Writing Stream Processors in Kotlin

on YouTube ↗33m

" summary

Shows migrating Kafka Streams Java code to Kotlin and claims Kotlin cuts ceremony and boosts readability using extension functions and concise closures. Demonstrates a home automation pipeline: WebSocket source → Kafka Connect → Kafka Streams that group by node ID, window 2s, count >3, emit to a notification topic, sink writes back to WebSocket to trigger lights. Uses RocksDB for local state, protobuf for payloads, and reports ~80–100 ms processing time and end-to-end under 500 ms, and that the Kotlin DSL compacts the code.

AI-written summary · about

" chapters (22)

1. 0:00Intro
2. 1:10Kafka
3. 1:40Kafka Architecture
4. 3:13Kafka Persistence
5. 4:22Kafka Messages
6. 6:25Event Streams
7. 7:40Compaction
8. 9:19Division
9. 12:10Home Automation
10. 13:05WebSocket
11. 14:55Jason
12. 15:45Serializer
13. 17:05Extreme Person
14. 18:30GroupBy
15. 22:00Improvements
16. 23:00Reusable Context
17. 24:10Configure StreamContext
18. 25:20StreamMotion Events
19. 27:00Why Kotlin
20. 27:20Engineering View
21. 28:50Team Leads View
22. 30:40Wrap Up

" related talks

• 31mEvent Streaming with Kafka StreamsViktor Gamov · Scale By the Bay 2020
• 51mStream Processing Smackdown: Kafka Streams vs. Apache FlinkViktor Gamov · Voxxed Days Ticino 2025
• 29mApache Kafka and the Next 700 Stream Processing SystemsJay Kreps · Strange Loop 2015
• 43mThe Stream Processor as a DatabaseJamie Grier · Flink Forward Berlin 2016
• 08mPREVIEW: Kafka Stream Processing for Everyone with KSQLNick Dearden · Kafka Summit San Francisco 2017
• 33mKafka streams at scaleDeepak Goyal · Rootconf 2019
• 49mLet’s Build a Streaming Data Pipeline!Robin Moffatt · DataXDay 2020
• 41mApache Kafka and ksqlDB in Action: Let’s Build a Streaming Data Pipeline!Robin Moffatt · All Things Open 2020