The “Food Court Menu” of APIs: A GraphQL Introduction
summary
GraphQL claims to eliminate over‑ and under‑fetching by returning “no more, no less” via a schema described in SDL and served through resolvers; Intuit implements resolvers in Java Spring Boot using Netflix DGS and developers test queries in GraphiQL or Postman (POST with 200 and errors in the body). Schema composition uses either schema stitching or Apollo Federation; Intuit favors Federation for a migration across 7,000+ engineers while keeping REST/grpc for east‑west service traffic.
AI-written summary · about
chapters (8)
- 0:00Introduction
- 1:28REST vs GraphQL analogy
- 4:15GraphQL schema basics
- 6:20Querying data demo
- 8:08Building services with resolvers
- 10:12Schema composition solutions
- 13:00REST vs GraphQL pros and cons
- 16:27Learning resources
related talks
55mGraphQL - APIs the New Way
35mThe evolution of the GraphQL Orchestrator powering Intuit Consumer Apps
27mDesigning Secure GraphQL APIs : Not a Paradigm Shift but Handling Complexity
22mOrchestrating Microservices with GraphQL
37mGraphQL — A New Look at the API
16mIntro to GraphQL
19mGraphQL: Accelerating Digital Transformation Through Modern APIs.
41mDoes Your API Need a REST? Check Out GraphQL.