Flowable business processing from Kafka events

on YouTube ↗47m

" summary

Flowable directly ingests Kafka streams using a new event registry, channel adapters and inbound/outbound pipelines so modeled BPMN/CMMN elements start and correlate on real messages; the demo wires Spring Boot + Spring WebFlux + Kafka + Postgres and calls AWS Comprehend for sentiment, spawning one case per customer via a correlation hash and creating tasks for negative reviews. Race conditions use a triggerable service task (post-commit async send). The end-to-end demo runs and scales under simulated “frantic Friday” load.

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" chapters (51)

1. 0:00Introduction
2. 0:22Who are you
3. 0:51Agenda
4. 1:46Facts and highlights
5. 2:45Open standards
6. 4:16Standalone
7. 7:01Model centric
8. 7:47Runtime overview
9. 9:02Flowable architecture
10. 10:52REST API
11. 11:26Spring Boot Starter
12. 12:53MyMan
13. 16:09Eventdriven architectures
14. 17:11Design environment
15. 19:45Concepts
16. 22:36Use case
17. 23:04Customer reviews
18. 23:26Customer case
19. 24:14Bad review
20. 24:27Architecture
21. 24:55Demo
22. 25:45Architecture overview
23. 27:26Model overview
24. 27:46Case model
25. 28:08Review event
26. 28:48Active subscription
27. 30:17Handling support requests
28. 30:43Starting the process
29. 31:19Running the process
30. 31:40Running the process in Kafka
31. 32:19Review events
32. 32:38Review sentiment analysis
33. 33:42Review code
34. 34:15Push Kafka architecture
35. 34:26Spring Boot application
36. 34:39Spring Wet Flux endpoint
37. 35:04Customer demo
38. 35:15Customer case application
39. 35:27Dependency
40. 36:56Kafka API
41. 38:32Send Receive
42. 38:57Race Condition
43. 39:17Triggerable Service Tasks
44. 40:01Making Kafka events reactive
45. 40:45Calling AWS comprehend
46. 41:08Application overview
47. 41:52Cheating
48. 42:14Sentiment
49. 43:06Experiments
50. 44:07Create task
51. 44:23Send to Twitter

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