GraphQL Error Handling

Error Handling Overview

Error Handling is a building block you will reach for often in GraphQL. It keeps related logic together and makes your intent obvious to reviewers and future maintainers.

When you learn error handling properly, you avoid the guesswork that leads to bugs and rework. The example below shows the shape you will use in most real GraphQL projects.

import { GraphQLError } from 'graphql';

if (!input.email.includes('@')) {
  throw new GraphQLError('Invalid email', {
    extensions: { code: 'BAD_USER_INPUT', field: 'email' },
  });
}

Throw GraphQLError with an extensions code so clients can handle failures precisely.

Error Handling Example

const typeDefs = gql`
  type Query { hello: String! }
`;
const resolvers = { Query: { hello: () => 'world' } };
const server = new ApolloServer({ typeDefs, resolvers });

• Start from a minimal Error Handling example and grow it only as needed.
• Keep configuration explicit so Error Handling behaves the same in every environment.
• Name things clearly so teammates understand your Error Handling at a glance.
• Add tests around Error Handling early to lock in expected behaviour.

GraphQL Cheatsheet

Quick GraphQL reference related to error handling.

How Error Handling Works in GraphQL

Error Handling fits into GraphQL's model of a single typed schema that clients query for exactly the data they need. The server resolves each requested field through resolver functions.

Throw GraphQLError with an extensions code so clients can handle failures precisely.

• The schema is the contract between client and server.
• Resolvers fetch data field by field, including nested types.
• Clients request only the fields they use, avoiding over-fetching.
• Context carries auth and shared services into every resolver.

Practical Guidance for Error Handling

In production, error handling should be efficient and secure. Batch data access with DataLoader, guard resolvers with authorization, and limit query depth and complexity.

Common Mistakes

• Skipping error handling and edge cases when wiring up error handling.
• Leaving error handling untested, so regressions slip into production.
• Over-engineering error handling before you actually need the extra flexibility.
• Ignoring documentation, which makes error handling hard for the next developer to change.

Key Takeaways

• Error Handling is a core part of working effectively with GraphQL.
• Start small and keep error handling focused on a single responsibility.
• Apply consistent patterns so error handling scales across your project.
• Test and document error handling to keep it maintainable over time.