Microservices Architecture and Data Consistency: So How Do We Do It for Real?

on YouTube ↗47m

" summary

Compares two concrete approaches for distributed-data consistency in microservices with runnable demos: MicroProfile LRA + Narayana uses synchronous HTTP lifecycle annotations (start/complete/compensate) across Quarkus/OpenLiberty services and covers invalid client, unknown destination, price-exceeded and timeout cases; Eeventuate Tram with CDC + Kafka uses an orchestration DSL, a transactional outbox (CDC) and Kafka messages for asynchronous sagas and compensations. Both examples use Postgres, discuss trade-offs (configuration complexity versus coupling), and provide about 1,600 lines of demo code to reuse.

AI-written summary · about

" chapters (13)

1. 0:00Introduction
2. 2:41Transaction ACID in-place
3. 3:09Did you say ACID?
4. 4:18Distributed ACID Transactions 2PC
5. 4:49Distributed ACID Transaction 2PC
6. 5:34A little less ACID please...
7. 6:33Coordination Principles
8. 7:14Solutions
9. 18:56A simple but ... model
10. 26:57Eventuate Architecture
11. 29:23Transactional messaging
12. 31:08Eventuate Database
13. 42:01To go further

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