Build ML Enhanced Event Streaming Apps with Java Microservices
summary
Demonstrates a runnable Java microservice pipeline that ingests simulated tweets, runs a bundled NLP model inside a Pulsar Function, and writes labeled results to a tweets_out topic; uses Apache Pulsar 2.9.3, packages code as a Pulsar Functions NAR via Maven, and relies on BookKeeper for durable storage. The tweet source, function class, topic names and commands are shown and executed, processing works end-to-end and exposes metrics like average processing latency.
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chapters (18)
- 0:00intro
- 0:22preface
- 0:38about the speaker
- 1:06agenda
- 1:27event-driven microservices
- 3:00what is apache pulsar?
- 3:42pulsar pub/sub model
- 4:15topics
- 5:20physical architecture of a pulsar cluster
- 7:16what are pulsar functions?
- 8:15pulsar functions programming model
- 9:23why pulsar functions?
- 10:32when to use pulsar functions
- 11:21developing pulsar functions - sdk
- 12:32packaging functions
- 13:14coding demo
- 25:24review
- 26:06let's keep in touch
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