Page 2 - GraphQL

Intermittent GraphQL errors are hard to reproduce because context is missing. Structured logging, request tracing, and correlation IDs make every error traceable, even days after it occurred, even across multiple resolver chains.

Authentication in GraphQL is not a special case, it is part of every resolver that touches user-specific data. Anyone who fails to explicitly model token validation, session context and field-precise access control is building security gaps into the schema before the first query ever reaches production.

Untested GraphQL resolvers are a ticking time bomb: schema changes silently break frontend contracts, and authentication bugs stay hidden until production. This article shows how to test Magento GraphQL on three levels, from unit tests for resolver logic to real HTTP requests against the endpoint.

A GraphQL resolver that combines database queries, validation, permission checks and transformation logic in a single class is no longer a resolver, it is an unbounded mini-service. This article shows how to keep resolvers thin, introduce clear layers, and move business logic to where it actually belongs.

A GraphQL API without a complexity limit is an open door for overloading attacks. Depth limits, field-specific costs and complexity budgets are the three layers that stop a single query from occupying the server for seconds, or for minutes, if the schema has enough expensive fields.

Good GraphQL documentation is not a static file, it lives inside the schema itself, complemented by introspection tools, living example queries, deprecation strategies, and a schema registry workflow that makes changes communicable.

In production systems, GraphQL is not a query format, it is an architecture topic. Anyone who writes elegant queries but ignores resolver depth, N+1 problems, complexity limits and caching builds APIs that break under load. These 50 patterns show what actually works in real GraphQL projects.

A GraphQL schema without a review process evolves in an uncontrolled way: breaking changes, inconsistent naming conventions, and missing documentation creep in. This article shows which points should be checked before every merge, manually and automatically with tooling.

API Platform automatically generates GraphQL schemas from PHP entities, which sounds like the simplest possible solution. In practice, though, the limits show up quickly: complex mutations, domain-specific validation, N+1 performance problems, and a lack of control over the generated schema. This article shows when API Platform GraphQL is enough, and when it needs to be extended or replaced.

The right tool makes the difference between developing blind and maintaining an API in a structured way. GraphiQL, Apollo Studio, GraphQL Hive and Inspector cover different phases of the API lifecycle, from exploratory development to production schema management across a team.