Design your Production Schema
Design your first GraphQL schema for adaptability and clarity
This guide helps you design your first GraphQL schema—the foundational layer of your application’s data interface. You'll learn why schema design is critical, follow clear steps to build your first schema rapidly, and discover the essential resources for best practices and ongoing evolution.
Prerequisites
A basic understanding of your business model
A basic understanding of GraphQL
A decision on the first use cases this schema will support
By the end of the milestone, you'll have:
A minimal, well-documented schema covering your core business use cases
Initial entity definitions, relationships, and well-named fields
The importance of schema design
Your GraphQL schema is the foundation of your application's data interface. Good schema design:
Enables adaptability: Your graph evolves as your business needs change
Improves discoverability: Clear naming and documentation help clients understand your data
Simplifies governance: Well-structured schemas make changes easier to manage and deploy
Steps to complete
Focus on your known use cases only. Start simple and iterate quickly. Build a pragmatic initial version covering your main use cases. Plan to evolve your schema as you learn from usage and feedback.
Schema design is an ongoing process. The best schemas evolve alongside your business and are built for change.
1. Identify core business entities
List the most important objects or concepts in your business domain (for example, User, Order, Product) that align with your known use cases.
Begin with a short summary of your app—what your graph represents and enables.
2. Define relationships and key operations
Determine how entities relate to one another (for example, a User can have many Orders).
Identify which queries or mutations clients need (such as fetching product details or creating orders).
3. Create the schema definition (SDL)
Create your GraphQL schema files using Schema Definition Language (SDL) based on your identified entities, relationships, and operations. Start with the core types and fields needed for your known use cases.
4. Name types, fields, and operations clearly
Use descriptive, consistent naming and avoid ambiguous language and abbreviations.
Clear naming benefits both developers and AI-powered tools consuming your schema.
5. Document every type and field
Write concise descriptions for each type and field, explaining their purpose and expected usage.
Schema documentation enables discovery and rapid onboarding—crucial for new team members and AI agents.
6. Define subgraph boundaries
Keeping subgraphs scoped to specific domains and teams helps with maintainability and clarity. Discuss what your subgraph boundaries should be within your organization.