multi-repo setups provide stronger access controls for production resources and stricter operational isolation.

A typical Terraform GitOps repository structure includes:

terraform/
├── modules/            # Reusable infrastructure components
│   ├── networking/
│   ├── database/
│   └── compute/
├── environments/       # Environment-specific configurations
│   ├── development/
│   ├── staging/
│   └── production/
└── pipelines/          # CI/CD workflow definitions

The CI pipeline for Terraform changes should include several primary stages. First, validation confirms syntactic correctness and internal consistency. Next, linting enforces code standards using tools like TFLint. Security scanning with tfsec or checkov identifies potential vulnerabilities before they reach production. Finally, plan generation creates the execution roadmap that shows what will change.

Pull requests trigger these pipelines automatically, with the generated plan attached to the PR as a comment. This workflow gives reviewers a clear picture of the proposed changes, including affected resources and their relationships. Many teams require approvals from both infrastructure specialists and application owners when changes might impact running services.

Once approved, the apply stage executes the plan with proper state locking to prevent concurrent modifications. Error handling is crucial here - the pipeline should provide detailed logs on failures while preventing partial applys that might leave infrastructure in an inconsistent state.

For multi-account or multi-region deployments, pipeline orchestration is more complex. Teams typically implement staged rollouts that deploy to development environments first, run integration tests, then proceed to production only after verification. This approach catches configuration issues early while minimizing risk to critical environments.

Tooling for GitOps with Terraform

Several tools support GitOps workflows for Terraform, each with different strengths depending on your existing infrastructure and team preferences.

For teams already using Kubernetes, Flux works well as an extension point for infrastructure automation. While primarily designed for Kubernetes resources, Flux can trigger Terraform operations through its sources and notification controllers. This approach works best when your infrastructure changes frequently follow application deployments.

If you’re already invested in BSL-licensed Terraform and the Hashicorp ecosystem, Terraform Cloud provides some GitOps capabilities. When connected to your Git repositories, it automatically queues plans when pull requests are created and waits for approval before applying changes. The platform handles state management, secret storage, and access controls while providing an audit trail of executed operations.

Atlantis offers a lightweight alternative focused specifically on Terraform automation. It runs as a standalone service that monitors pull requests, automatically generates plans, and applies approved changes. Its commenting functionality makes the review process transparent, showing exactly what will change before approval.

Alternatively, solutions like Terrateam act as a dedicated GitOps layer directly within your Git provider, extending support beyond Terraform to include OpenTofu, Terragrunt, CDKTF, and Pulumi. These tools automate the complete pull request lifecycle for infrastructure changes and often include integrated policy enforcement, cost estimation, and dependency tracking features.

Many organizations start by building custom GitOps pipelines using general-purpose CI/CD tools:

# Example GitHub Actions workflow (simplified)

name: Terraform GitOps

on:
  pull_request:
    paths:
      - 'terraform/**'

jobs:
  terraform:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: hashicorp/setup-terraform@v2

      - name: Terraform Init
        run: terraform init

      - name: Terraform Plan
        run: terraform plan -out=tfplan

      - name: Add Plan to PR
        uses: actions/github-script@v6
        with:
          script: |
            // Add plan output as PR comment

The key is choosing tools that integrate well with your existing development workflow while providing the automation and visibility needed for a working GitOps implementation.

Implementation Challenges

Implementing GitOps for Terraform introduces several challenges that teams must address to ensure successful adoption.

Environment-specific variables create one of the first hurdles. Unlike application deployments where environment variables might be injected at runtime, Terraform requires different variable sets for development, staging, and production. Most teams solve this through environment-specific variable files (tfvars) stored alongside their configurations. This approach works well but requires careful handling of sensitive values.

Securing sensitive data presents another significant challenge. Teams typically employ one of three approaches: integration with secret management tools like HashiCorp Vault, encryption-at-rest using SOPS or similar tools, or leveraging cloud provider secret services. Each method involves tradeoffs between security, usability, and integration complexity.

Terraform state files contain sensitive output values and require careful handling. In a GitOps context, state should be stored remotely with proper access controls and versioning. Teams implement state locking to prevent concurrent operations that could corrupt state files, particularly important when multiple pipelines might trigger simultaneously.

Managing dependencies between infrastructure components frequently challenges teams new to GitOps. When network changes must precede database updates, which in turn must happen before application changes, pipeline orchestration suddenly becomes a complex issue. Successful implementations typically map these dependencies explicitly and create staged workflows that respect these relationships.

Testing infrastructure code reveals another pain point. Unlike application code with well-established testing frameworks, infrastructure testing often requires actual resource creation. Tools like Terratest help address this need by spinning up real resources in isolated environments, running validation tests, and then tearing them down. These tests catch configuration issues before they reach production, but do add time and cost to pipelines.

Best Practices for Success

There are some general best practices your team can follow that can help boost your chances of a successful GitOps implementation.

Repository structure decisions significantly impact long-term maintainability. Successful teams balance modularization with operational needs by creating reusable modules for common infrastructure patterns while keeping environment-specific configurations separate. This separation lets you standardize resource creation while accommodating legitimate variations between environments.

PR templates help reviewers focus on critical aspects of infrastructure changes. Effective templates highlight security implications, cost impacts, and potential service disruptions. They prompt submitters to explain their changes in business terms, not just technical details:

## Change Description
[Describe infrastructure change and business purpose.]

## Security Impact
[Note any changes to security groups, IAM permissions, or network ACLs.]

## Service Impact
[Will this change cause downtime? Are there dependencies to consider?]

## Rollback Plan
[How can we revert if problems occur?]

Automated policy enforcement through tools like Open Policy Agent (OPA), tfsec, or checkov prevents common security and compliance issues. These tools validate infrastructure definitions against organizational policies before changes reach production. Examples include ensuring all S3 buckets are encrypted, preventing public access to sensitive resources, and enforcing tagging standards.

For high-risk infrastructure changes, canary and progressive deployment patterns reduce potential impact. Teams implement these patterns by deploying changes to a subset of resources, validating functionality, then gradually expanding scope. This approach works particularly well for regional infrastructure where changes can be tested in a single region before rolling out globally.

The Path Forward

Applying GitOps principles to Terraform-managed infrastructure solves a common problem in DevOps workflows. Teams that handle infrastructure changes like application code make fewer manual errors, maintain more stable software environments, and create clear records of each change.

To implement GitOps for your Terraform workflows:

1. Move Terraform configurations to version-controlled repositories
2. Set up CI pipelines for validation, security scans, and plan generation
3. Create PR templates highlighting security and service impacts
4. Automate applying approved changes
5. Monitor for drift between defined and actual states

When application and infrastructure pipelines work together, teams deploy related components in coordination, reducing partial deployment risks. Success metrics include deployment frequency, time-to-recovery, and how often infrastructure deviates from the Git-defined state.

By treating infrastructure as code with proper version control, review processes, and automated deployment, organizations build a solid foundation for cloud resources while maintaining the agility modern technology demands.