There is no denying the fact that many development efforts have to be spent on existing applications - legacy that is - which typically exhibit a monolithic design based on traditional tech stacks. Thus, affected companies strive to move towards distributed architectures and modern technologies. This talk introduces you to the strangler fig pattern, which aids a smooth and step-wise migration of monolithic applications into separate services. The practical part shows how to apply this pattern to extract parts of a fictional monolith into its own service by featuring: * Apache Kafka, the de-facto standard for event streaming * MongoDB and its official connector for Apache Kafka * plus Debezium, a distributed open-source change-data-capture platform After experiencing this talk, you have a better understanding and a concrete blueprint how to extract functionality from your monoliths, thereby gradually evolving into a (micro)service architecture and an en vogue tech stack.

1. Dissecting our Legacy
The Strangler Fig Pattern
with Apache Kafka, Debezium and MongoDB
Hans-Peter Grahsl
Technical Trainer
@hpgrahsl
Gunnar Morling
Software Engineer
@gunnarmorling

2. @gunnarmorling @hpgrahsl

3. @gunnarmorling @hpgrahsl
● Technical Trainer at NETCONOMY
● Independent Consultant & Engineer
● Confluent Community Catalyst
● MongoDB Champion
Hans-Peter Grahsl

4. @gunnarmorling @hpgrahsl
● Open source software engineer at Red Hat
○ Debezium
○ Quarkus
● Spec Lead for Bean Validation 2.0
● Java Champion
Gunnar Morling

5. @gunnarmorling @hpgrahsl
system migrations
are challenging
@hpgrahsl

6. @gunnarmorling @hpgrahsl
hard cut-overs
are very risky
@gunnarmorling

7. @gunnarmorling @hpgrahsl
BIG BANG
migrations often
doomed to failure
@hpgrahsl

8. @gunnarmorling @hpgrahsl
strangler fig
pattern to
the rescue
@gunnarmorling

9. @gunnarmorling @hpgrahsl
3 Strangler Fig Phases
Eliminate
Extract Co-Exist

10. @gunnarmorling @hpgrahsl
System Migration Goal
● gradually evolve from old into new
● support temporary coexistence
● avoid big bang cut-over
@hpgrahsl

11. @gunnarmorling @hpgrahsl
Detour: Log-based Change-Data-Capture
● captures INSERT/UPDATE/DELETE events by tapping into DB’s TX log
● changes propagated via Apache Kafka & Kafka Connect

12. @gunnarmorling @hpgrahsl
Detour: Data Change Events
● Message Key: table PK
● Message Value:
○ Old and new row state
○ Metadata on table, TX id, etc.
○ Operation type, timestamp
● Serialized as JSON, Avro, etc.

13. @gunnarmorling @hpgrahsl
Detour: Data Change Events
● Message Key: table PK
● Message Value:
○ Old and new row state
○ Metadata on table, TX id, etc.
○ Operation type, timestamp
● Serialized as JSON, Avro, etc.

14. @gunnarmorling @hpgrahsl
Detour: Data Change Events
● Message Key: table PK
● Message Value:
○ Old and new row state
○ Metadata on table, TX id, etc.
○ Operation type, timestamp
● Serialized as JSON, Avro, etc.

15. @gunnarmorling @hpgrahsl
CDC-based Strangler Fig Pattern

16. @gunnarmorling @hpgrahsl
CDC-based Strangler Fig Pattern

17. @gunnarmorling @hpgrahsl
CDC-based Strangler Fig Pattern

18. @gunnarmorling @hpgrahsl
CDC-based Strangler Fig Pattern

19. @gunnarmorling @hpgrahsl
CDC-based Strangler Fig Pattern

20. @gunnarmorling @hpgrahsl
CDC-based Strangler Fig Pattern

21. @gunnarmorling @hpgrahsl
CDC Pipeline Considerations
● data model leaking from monolith ?
● “1:1 replication” → building aggregates ?
● transactional boundaries in the monolith ?
@hpgrahsl

22. @gunnarmorling @hpgrahsl
Enhanced CDC Pipelines

23. @gunnarmorling @hpgrahsl
Enhanced CDC Pipelines

24. @gunnarmorling @hpgrahsl
Enhanced CDC Pipelines

25. @hpgrahsl
@gunnarmorling

26. @gunnarmorling @hpgrahsl
Wrapping Up
Strangler Fig Pattern Benefits
● incremental migration → “baby steps”
● pause or stop without losing spent efforts
● extraction steps ideally reversible
● rationale: ⚠ minimize risk ⚠
@hpgrahsl

27. @gunnarmorling @hpgrahsl
Resources
● MongoDB Connector for Apache Kafka: https://www.mongodb.com/kafka-connector
● Debezium Website: https://debezium.io/
● Demo Repository: https://bit.ly/ks21-am-sfp

28. Thank You!
Join our Live Q & A
Hans-Peter Grahsl
Technical Trainer
@hpgrahsl
Gunnar Morling
Software Engineer
@gunnarmorling

29. @gunnarmorling @hpgrahsl
Image Credits
in order of appearance:
@davidclode https://unsplash.com/photos/T49WTav4LgU
@mparzuchowski https://unsplash.com/photos/geNNFqfvw48
@florianolv https://unsplash.com/photos/ca7tJ48YD64
@mischievous_penguins https://unsplash.com/photos/wqAuyugJIeU
@jernejcic https://unsplash.com/photos/Oi31uKsnM1Q
@ahmad_elsafty https://unsplash.com/photos/x97saLWeMNI
@anniespratt https://unsplash.com/photos/t3IYuQZRDNE
@janoschphotos https://unsplash.com/photos/w9rYOScXf6E