GraphQL mocking and why it is important for developer productivity.
summary
Claim: using contract-plus-examples mocking cuts developer wait time by letting frontends run in parallel with backends. Implementation uses Microcks with a Postman collection (Docker extension or Git importer), a schema registry, and Faker-based generators to produce endpoints that return live mock responses (demo returns ID and title, different UID each request). Team size is small (about five contributors), no-code updating via versioned artifacts works and the demo runs as shown.
AI-written summary · about
chapters (11)
- 0:00Introduction
- 0:23GraphQL mocking boosts productivity
- 3:52API development challenges
- 5:36Schemas and types as contracts
- 7:22Contracts with real-world examples
- 9:09Translating contracts into mocks
- 10:54Faking it with mocks
- 12:44Microcks for GraphQL mocking
- 15:15Microcks demo setup
- 23:03Mocking takeaways
- 26:58Q&A
related talks
30mIncrease Your Productivity With No Code GraphQL Mocking
22mA Mock Is a Promise: Making GraphQL Mocks Enforceable
49mIncreasing Team Productivity with Mock API Servers.
25mMock to start
22mMocking and automocking for tests and storybooks
34mSchema-Driven Testing with Mock Service Worker
22mStrategies for Generating Dynamic, Realistic Mocks for Messaging APIs
25mDevelop in parallel and ship earlier with OpenAPI and mocking
