Distributed Async Await • A new programming model for the cloud

on YouTube ↗47m

" summary

Cloud async-await extends to multiple processes by persisting durable promises with stable IDs in a database so cross-process calls form one coherent call graph, propagating values and errors and enabling restart-and-resume semantics. Paper-backed scale: a 7-day Alibaba trace of 20,000 microservices shows 10% of call graphs exceed 40 hops. Practical limits: AWS Lambda 15‑minute timeouts and a 10→0 countdown that would run 2h15m if naive (twilio send ≈500ms) motivate the model. An SDK (available for JavaScript TypeScript Python plus optional server component, GitHub linked) implements the model and demonstrates recovery and call-graph repair in examples.

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" chapters (26)

1. 0:00Introduction
2. 1:12Highly distributed apps
3. 2:18From pets to cattle to family
4. 4:04Long-lived executions
5. 5:28Developer pain in distributed systems
6. 7:16Abstractions and dev experience
7. 9:48Recursive abstractions
8. 10:52Good vs bad abstractions
9. 11:33Distributed computing fundamentals
10. 12:39Evolution of programming models
11. 15:52Async/await basics
12. 16:56Shift to distributed programming
13. 18:21Distributed async/await solution
14. 19:48Key requirements
15. 20:29Durable executions
16. 23:42Limitations of durable systems
17. 24:46Extending async/await
18. 27:14Async/await core concepts
19. 30:29Async/await shortcomings
20. 34:42Formalizing distributed structure
21. 36:55Recovery formalization
22. 37:15Case study: local vs remote
23. 38:19Case study: countdown timer
24. 42:15Sequential vs event-driven problems
25. 46:08Distributed async/await for timer
26. 47:14Q&A

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