When it comes to managing AWS infrastructure at scale, Terraform has become the de facto standard for Infrastructure as Code (IaC). However, the difference between a Terraform project that works and one that scales reliably in production environments is often in the details.
In this guide, we'll explore the battle-tested practices we've refined over years of deploying production infrastructure for fintech, e-commerce, and SaaS companies.
1. Project Structure: Keep It Modular
The first critical decision is how to structure your Terraform code. A common mistake is putting everything in a single monolithic configuration. This creates several problems: long apply times, increased blast radius for changes, and difficulty in managing different environments.
Instead, we recommend a modular approach:
- Separate by environment: dev, staging, and production should be isolated
- Use modules for reusable components: VPC, ECS clusters, RDS instances
- Keep state files separate: Different backend configurations per environment
- Layer your infrastructure: Networking, compute, data, and application layers
Example Structure
terraform/
├── modules/
│ ├── vpc/
│ ├── ecs-cluster/
│ └── rds/
├── environments/
│ ├── dev/
│ ├── staging/
│ └── production/
└── global/
└── iam/
2. State Management: S3 + DynamoDB
Terraform state is the source of truth for your infrastructure. Losing it or having conflicts can be catastrophic. Always use remote state with proper locking:
- S3 backend for storing state files with versioning enabled
- DynamoDB for state locking to prevent concurrent modifications
- Encryption at rest using AWS KMS
- Separate state files per environment and layer
3. Variable Management and Secrets
How you manage variables and secrets is crucial for both security and maintainability:
- Use
terraform.tfvarsfiles per environment, but never commit secrets - Store sensitive values in AWS Secrets Manager or Parameter Store
- Use
datasources to fetch secrets at runtime - Implement proper IAM policies to control access to secrets
Pro tip: Use pre-commit hooks with tools like terraform-docs and tfsec to catch issues before they reach your CI/CD pipeline.
4. CI/CD Integration
Manual Terraform runs should be the exception, not the rule. A proper CI/CD pipeline ensures consistency and reduces human error:
- Plan on pull requests: Automatically run
terraform planand post results as comments - Apply on merge: Only apply changes after code review and approval
- Use workspaces strategically: Or better yet, separate directories with different backends
- Implement proper approval gates: Especially for production deployments
5. Testing and Validation
Before changes reach production, they should pass multiple validation layers:
terraform fmtfor consistent formattingterraform validatefor syntax checkingtfsecfor security scanningcheckovfor policy as code validation- Integration tests in lower environments
6. Documentation and Drift Detection
Documentation isn't optional—it's essential for maintainability:
- Use
terraform-docsto auto-generate module documentation - Maintain a README in each module explaining its purpose and usage
- Implement drift detection with scheduled
terraform planruns - Set up alerts for when infrastructure drifts from the desired state
Conclusion
These practices aren't just theoretical—they're the result of managing infrastructure for dozens of production applications. They help you move fast while maintaining reliability, security, and maintainability.
The key is to start with good foundations. It's much harder to retrofit these practices into an existing messy Terraform setup than to start with them from day one.
At Core Infrastructure, we implement these patterns as standard practice in every engagement. If you're looking to modernize your infrastructure or start a new project with Terraform best practices baked in, let's talk.