A Practical Guide To Building Enterprise-Grade APIs

In today's interconnected software ecosystem, APIs are the lifeblood of modern applications. The difference between a good API and a great one often determines whether developers love or loathe integrating with your service. Companies like Stripe and Plaid have set the gold standard—their APIs are not just functional, they're delightful to use.

But what separates an enterprise-grade API from a hastily constructed endpoint? The little details.

The Seven Pillars of Enterprise APIs

Before diving into implementation details, understand what makes an API truly enterprise-ready:

1. Well-documented: Clear, comprehensive documentation that developers actually want to read
2. Intuitive and easy to use: Predictable behavior that follows common conventions
3. Consistent: Uniform patterns across all endpoints
4. Scalable and performant: Handles growth without breaking
5. Secure and resilient: Protects data and gracefully handles failures
6. Useful dataset: Provides real value to consumers
7. Reasonable pricing: Accessible to developers at various scales

URI Design: The Foundation of Discoverability

Your URIs are the first thing developers interact with. Make them count.

Follow Kebab-Case for Readability

Use hyphens to delimit combined words, and always use plural nouns for collections:

// ❌ Bad
POST /api/v2/LiquidityProvider
GET /api/v2/LiquidityProviders?id=12345
DELETE /api/v2/LiquidityProviders/

// ✅ Good
POST /api/v2/liquidity-providers
GET /api/v2/liquidity-providers/12345
DELETE /api/v2/liquidity-providers/12345

Key principles:

• Never end URIs with a trailing slash
• Use plural nouns for collections (/reports, /assets)
• Individual resources live beneath their collection (/reports/:reportId)
• Maintain lowercase throughout

Separate Your Models: A Critical Architecture Decision

One of the most important architectural decisions you'll make is separating your API models from your database models. Think of it like this: your database model is your private implementation detail; your API model is your public contract.

Be like tommy, separate the API, service layer and DB models.

Why This Matters

1. Removes tight coupling:

• Your API shouldn't break every time you refactor your database schema.
• Web APIs are how clients experience your application, not how you store data internally.

2. Selective exposure:

• You rarely want to expose all database fields. Some are internal, some are sensitive, some are implementation artifacts.

3. Derived fields:

• Sometimes you want to expose calculated or aggregated data rather than raw database columns.

Type flexibility:

• Return the most appropriate data type for API consumers, which may differ from your storage format.

Your Controllers should know nothing about database models. Your repositories should know nothing about API models. The service layer is the business logic layer that interacts with both. the This separation creates a clean boundary that protects both your internal implementation, business logic and your external contract.

Request and Response Conventions

Consistency breeds familiarity. Establish clear conventions and follow them religiously:

• Use American English throughout
• Avoid acronyms that aren't universally understood
• Use camelCase for JSON properties
• Every identifier should be lowercase and human-readable

Validation: Fail Fast, Fail Clearly

Validation is your first line of defense against bad data and your best opportunity to provide helpful feedback.

Fail Fast

As soon as you encounter a validation error, stop processing and return an error. But don't stop at the first invalid field—return all validation errors at once. This dramatically improves the developer experience by allowing them to fix multiple issues in one iteration.

Validate at Multiple Layers

Implement validation at:

• The API level (parameters, headers, request bodies)
• The service/business logic level

This defense-in-depth approach catches issues from different code paths and provides an additional security layer.

Other Validation Best Practices

1. Sanitize Input

• Prevent SQL injection and XSS attacks by sanitizing HTML and SQL inputs.

2. Clear error messages:

• When validation fails, explain exactly what went wrong and how to fix it.

3. Length and size checks:

• Prevent buffer overflows and excessive payloads by validating data dimensions.

The Controller-Service-Repository Pattern

APIs are easy to build. Maintainable APIs are hard. The Controller-Service-Repository pattern provides the structure needed to keep your codebase organized as it grows.

Controller Layer (HTTP layer)

Handles HTTP concerns and orchestrates the request flow.

Responsibilities:

• Parse and validate incoming requests
• Orchestrate data flow between client and other layers
• Transform request/response data as needed
• Invoke service layer methods
• Handle HTTP status codes and error responses

Do:

• Keep Controllers lightweight
• Maintain separation of concerns
• Handle authentication/authorization

Don't:

• Implement business logic
• Access databases directly
• Mix multiple concerns.

Service Layer (Business Logic)

Contains your core application logic and business rules.

Responsibilities:

• Implement business logic and rules
• Coordinate actions across repositories
• Perform data transformations and calculations
• Enforce security and access control
• Handle complex validations
• Call external services for additional data
• Manage transactional integrity

Do:

• Encapsulate business logic
• Focus on single responsibility
• Use dependency injection
• Write comprehensive unit tests (depending on sensitivity)

Don't:

• Access databases directly
• expose infrastructure concerns
• Mix unrelated operations
• Include presentation logic

Repository Layer (Data Access)

Abstracts the underlying data storage and provides a clean interface for data operations.

Responsibilities:

• Perform CRUD operations
• Implement querying and filtering logic
• Ensure data integrity and consistency
• Manage database transactions
• Abstract storage technology details

Do:

• Keep data access logic isolated
• Abstract storage specifics
• Optimize queries for performance
  • Create materialized views, indexes, etc.

Don't:

• Implement business logic
• Expose database-specific operations
• Neglect security measures

Logging: Your Window into Production

Good logging turns debugging from a nightmare into a manageable task.

Log Levels Matter

Choose the appropriate level based on severity:

Error

• Requires immediate attention
• Something broke that needs fixing, drive alerts from!

Warning

• Suspicious but not critical
• Unusual code paths that deserve monitoring, potential alerting usually with thresholding
  • After X warnings in Y hours, log an error (overly sus)

Info

• Useful operational information. Use sparingly to avoid noise / cost

Debug

• Development-time visibility
• Verbose details for troubleshooting

What to Log

Context is KEY!:

• Include contextual information that aids troubleshooting!
  • Request/response data
  • Timestamps
  • User IDs
  • Error codes
  • Relevant business context
  • Params used in function invocation

Critical:

• Never log sensitive information like passwords, personally identifiable information (PII), or confidential data. If you must log it, ensure proper obfuscation.

Tracing: Observability at Scale

Distributed tracing enables you to observe API calls through the entire stack, revealing not just issues but trends and performance bottlenecks. Implement tracing early—it's far harder to add later when you're trying to debug production issues at 2 AM.

Enrichment: Parallel Processing for Performance

When your endpoint needs data from multiple sources, fetch them in parallel rather than sequentially. Use concurrent programming constructs (goroutines, threads, async/await) to minimize latency.

This approach:

• Builds endpoints with the lowest possible latency
• Avoids duplicate calls to microservices
• Reduces load on dependent systems

The Path Forward

Building enterprise-grade APIs isn't about following rigid rules—it's about adopting principles that create consistency, maintainability, and a delightful developer experience. Start with these foundations, adapt them to your context, and always keep your API consumers in mind.

Remember: your API is a product, and like any product, it should be designed with empathy for its users. When developers can integrate with your API in minutes instead of days, you've succeeded in building something truly enterprise-grade.