Change Data Streaming Patterns in Distributed Systems @ Flink Forward 2021

Abstract:
Microservices are one of the big trends in software engineering of the last few years; organising business functionality in several self-contained, loosely coupled services helps teams to work efficiently, make the most suitable technical decisions, and react quickly to new business requirements.

In this session we'll discuss and showcase how open-source change data capture (CDC) with Debezium can help developers with typical challenges they often face when working on microservices. Come and join us to learn how to:

* Employ the outbox pattern for reliable, eventually consistent data exchange between microservices, without incurring unsafe dual writes or tight coupling
* Gradually extract microservices from existing monolithic applications, using CDC, the strangler fig pattern and Apache Flink
* Coordinate long-running business transactions across multiple services using CDC-based saga orchestration, ensuring such activity gets consistently applied or aborted by all participating services.

Event Page:
https://www.flink-forward.org/global-2021/conference-program#change-data-streaming-patterns-in-distributed-systems

Video Recording:
https://www.youtube.com/watch?v=JsihpvQEv2c

Demo Repository: https://github.com/hpgrahsl/flinkforward21

Transcript

1. Gunnar Morling Software Engineer, Red Hat @gunnarmorling Change Data Streaming Patterns in Distributed Systems Hans-Peter Grahsl Technical Trainer, Netconomy @hpgrahsl
2. #CDCPatterns @gunnarmorling @hpgrahsl … implemented using Change Data Capture Today’s Objectives
3. #CDCPatterns @gunnarmorling @hpgrahsl • Open source software engineer at Red Hat ◦ Debezium ◦ Quarkus • Spec Lead for Bean Validation 2.0 • Java Champion • @gunnarmorling Gunnar Morling
4. #CDCPatterns @gunnarmorling @hpgrahsl • Technical Trainer at NETCONOMY • Independent Engineer & Consultant • Confluent Community Catalyst • MongoDB Champion • @hpgrahsl Hans-Peter Grahsl
5. #CDCPatterns @gunnarmorling @hpgrahsl • Taps into TX log to capture INSERT/UPDATE/DELETE events • Propagated to consumers via Apache Kafka and Kafka Connect Debezium — Log-based Change Data Capture
6. #CDCPatterns @gunnarmorling @hpgrahsl Debezium in a Nutshell • A CDC Platform ▪ Based on transaction logs ▪ Snapshotting, filtering, etc. ▪ Outbox support ▪ Web-based UI • Fully open-source, very active community • Large production deployments
7. #CDCPatterns @gunnarmorling @hpgrahsl Debezium: Connectors • Stable ▪ MySQL ▪ Postgres ▪ MongoDB ▪ SQL Server ▪ Db2 ▪ Oracle • Incubating ▪ Vitess ▪ Cassandra
8. #CDCPatterns @gunnarmorling @hpgrahsl Debezium: Deployment Alternatives Embedded Engine and Debezium Server
9. #CDCPatterns @gunnarmorling @hpgrahsl Data Change Events • Old and new row state • Metadata on table, TX id, etc. • Operation type, timestamp
10. #CDCPatterns @gunnarmorling @hpgrahsl • Old and new row state • Metadata on table, TX id, etc. • Operation type, timestamp Data Change Events
11. #CDCPatterns @gunnarmorling @hpgrahsl • Old and new row state • Metadata on table, TX id, etc. • Operation type, timestamp Data Change Events
12. Outbox Pattern
13. #CDCPatterns @gunnarmorling @hpgrahsl • Services need to update their database, • send messages to other services, • and that consistently! Challenge: Microservices Data Exchange
14. #CDCPatterns @gunnarmorling @hpgrahsl “Dual writes” are prone to inconsistencies! Outbox Pattern
15. #CDCPatterns @gunnarmorling @hpgrahsl Outbox Pattern
16. #CDCPatterns @gunnarmorling @hpgrahsl Outbox Pattern
17. #CDCPatterns @gunnarmorling @hpgrahsl Outbox Pattern
18. #CDCPatterns @gunnarmorling @hpgrahsl Outbox Pattern
19. #CDCPatterns @gunnarmorling @hpgrahsl Outbox Pattern with enrichment from external system using Flink
20. #CDCPatterns @gunnarmorling @hpgrahsl Integrating Debezium With Apache Flink Debezium → Kafka Topic → Flink
21. #CDCPatterns @gunnarmorling @hpgrahsl Integrating Debezium With Apache Flink Flink CDC Connectors (Debezium Embedded Engine) → Flink
22. Strangler Fig Pattern
23. #CDCPatterns @gunnarmorling @hpgrahsl • Gradually evolve from old into new • Support temporary coexistence • Avoid big bang cut-over Challenge: Migrating Systems
24. #CDCPatterns @gunnarmorling @hpgrahsl CDC-based Strangler Fig Pattern
25. #CDCPatterns @gunnarmorling @hpgrahsl CDC-based Strangler Fig Pattern
26. #CDCPatterns @gunnarmorling @hpgrahsl CDC-based Strangler Fig Pattern
27. #CDCPatterns @gunnarmorling @hpgrahsl CDC-based Strangler Fig Pattern
28. #CDCPatterns @gunnarmorling @hpgrahsl CDC-based Strangler Fig Pattern
29. #CDCPatterns @gunnarmorling @hpgrahsl CDC-based Strangler Fig Pattern
30. #CDCPatterns @gunnarmorling @hpgrahsl CDC-based Strangler Fig Pattern
31. #CDCPatterns @gunnarmorling @hpgrahsl CDC-based Strangler Fig Pattern Demo Repo: https://bit.ly/ff21-sfp
32. #CDCPatterns @gunnarmorling @hpgrahsl • Incremental migration → “baby steps” • Pause or stop migration without losing spent efforts • Migration steps ideally reversible Rationale: ⚠ minimize risk ⚠ Benefits
33. #CDCPatterns @gunnarmorling @hpgrahsl CDC Pipeline Considerations • data model leaking from monolith ? • “1:1 replication” → building aggregates ?
34. #CDCPatterns @gunnarmorling @hpgrahsl Enhanced CDC Processing Single Message Transforms
35. #CDCPatterns @gunnarmorling @hpgrahsl Enhanced CDC Processing custom stream processing with Flink
36. #CDCPatterns @gunnarmorling @hpgrahsl Example: join with custom aggregation
37. #CDCPatterns @gunnarmorling @hpgrahsl Example: join with custom aggregation Flink Table API
38. #CDCPatterns @gunnarmorling @hpgrahsl Example: join with custom aggregation Flink SQL
39. Saga Pattern
40. #CDCPatterns @gunnarmorling @hpgrahsl • Multiple services need to act collaboratively to achieve a consistent outcome • Without 2-phase commit protocols • Ensure correctness in case of failures Challenge: Long-running Business Transactions
41. #CDCPatterns @gunnarmorling @hpgrahsl Saga Pattern
42. #CDCPatterns @gunnarmorling @hpgrahsl Saga Pattern Message Flow
43. #CDCPatterns @gunnarmorling @hpgrahsl Saga Pattern Compensation
44. #CDCPatterns @gunnarmorling @hpgrahsl Saga Pattern Configuration
45. #CDCPatterns @gunnarmorling @hpgrahsl Saga Pattern Execution Flow
46. #CDCPatterns @gunnarmorling @hpgrahsl Saga Pattern Execution Flow
47. #CDCPatterns @gunnarmorling @hpgrahsl Saga Pattern Execution Flow
48. #CDCPatterns @gunnarmorling @hpgrahsl Saga Pattern Expanding Partial Change Events with Flink
49. #CDCPatterns @gunnarmorling @hpgrahsl Saga Pattern Expanding Partial Change Events with Flink
50. Wrap-Up
51. #CDCPatterns @gunnarmorling @hpgrahsl • CDC: a powerful tool in the box for event-driven architectures • Debezium: open-source CDC for a variety of databases • Debezium + Apache Flink = ❤ Takeaways
52. #CDCPatterns @gunnarmorling @hpgrahsl • Outbox implementation https://debezium.io/blog/2019/02/19/reliable-microservices-data -exchange-with-the-outbox-pattern/ • Strangler fig pattern https://martinfowler.com/bliki/StranglerFigApplication.html • Saga implementation https://www.infoq.com/articles/saga-orchestration-outbox/ • Demo repo https://github.com/debezium/debezium-examples Resources
53. #CDCPatterns @gunnarmorling @hpgrahsl Q & A gunnar@hibernate.org @gunnarmorling 📧 grahslhp@gmail.com @hpgrahsl 📧 Thank You!
54. #CDCPatterns @gunnarmorling @hpgrahsl Unsplash https://unsplash.com/license © Pablo García Saldaña https://unsplash.com/photos/lPQIndZz8Mo © David Clode https://unsplash.com/photos/T49WTav4LgU © Aaron Burden https://unsplash.com/photos/GFpxQ2ZyNc0 © Nathan Dumlao https://unsplash.com/photos/wQDysNUCKfw © mari lezhava https://unsplash.com/photos/q65bNe9fW-w © Michał Parzuchowski https://unsplash.com/photos/Bt0PM7cNJFQ © Charles Forerunner https://unsplash.com/photos/3fPXt37X6UQ Flickr Attribution 2.0 Generic https://creativecommons.org/licenses/by/2.0/ © Thomas Kamann https://flic.kr/p/coa2c CC0 1.0 Universal Public Domain Dedication https://creativecommons.org/publicdomain/zero/1.0/ © Wall Boat https://flic.kr/p/Y6zkmX Attribution-ShareAlike 2.0 Generic https://creativecommons.org/licenses/by-sa/2.0/ © Andrew Hart https://flic.kr/p/dmjkSk Image Credits In Order of Appearance