6/30/2025

This guide details best practices for Apollo GraphQL API development. It covers schema design, security, performance optimization, code organization, testing, and more. It also provides tips on avoiding common pitfalls, using tools, and following additional practices like versioning and documentation.


# Apollo GraphQL Best Practices

This document provides a comprehensive guide to best practices and coding standards for developing GraphQL APIs and applications using the Apollo ecosystem.

## Library Information:
- Name: apollo-graphql
- Tags: web, api, graphql, javascript

## 1. Schema Design

- **Clarity and Consistency:**
    - Use descriptive naming conventions for types, fields, and arguments (e.g., `getUserById` instead of `getUser`).
    - Maintain consistency across the schema in terms of naming and structure.
    - Define a clear schema that reflects your business domain and data model.

- **Interfaces and Unions:**
    - Implement interfaces and unions for shared features and common data structures.
    - Use interfaces to define contracts for types that implement shared behaviors.
    - Use unions when a field can return different object types that don't share a common interface.

- **Nullability:**
    - Every field is nullable by default unless explicitly marked as non-null using `!`.  Carefully consider nullability for each field.
    - Use non-null types (`!`) only when you can guarantee that the field will always return a value.
    - Handle potential errors gracefully and return `null` for nullable fields when appropriate.

- **Demand-Driven Schema Design:**
   - Design your schema to serve client use cases and product requirements.
   - Intentionally design your schema to serve client use cases and product requirements.

- **Avoid Autogenerated Schemas:**
    - Avoid autogenerating schemas, especially the fields on the root operation types

## 2. Security

- **Disable Introspection in Production:**
    - Disable introspection in production environments to prevent unauthorized access to your schema.
    - Restrict access to staging environments where introspection is enabled.

- **Input Validation:**
    - Validate all user inputs to prevent injection attacks and data corruption.
    - Use custom scalars or directives to enforce validation rules on input types.
    - Sanitize and escape user inputs before using them in resolvers.

- **Authentication and Authorization:**
    - Implement robust authentication and authorization mechanisms to protect your API.
    - Use industry-standard protocols like OAuth 2.0 or JWT for authentication.
    - Implement fine-grained authorization checks at the field level.
    - Enforcing authentication and authorization in the router protects your underlying APIs from malicious operations

- **Rate Limiting and Depth Limiting:**
    - Implement rate limiting to prevent abuse and denial-of-service attacks.
    - Limit query depth to prevent complex queries from overwhelming your server.

- **Whitelisting Queries:**
    - Consider whitelisting queries to restrict the operations that can be executed against your API.

- **Obfuscate Error Details:**
    - Remove verbose error details from API responses in your production graph.
    - Only selectively expose error details to clients in production.

- **Data Validation and Sanitization:**
    - As a schema design best practice, you should deliberately design your schema to serve client use cases and product requirements.

## 3. Performance Optimization

- **Batching and Caching:**
    - Utilize batching techniques (e.g., DataLoader) to reduce the number of requests to backend data sources.
    - Implement caching at different levels (e.g., server-side, client-side) to improve response times.

- **Pagination:**
    - Implement pagination strategies to manage large datasets effectively.
    - Use cursor-based pagination for efficient retrieval of paginated data.

- **N+1 Problem:**
    - Use tools like DataLoader to address the N+1 query problem and ensure efficient data fetching.

- **Server-Side Batching & Caching:**
    - GraphQL is designed in a way that allows you to write clean code on the server, where every field on every type has a focused single-purpose function for resolving that value.

- **Automatic Persisted Queries (APQ):**
    - Consider implementing automatic persisted queries (APQ) to optimize network usage and improve security

## 4. Code Organization and Structure

- **Directory Structure:**
    
    src/
      schema/
        types/
          *.graphql
        resolvers/
          *.js
      dataSources/
        *.js
      utils/
        *.js
      index.js // Entry point
    

- **File Naming Conventions:**
    - Use PascalCase for type definitions (e.g., `UserType.graphql`).
    - Use camelCase for resolver functions (e.g., `getUserById.js`).

- **Module Organization:**
    - Organize your code into reusable modules based on functionality (e.g., user management, product catalog).
    - Create separate modules for schema definitions, resolvers, and data sources.

- **Component Architecture:**
    - Follow a component-based architecture for building GraphQL applications.
    - Create reusable components for common UI elements and data fetching logic.

- **Code Splitting:**
    - Use code splitting to reduce the initial bundle size and improve page load times.
    - Consider splitting your application into smaller chunks based on routes or features.

## 5. Common Patterns and Anti-patterns

- **Design Patterns:**
    - **Data Source Pattern:** Decouple data fetching logic from resolvers using data sources.
    - **Schema Stitching:** Combine multiple GraphQL APIs into a single, unified schema.

- **Recommended Approaches:**
    - Use a GraphQL client library (e.g., Apollo Client, Relay) for efficient data fetching and caching.
    - Implement custom directives to add additional functionality to your schema.

- **Anti-patterns:**
    - **Over-fetching/Under-fetching:** Avoid returning more or less data than required by the client.
    - **Chatty APIs:** Reduce the number of round trips between the client and the server.
    - **God Objects:** Avoid creating large, monolithic types with too many fields.

- **State Management:**
    - Use a state management library (e.g., Redux, Zustand, Jotai) to manage client-side state.
    - Consider using Apollo Client's local state management features for simple state requirements.

- **Error Handling:**
    - Use a consistent error handling mechanism across your application.
    - Return informative error messages to the client.
    - Log errors on the server for debugging purposes.

## 6. Testing Approaches

- **Unit Testing:**
    - Unit test individual resolvers and data sources.
    - Mock external dependencies to isolate the code under test.

- **Integration Testing:**
    - Integrate test your GraphQL API with your database and other backend services.
    - Use a testing framework like Jest or Mocha for writing integration tests.

- **End-to-End Testing:**
    - Use end-to-end testing to verify the entire application flow.
    - Use a testing tool like Cypress or Puppeteer for writing end-to-end tests.

- **Test Organization:**
    - Organize your tests into separate directories based on functionality.
    - Use descriptive names for your test files and test cases.

- **Mocking and Stubbing:**
    - Use mocking and stubbing techniques to isolate the code under test and simulate external dependencies.

## 7. Common Pitfalls and Gotchas

- **N+1 Problem:** Be aware of the N+1 query problem and use DataLoader or other batching techniques to solve it.
- **Schema Evolution:** Plan for schema evolution and use techniques like adding new fields and deprecating old ones to avoid breaking changes.
- **Performance Bottlenecks:** Monitor your API for performance bottlenecks and use profiling tools to identify slow resolvers.
- **Nullability:** Ensure that non-null fields never return `null` to avoid unexpected errors.

## 8. Tooling and Environment

- **Development Tools:**
    - Use a GraphQL IDE like GraphiQL or Apollo Studio for exploring and testing your API.
    - Use code generation tools to generate types and resolvers from your schema.

- **Build Configuration:**
    - Use a build tool like Webpack or Parcel to bundle your code for production.
    - Configure your build tool to optimize your code and reduce bundle size.

- **Linting and Formatting:**
    - Use a linter like ESLint or Prettier to enforce code style and prevent errors.

- **Deployment:**
    - Deploy your GraphQL API to a production environment like AWS Lambda, Google Cloud Functions, or a Node.js server.
    - Use a serverless platform for easy scaling and management.

- **CI/CD Integration:**
    - Integrate your GraphQL API with a CI/CD pipeline for automated testing and deployment.

## 9. Additional Best Practices

- **Versioning:** While GraphQL promotes continuous evolution, consider versioning your API if you need to make breaking changes.
- **Documentation:** Provide comprehensive documentation for your GraphQL API using tools like GraphQL Docs.
- **Monitoring:** Monitor your GraphQL API for performance and errors using tools like Apollo Studio or New Relic.
- **Error Messages and Notifications:** You can also opt for union types to represent an error and to prompt suggestions to users, though this is a more expensive choice.

## 10. Global Identification

- Another way to organize components, besides Pagination, is by using a global identification. Originally proposed on Relay and similar to URIs, this method has become a more general good practice though it is not considered mandatory — especially if you are not planning on supporting Relay in your application

## 11. Rate Limiting

-  Like any other web API, setting limits is a good strategy to avoid, for example, an overload of requests per minute. There are a few ways this can be done in GraphQL

## 12. Authentication and Authorization

- Often interchanged in their meaning, authentication is the act of determining who a user is and whether they are logged in or not. Authorization, on the other hand, is the act of determining if a user is allowed to do an action or see something.

## 13. Safelisting with Persisted queries

-  Beyond operation limits, GraphOS enables first-party apps to register trusted operations in a persisted query list ( PQL) or safelist.