GraphQL Future

on YouTube ↗32m

" summary

Recap of concrete results and experiments: an open spec plus a GraphQL.js reference and tools like GraphiQL, Relay and Apollo are driving multi-language adoption; a production feature called graph batch reduces round trips while defer/stream directives and a live proposal stream partial JSON patches so critical fields arrive early (defer/stream/live are experimental, not yet broadly productionized); an event-based subscriptions system (MQTT + internal pub/sub) already runs at scale — about 150 billion subscribes per day and 35 billion payloads per day — and yields measurable engagement gains.

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" chapters (34)

1. 0:00Intro
2. 1:00Quick recap
3. 2:50Released GraphiQL last fall
4. 3:03Specification enables new Implementations
5. 4:30New GraphQL Services
6. 4:48GraphQL Ecosystem
7. 6:07Disclaimer: These are experiments
8. 6:22We only open source what we use.
9. 7:02Experiment in the open
10. 7:51Clients express what they need
11. 8:03Minimize network requests
12. 8:21Colocate data needs to views
13. 8:39Strong types
14. 9:24New Problems: 1. Time to important data 2. Real-time data updates
15. 10:27New Problem: Improve time to access the most important data.
16. 10:57Solution: Just send two network requests?
17. 11:48GraphQL Batch
18. 13:45Time to first Story
19. 14:11@stream
20. 14:57Many open questions
21. 15:56Solution: Repeated Polling
22. 16:27WebSockets, OMQ & Notifications
23. 17:22Reactive Backend
24. 20:18Non-reactive infrastructure
25. 20:56What about data dependencies?
26. 22:35Intricate data dependencies
27. 22:57Event-based subscriptions
28. 25:26What does the GraphQL look like?
29. 27:23Outside of Facebook?
30. 28:3535B daily payload deliveries
31. 28:51What are the use cases?
32. 29:26Batching
33. 30:34Increased engagement
34. 30:52GraphQL Subscriptions has enabled new product scenarios

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