API Design Patterns

Expert guidance for designing scalable, maintainable REST and GraphQL APIs with industry-standard patterns for versioning, pagination, error handling, authentication, and service contracts.

When to Use This Skill

• Designing new REST or GraphQL APIs from scratch
• Refactoring existing APIs for better scalability and consistency
• Defining service contracts for microservices architectures
• Implementing versioning strategies for API evolution
• Standardizing error handling and response formats across services
• Designing pagination for large datasets
• Implementing HATEOAS or hypermedia-driven APIs
• Creating API specifications (OpenAPI, GraphQL Schema)

Quick Reference

Core Principles

1. Resource-Oriented Design (REST)

URLs represent resources, not actions:

✓ GET    /users/123
✓ POST   /users
✓ PUT    /users/123
✓ DELETE /users/123

✗ GET    /getUser?id=123
✗ POST   /createUser
✗ POST   /deleteUser

Use HTTP methods semantically:

• GET: Retrieve resource(s), idempotent, cacheable
• POST: Create resource, non-idempotent
• PUT: Replace entire resource, idempotent
• PATCH: Partial update, idempotent
• DELETE: Remove resource, idempotent

2. Consistent Naming Conventions

Resources:        /users, /orders, /products (plural nouns)
Nested:           /users/123/orders
Collections:      /users?status=active&page=2
Sub-resources:    /users/123/settings
Actions (rare):   /users/123/activate (POST)

3. HTTP Status Codes

Success:

• 200 OK: Standard response for GET, PUT, PATCH
• 201 Created: Resource created (POST), return Location header
• 202 Accepted: Async processing started
• 204 No Content: Success with no response body (DELETE)

Client Errors:

• 400 Bad Request: Invalid syntax or validation failure
• 401 Unauthorized: Authentication required or failed
• 403 Forbidden: Authenticated but insufficient permissions
• 404 Not Found: Resource doesn't exist
• 409 Conflict: State conflict (duplicate, version mismatch)
• 422 Unprocessable Entity: Semantic validation failure
• 429 Too Many Requests: Rate limit exceeded

Server Errors:

• 500 Internal Server Error: Unexpected server failure
• 502 Bad Gateway: Upstream service failure
• 503 Service Unavailable: Temporary overload or maintenance
• 504 Gateway Timeout: Upstream timeout

Versioning Strategies

URI Versioning (Most Common)

GET /v1/users/123
GET /v2/users/123

Pros: Clear, easy to route, browser-testable
Cons: URL proliferation, cache fragmentation
When: Public APIs, major breaking changes

Header Versioning

GET /users/123
Accept: application/vnd.myapi.v2+json

Pros: Clean URLs, content negotiation
Cons: Harder to test, caching complexity
When: Internal APIs, minor version differences

Query Parameter Versioning

GET /users/123?version=2

Pros: Simple, backward compatible
Cons: Pollutes query space, inconsistent
When: Rare, legacy compatibility

Deprecation Headers

Sunset: Sat, 31 Dec 2024 23:59:59 GMT
Deprecation: true
Link: <https://api.example.com/v2/users/123>; rel="successor-version"

Pagination Patterns

Offset-Based Pagination

GET /users?limit=20&offset=40

Response:
{
  "data": [...],
  "pagination": {
    "limit": 20,
    "offset": 40,
    "total": 1543
  },
  "links": {
    "next": "/users?limit=20&offset=60",
    "prev": "/users?limit=20&offset=20"
  }
}

Pros: Simple, predictable, supports total count
Cons: Inconsistent with concurrent writes, performance degrades
When: Small datasets, stable data, admin UIs

Cursor-Based Pagination

GET /users?limit=20&cursor=eyJpZCI6MTIzfQ

Response:
{
  "data": [...],
  "pagination": {
    "next_cursor": "eyJpZCI6MTQzfQ",
    "has_more": true
  },
  "links": {
    "next": "/users?limit=20&cursor=eyJpZCI6MTQzfQ"
  }
}

Pros: Consistent with writes, scalable, efficient
Cons: No total count, can't jump to arbitrary page
When: Large datasets, real-time feeds, infinite scroll

Keyset Pagination (Seek Method)

GET /users?limit=20&after_id=123&created_after=2024-01-01T00:00:00Z

Pros: Most performant, index-friendly
Cons: Requires sortable field, complex queries
When: Very large datasets, time-series data

Error Response Format

Standard Error Schema

{
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Request validation failed",
    "details": [
      {
        "field": "email",
        "code": "INVALID_FORMAT",
        "message": "Email format is invalid"
      },
      {
        "field": "age",
        "code": "OUT_OF_RANGE",
        "message": "Age must be between 18 and 120"
      }
    ],
    "request_id": "req_a3f7c9b2",
    "timestamp": "2024-01-15T10:30:00Z",
    "documentation_url": "https://docs.api.com/errors/VALIDATION_ERROR"
  }
}

Error Code Patterns

Format: CATEGORY_SPECIFIC_REASON

Authentication:
- AUTH_MISSING_TOKEN
- AUTH_INVALID_TOKEN
- AUTH_EXPIRED_TOKEN

Authorization:
- AUTHZ_INSUFFICIENT_PERMISSIONS
- AUTHZ_RESOURCE_FORBIDDEN

Validation:
- VALIDATION_MISSING_FIELD
- VALIDATION_INVALID_FORMAT
- VALIDATION_OUT_OF_RANGE

Business Logic:
- BUSINESS_DUPLICATE_EMAIL
- BUSINESS_INSUFFICIENT_BALANCE
- BUSINESS_OPERATION_NOT_ALLOWED

System:
- SYSTEM_INTERNAL_ERROR
- SYSTEM_SERVICE_UNAVAILABLE
- SYSTEM_RATE_LIMIT_EXCEEDED

Filtering and Searching

Query Parameters for Filtering

GET /users?status=active&role=admin&created_after=2024-01-01

GET /users?search=john&fields=name,email

GET /users?sort=-created_at,name  # - prefix for descending

Complex Filtering (FIQL/RSQL)

GET /users?filter=status==active;role==admin,role==moderator
               # AND between semicolons, OR between commas

GET /products?filter=price>100;price<500;category==electronics

Full-Text Search

GET /users?q=john+smith&fields=name,bio,company

Response includes relevance scoring:
{
  "data": [
    {
      "id": 123,
      "name": "John Smith",
      "_score": 0.95
    }
  ]
}

Field Selection (Sparse Fieldsets)

GET /users/123?fields=id,name,email

Response:
{
  "id": 123,
  "name": "John Doe",
  "email": "john@example.com"
}

# Nested resources
GET /users/123?fields=id,name,profile(avatar,bio)

Benefits:
- Reduced payload size
- Faster response times
- Lower bandwidth consumption
- Better mobile performance

HATEOAS (Hypermedia)

HAL (Hypertext Application Language)

{
  "id": 123,
  "name": "John Doe",
  "email": "john@example.com",
  "_links": {
    "self": { "href": "/users/123" },
    "orders": { "href": "/users/123/orders" },
    "update": { "href": "/users/123", "method": "PUT" },
    "delete": { "href": "/users/123", "method": "DELETE" }
  },
  "_embedded": {
    "recent_orders": [
      {
        "id": 456,
        "total": 99.99,
        "_links": {
          "self": { "href": "/orders/456" }
        }
      }
    ]
  }
}

JSON:API Format

{
  "data": {
    "type": "users",
    "id": "123",
    "attributes": {
      "name": "John Doe",
      "email": "john@example.com"
    },
    "relationships": {
      "orders": {
        "links": {
          "self": "/users/123/relationships/orders",
          "related": "/users/123/orders"
        }
      }
    },
    "links": {
      "self": "/users/123"
    }
  }
}

Rate Limiting Headers

X-RateLimit-Limit: 1000
X-RateLimit-Remaining: 742
X-RateLimit-Reset: 1705320000
Retry-After: 3600

# Standard (RFC 6585)
RateLimit-Limit: 1000
RateLimit-Remaining: 742
RateLimit-Reset: 3600

Authentication Patterns

Bearer Token (OAuth 2.0, JWT)

Authorization: Bearer eyJhbGciOiJIUzI1NiIs...

Pros: Stateless, scalable, standard
Cons: Token size, revocation complexity
When: Modern APIs, microservices

API Key

X-API-Key: ak_live_a3f7c9b2d8e1f4g6h9

Pros: Simple, server-side management
Cons: Less secure, harder to scope
When: Internal services, admin APIs

Basic Auth

Authorization: Basic dXNlcm5hbWU6cGFzc3dvcmQ=

Pros: Simple, built-in browser support
Cons: Credentials in every request
When: Internal tools, development only

Idempotency

Idempotency Keys (POST)

POST /payments
Idempotency-Key: a3f7c9b2-d8e1-4f6g-h9i0-j1k2l3m4n5o6
Content-Type: application/json

{
  "amount": 100.00,
  "currency": "USD",
  "description": "Payment for order #123"
}

# Server stores key + response for 24 hours
# Duplicate requests return cached response with 200 OK

Natural Idempotency

PUT /users/123          # Always idempotent
DELETE /users/123       # Idempotent (404 on repeat)
POST /users/123/follow  # Use PUT for idempotency

Caching Strategies

ETags (Conditional Requests)

# Initial request
GET /users/123
ETag: "a3f7c9b2"

# Subsequent request
GET /users/123
If-None-Match: "a3f7c9b2"

# Response if unchanged:
304 Not Modified

Cache-Control Headers

# Never cache
Cache-Control: no-store

# Cache for 1 hour, revalidate
Cache-Control: max-age=3600, must-revalidate

# Cache forever (immutable)
Cache-Control: public, max-age=31536000, immutable

GraphQL Patterns

Query Structure

query GetUser($id: ID!) {
  user(id: $id) {
    id
    name
    email
    orders(first: 10) {
      edges {
        node {
          id
          total
          status
        }
      }
      pageInfo {
        hasNextPage
        endCursor
      }
    }
  }
}

Error Handling

{
  "data": {
    "user": null
  },
  "errors": [
    {
      "message": "User not found",
      "locations": [{ "line": 2, "column": 3 }],
      "path": ["user"],
      "extensions": {
        "code": "NOT_FOUND",
        "userId": "123"
      }
    }
  ]
}

Mutation Patterns

mutation CreateUser($input: CreateUserInput!) {
  createUser(input: $input) {
    user {
      id
      name
      email
    }
    errors {
      field
      message
    }
  }
}

Best Practices Summary

1. Consistency: Follow conventions across all endpoints
2. Versioning: Plan deprecation strategy from day one
3. Documentation: Use OpenAPI/GraphQL schemas, keep updated
4. Error Handling: Detailed, actionable error messages with codes
5. Security: Always use HTTPS, validate inputs, rate limit
6. Performance: Implement caching, pagination, field selection
7. Monitoring: Log request IDs, track latency and error rates
8. Backward Compatibility: Additive changes only within versions
9. Testing: Contract tests, integration tests, load tests
10. Documentation: Interactive docs (Swagger UI, GraphQL Playground)

Anti-Patterns to Avoid

1. Chatty APIs: Too many round trips (use batching, GraphQL)
2. Over-fetching: Returning unnecessary data (use field selection)
3. Under-fetching: Requiring multiple calls (use includes/embeds)
4. Leaking Implementation: Exposing DB structure in API
5. Poor Error Messages: Generic errors without details
6. Breaking Changes: Modifying existing fields without versioning
7. No Rate Limiting: Allowing resource exhaustion
8. Missing Documentation: Undocumented endpoints and parameters
9. Inconsistent Naming: Mixed conventions across endpoints
10. Ignoring HTTP Semantics: Misusing status codes and methods

Resources

• REST: Roy Fielding's dissertation, RFC 7231 (HTTP semantics)
• OpenAPI: https://spec.openapis.org/oas/latest.html
• GraphQL: https://graphql.org/learn/
• HAL: https://stateless.group/hal_specification.html
• JSON:API: https://jsonapi.org/
• RFC 7807: Problem Details for HTTP APIs