Expedite Infrastructure Delivery with GitOps and CI/CD Integration

For many infrastructure teams, configuration drift is an all-too-familiar headache. A quick manual fix during an outage never gets documented. A hotfix applied in production never makes it back to staging. Over time, these small lapses accumulate, environments diverge, and the once-stable deployment pipeline becomes fragile. Changes that passed flawlessly in testing suddenly fail in production, and no one is quite sure why.

GitOps offers a systematic solution to this problem. Treating infrastructure as code and managing it through Git repositories helps teams create a single source of truth for their infrastructure configurations. The same best practices used in software development–version control, peer reviews, automated testing, and repeatable deployments—can be applied to infrastructure management. GitOps offers fewer surprises, faster iterations, and a smoother collaboration between developers and operations teams.

Let’s explore how to apply GitOps principles effectively to infrastructure code, with a focus on practical implementation patterns, common pitfalls, and tools that support this workflow.

Repository Structure Matters.

One of the first decisions when adopting GitOps for infrastructure is how to organize your code repositories, in particular, whether to use a single repository or multiple repositories for infrastructure code. While it might seem like a trivial detail, the right structure can prevent significant headaches as your infrastructure scales.

Monorepo Approach

Most teams find success with a monorepo approach, where infrastructure code for networking, compute, storage, and other resources is consolidated into a single repository. This model simplifies dependency management and gives engineers a holistic view of infrastructure changes. For example, if an update to a VPC impacts compute resources, having both configurations in the same repository makes coordination far easier.

Within the monorepo, a logical directory structure is essential. Organizing resources by type and function (such as networking/, compute/, and data/) creates clear boundaries for changes. This clarity simplifies code reviews and makes it easier for new team members to navigate the repository.

infrastructure/
├── networking/
│   ├── vpc/
│   ├── subnets/
│   └── security-groups/
├── compute/
│   ├── ecs-clusters/
│   ├── lambda-functions/
│   └── ec2-instances/
└── data/
  ├── rds-instances/
  ├── s3-buckets/
  └── dynamodb-tables/

Branching Strategy

Equally important is the branching strategy. Feature branches work particularly well with the monorepo approach because they bundle related infrastructure changes together and allow teams to isolate and test related infrastructure changes without disrupting ongoing development. Combined with ephemeral environments spun up for each branch, this approach ensures that changes are validated in realistic conditions before being merged. Protecting the main branch with required pull requests and reviews adds an additional layer of safety, ensuring no direct modifications to production infrastructure can slip through unnoticed.

Ensuring Accountability

To formalize accountability, teams often use CODEOWNERS files. These files assign specific reviewers to critical infrastructure components, ensuring that subject matter experts evaluate changes to sensitive areas like network configurations or database schemas. Here’s an example of what a CODEOWNERS file looks like, borrowed from GitLab docs:

# Specify a default Code Owner for all files with a wildcard:
* @default-owner

# Specify multiple Code Owners to a specific file:
README.md @doc-team @tech-lead

# Specify a Code Owner to all files with a specific extension:
*.rb @ruby-owner

# Specify Code Owners with usernames or email addresses:
LICENSE @legal janedoe@gitlab.com

# Use group names to match groups and nested groups:
README @group @group/with-nested/subgroup

# Specify a Code Owner to a directory and all its contents:
/docs/ @all-docs
/docs/* @root-docs
/docs/**/*.md @root-docs

# Use a section to group related rules:
[Documentation]
ee/docs    @docs
docs       @docs

# Assign a role as a Code Owner:
/config/ @@maintainer

This structured approach reduces the risk of misconfigurations and aligns infrastructure management with broader organizational security practices.

Validate Infrastructure with CI Pipelines.

Once the repository structure is in place, the next step is to enforce quality through automated validation. Continuous Integration (CI) pipelines become the first line of defense against misconfigured infrastructure.

Pre-commit Hooks

For Terraform-based workflows, the pre-commit-terraform collection maintained by Anton Babenko is a widely recommended starting point. Running linting and validation checks locally as pre-commit hooks, developers can catch common errors early, without consuming CI/CD resources unnecessarily. This immediate feedback loop improves developer efficiency and reduces friction in the development process.

Terratest

For more comprehensive validation, particularly of complex integrations, Terratest offers a robust solution. Terratest allows teams to execute end-to-end tests on infrastructure modules, ensuring they behave as expected in a real (or simulated) environment. However, Terratest comes with tradeoffs: full cycles of plan, apply, and destroy can take 10-20 minutes, which may not be practical for every pipeline. A common pattern is to run Terratest on external modules in separate repositories, avoiding bottlenecks in the main deployment workflow while still maintaining test coverage.

LocalStack

When speed and cost are concerns, tools like LocalStack become invaluable. LocalStack provides a local AWS cloud emulator, enabling teams to run Terraform plans and apply configurations against local endpoints. This approach accelerates feedback loops, catches misconfigurations early, and eliminates the need to provision actual cloud resources for every test. Integrating LocalStack into CI pipelines helps teams validate IAM permissions, networking setups, and resource configurations in minutes, not hours.

Balance Deployment Automation with Control.

With validation covered, attention turns to deployment workflows. The goal is to automate deployments across environments while maintaining appropriate safeguards, especially for production.

Terraform Plan

The deployment process typically begins with terraform plan generating a preview of proposed changes. Displaying this plan directly within pull requests enhances transparency, allowing reviewers to see exactly what resources will be added, modified, or destroyed. Visual diffs, such as highlighting additions in green and deletions in red, transform code reviews from abstract exercises into concrete infrastructure assessments.

To protect production environments, pull requests should require approvals from at least one additional engineer, enforcing the “four-eyes” principle. For critical systems, additional approval gates from security teams or system owners can provide further assurance.

Traceability, Auditing and Troubleshooting.

Once changes are approved, automated pipelines handle resource tagging and metadata management, ensuring that every infrastructure resource is traceable back to its originating commit. This level of traceability simplifies cost allocation, auditing, and troubleshooting.

To guard against drift, the slow divergence of actual infrastructure from its declared state, scheduled drift detection should run periodically. Deviations can either trigger alerts for manual review or be automatically reverted, depending on organizational policies.

For emergency scenarios, resource targeting enables rapid, scoped deployments. This “break-glass” function allows teams to address urgent issues without executing a full infrastructure deployment, minimizing risk and downtime.

Prioritize Workflow Fit Over Tooling Features.

As teams mature in their GitOps journey, they often look to specialized tools or Terraform Automation and Collaboration Software (TACOS) to streamline Terraform operations.

TACOS platforms provide centralized management of Terraform operations. They automate the plan/apply cycle, display changes visually for easier review, and often add governance controls. The market includes both comprehensive platforms and focused tools that integrate with existing CI/CD systems, with two notable ones being Terraform Cloud and Terrateam.

Terraform Cloud

Terraform Cloud, HashiCorp’s native solution, excels at state management, variable encryption, and governance controls. However, it introduces its own workflow engine, which can diverge from strict GitOps principles. Changes made directly through the Terraform Cloud UI bypass Git workflows, potentially undermining the “Git as the source of truth” model. Moreover, heavy reliance on Terraform Cloud can lead to vendor lock-in, complicating future migrations.

Terrateam

In contrast, Terrateam fully embraces GitOps. As an open-source solution, it integrates directly into existing pull request workflows, rendering Terraform plans in PRs and keeping all changes within Git. Features like dynamic dependency management, drift detection, and advanced access controls align with GitOps philosophies, while maintaining transparency and flexibility.

Going Beyond TACOS.

These TACOS platforms focus primarily on Terraform workflows for infrastructure provisioning, but GitOps principles extend beyond infrastructure code. For complete GitOps implementation, many organizations pair their infrastructure automation with application deployment tools like Argo CD. As a Kubernetes-native continuous delivery tool, Argo CD applies the same GitOps principles to application deployments that we’ve discussed for infrastructure, creating an end-to-end GitOps pipeline where infrastructure and applications are defined, reviewed, and deployed.

The key takeaway should be to not select tools based solely on feature checklists. Start by identifying your specific pain points, be it state file management, approval bottlenecks, or visibility into changes, and choose tools that address those challenges while fitting seamlessly into your existing workflows.

Manage Security Without Sacrificing Agility.

Infrastructure pipelines inevitably require access to sensitive credentials and secrets. Committing these directly to Git is, of course, a non-starter, so teams need secure mechanisms for managing secrets.

A common entry point is storing credentials in CI/CD platform variables. While this suffices for small teams, it lacks robust management and rotation capabilities. As deployments scale, more sophisticated solutions become necessary.

Hashicorp Vault

Self-hosted tools like HashiCorp Vault offer advanced features such as dynamic secret generation and fine-grained access controls. However, operating Vault clusters introduces complexity and overhead, making it more suitable for organizations with dedicated platform teams.

Cloud-native Secrets Management

For many teams, cloud-native solutions like AWS Secrets Manager or Google Secret Manager provide a balanced alternative. These services integrate with cloud identity systems, simplify access control, and eliminate the need to manage additional infrastructure. For multi-cloud environments, managed Vault services (e.g., HCP Vault) strike a middle ground, offering Vault’s capabilities without the operational burden.

Ultimately, the right choice depends on your infrastructure footprint, team size, and long-term strategy. The guiding principle remains the same: keep secrets secure, manageable, and out of Git.

Start Small, Scale with Confidence.

GitOps is not a silver bullet, but it offers a proven framework for managing infrastructure with the same rigor and reliability as software code. The real value lies not just in faster deployments, but in reducing risk, improving collaboration, and making infrastructure changes a shared responsibility.

If you’re just getting started, don’t attempt a wholesale transformation overnight. Begin by moving your infrastructure code into a Git repository with branch protections. Add basic CI checks for formatting and security. Build deployment pipelines for lower environments first. Production can follow once you’ve refined your processes. Address secrets management as you scale.

GitOps success comes from thoughtful, incremental adoption. Focusing on practical implementation and choosing tools that fit your workflow empowers you to transform infrastructure management from a fragile, error-prone process into a disciplined, reliable practice.