Evolving the Graph

Coursera has had GraphQL in production for over three years now — here's the story of how we started, what things have stood the test of time, and what things haven't.

Transcript

1. Evolving the Graph GraphQL Conf 2019
2. jon wong @jnwng developer experience
4. we envision a world where anyone, anywhere can transform their life by accessing the world’s best learning experience.
5. (p.s., we're hiring in mountain view and toronto)
6. Evolving the Graph GraphQL Conf 2019
8. Evolving Our Graph GraphQL Conf 2019
9. DISCLAIMER Take everything beyond with a large Coursera- sized grain of salt. What works for our team may not work for yours.
10. Coursera has been using GraphQL for over three years!
11. GraphQL Three Years Ago We wanted a "data-first" solution to reflect our REST APIs in GraphQL
12. GraphQL Three Years Ago Clients were responsible for calling for the correct data for themselves.
13. The Tools (three years ago)
14. Federation
15. Code-first Schema Generation
16. Schema Stitching
17. Lessons Learned (three years later)
18. Federation
19. Federation meant teams could retain ownership over their services.
20. Federation with REST meant we only had one GraphQL resolver
21. Federation with REST meant you previewed changes in production.
22. Code-first Schema Generation
23. Code Generation It was really simple to get existing REST resources into our schema.
24. Code Generation It was really simple to get existing REST resources into our schema.
25. Code Generation ~ 7,546 types ~ 664 root fields
26. Schema Stitching
27. Schema Stitching Namespacing our types gave our graph room to grow. We have ~600+ distinct REST resources.
28. Schema Stitching We never had to figure out how to "deprecate" a field
29. Some things surprised us.
30. GraphQL clients are incredibly powerful For every feature our servers didn't have, our clients could add support.
31. Our implementation of GraphQL didn't look like GraphQL in the wild.
32. Our Biggest Realization
33. Is a data-first schema the best use of GraphQL?
34. The schema of your service is not always the same as the schema you want for your client.
37. Clients don't just need data, they need information.
38. Where We Go From Here
39. Optimizing for quality of schema over quantity of schema.
40. Coordination between engineers happens with GraphQL schemas as our common language.
41. We're vastly more intentional about what goes into the schema.
42. The graph doesn't evolve, people do.
43. Thanks! @jnwng