Tag: graphql

Build a production-ready GraphQL API with type-safe schemas, resolvers, and query optimization in Python, JavaScript, and Java.

How to build a production-ready GraphQL API using Apollo Server, TypeScript, and DataLoader to solve the N+1 query problem

Define custom GraphQL scalars for Date, Email, URL, and JSON fields with serialization, parsing, and validation logic

Use DataLoader to coalesce individual load requests into batched database calls, solving the N+1 query problem in GraphQL resolvers

Implement field-level authorization in GraphQL using custom schema directives that check user roles and permissions per field

Implement structured error handling in GraphQL with custom error classes, extension codes, and consistent error formatting for clients

Compose multiple GraphQL services into a single federated supergraph using Apollo Federation and a gateway that routes queries across subgraphs

Implement centralized input validation in GraphQL using custom validation functions, Zod schemas, and input type transforms

Set up mocked GraphQL resolvers with Apollo Server so frontend teams can develop against a fake API before the backend is ready

Identify N+1 query problems in GraphQL resolvers using logging, DataLoader, and query analysis tools before they hit production

Implement Relay-style cursor pagination in GraphQL with edges, nodes, and pageInfo for efficient forward and backward traversal

Implement GraphQL subscriptions over WebSockets with Apollo Server and PubSub for real-time updates pushed to connected clients

How to use Mock Service Worker (MSW) to intercept network requests in JavaScript tests and development, including REST and GraphQL mocking.

Create dedicated backend services tailored to the specific needs of each frontend client type, aggregating downstream APIs and optimizing data shapes per platform.

Implement Relay-style cursor-based pagination with edges, nodes, and pageInfo for stable GraphQL list queries.

Share entity types across federated GraphQL services so the gateway can resolve fields from multiple subgraphs transparently.

Centralize input validation for GraphQL mutations using custom validators, schema directives, and structured error responses.

A guideline for standardizing error responses, status codes, and error payloads across REST and GraphQL APIs.

Internal guidelines for designing GraphQL APIs: schema structure, naming, mutation patterns, error handling, pagination, authentication, rate limiting, versioning, and federation rules with code examples.

Policy template for deprecating GraphQL fields, types, arguments, and enum values safely. Includes deprecation timeline, communication plan, usage tracking, removal criteria, and migration examples.

Template for onboarding a service to a federated GraphQL graph: subgraph setup, entity definitions, resolver configuration, gateway integration, testing, deployment, and monitoring with code examples.

Checklist for reviewing GraphQL schemas: naming conventions, type design, pagination, error handling, security, performance, deprecation, and federation readiness with code examples and validation rules.

Version REST and GraphQL APIs with URI, header, query param, and content negotiation strategies. Covers deprecation, sunset, and migration patterns.

Cache GraphQL responses at every layer: CDN, gateway, DataLoader, persisted queries, and client-side. Covers cache keys, invalidation, HTTP caching directives, and Apollo Client cache.

Build unified GraphQL APIs across multiple services with Apollo Federation. Covers subgraphs, supergraph composition, entity resolution, and gateway deployment.

Run federated GraphQL in production with confidence. Covers subgraph composition, gateway deployment, entity resolution, schema coordination, observability, and failure handling.

Design GraphQL schemas for evolution, performance, and maintainability. Covers type design, connections, mutations, error handling, deprecation, and schema-first vs code-first workflows.

Secure GraphQL APIs against introspection leaks, query depth attacks, cost-based DoS, batching abuse, and injection. Covers auth patterns, rate limiting, and production hardening.

Test GraphQL APIs at every layer: unit tests for resolvers, integration tests for schema, E2E tests for operations. Covers mocking, fixtures, snapshot testing, and performance testing.

A decision guide comparing GraphQL and REST APIs: use cases, performance, caching, tooling, and migration strategies for engineering teams.