Implementing CRUD with Go in the Rentalin Backend

Implementing CRUD with Go in the Rentalin Backend

Building CRUD features in a production backend is not only about creating, reading, updating, and deleting records. In a real project, each CRUD operation must respect domain rules, authorization boundaries, and data consistency. In Rentalin Backend, the goal is to keep CRUD logic straightforward while still supporting transaction safety, auditing, and future multi-tenant isolation. The project structure already provides a strong base with clear separation between HTTP handlers, use cases, domain models, and repository adapters.

Why CRUD Needs Structure in This Project

Rental operations have state transitions and business constraints that are easy to break if CRUD is implemented directly in handlers. For example, a simple update on an inventory item can accidentally bypass validation for availability status. To avoid this, each request should flow through a use case layer that enforces business rules before data is persisted. This pattern also keeps handlers lightweight and testable, because handlers focus on parsing input and returning HTTP responses, while use cases perform orchestration and validation.
In practical terms, CRUD in Rentalin should follow one direction of dependency: HTTP adapter to use case to domain and port interfaces, then repository adapters for persistence. This keeps PostgreSQL or in-memory implementation details out of business logic. As a result, changing storage strategy later does not require rewriting core rental behavior.

CRUD Design Pattern for Core Entities

A reliable approach is to standardize CRUD flow for entities such as categories, products, and product items:

Create

Validate tenant scope, required fields, and uniqueness constraints in the use case. Use the repository to persist data inside a database transaction when related records are involved. Return a stable response DTO with generated identifiers and timestamps.

Read

Use filtered and paginated queries by default. Avoid loading unnecessary columns to reduce memory pressure, especially for a small VM target. Expose list and detail endpoints separately so each can optimize data shape and performance.

Update

Load current state first, apply domain validation, then persist only allowed changes. This prevents blind overwrites and helps maintain auditability. For stateful entities, allow only valid transitions instead of free-form status updates.

Delete

Prefer soft delete for master data that may still be referenced, and hard delete only when relations are guaranteed safe. Deletion must be tenant-aware and should include an audit entry for traceability.

Practical Implementation Notes in Go

In Go, define request and response models close to the HTTP adapter, and keep domain entities independent from transport concerns. Use context timeouts per request and pass context through repositories to ensure cancellation and resource control. For PostgreSQL, use conservative connection pool settings and parameterized queries to protect stability and security.
Testing should mirror the architecture. Unit tests should target use case behavior, including validation and status rules. Integration tests should verify repository correctness and tenant isolation behavior. With this setup, CRUD implementation remains clean, observable, and ready to scale into broader Rentalin workflows.

Conclusion

A professional CRUD implementation in Rentalin Backend is achieved by combining clear layer boundaries, domain-driven validation, and tenant-aware persistence patterns. This approach produces endpoints that are easier to maintain, safer under concurrent operations, and better aligned with the long-term roadmap of the project.