How Nextdoor improves their customer experience in real time with Apache Flink
summary
Built an Interaction Store that consumes Kinesis Data Streams, processes with Apache Flink on Kinesis Data Analytics, and writes to DynamoDB; state holds HyperLogLog sketches, snapshots run twice a day, and streams retain 24 hours for replay. Production deploy takes under three months. Key fixes: reduce OOMs with operator chaining and operator-level parallelism, cut DynamoDB cost spikes by switching to staggered processing windows, and smooth input with adaptive reads on the Kinesis consumer.
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chapters (11)
- 0:00Introduction
- 2:42kinesis Data Analytics
- 3:33How to build Apache Flink applications
- 4:23Key benefits of Apache Flink
- 4:34Introducing Eugene
- 4:47What is Nextdoor
- 5:28The problem
- 8:34Challenges
- 11:28Processing time windows
- 12:40Back pressure
- 15:05Conclusion
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