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Real-Time Event Streaming — Kafka + Spring Cloud Stream

Functional event-stream processing with Spring Cloud Stream and Kafka Streams: a supplier produces page events, a function transforms them, and a KStream pipeline applies 5-second sliding windows for real-time per-page analytics streamed to the browser via Server-Sent Events.

View Code
Kafka Streams
Streaming engine
5s sliding
Window size
SSE
Live transport
4
Functional beans
Approach

Functional supplier/function/consumer beans + windowed KStream aggregation streamed live over SSE

Tech Stack
Java 17Spring Boot 3.3Spring Cloud StreamApache KafkaKafka StreamsDocker Compose
Keywords
Apache KafkaKafka StreamsSpring Cloud StreamEvent-DrivenSSEDockerWindowing
Deep Dive

An event-driven pipeline built around the functional programming model of Spring Cloud Stream, with stateful Kafka Streams aggregations.

Pipeline

pageEvent1Supplier ──► topic R2 ──► pageEvent1Consumer (logs)
                                └─► pageEvent1Function (transform)
       StreamBridge
GET /publish/{topic}/{name} ─────► topic
                                     │
KStream1Function: filter ──► 5s sliding window ──► count by page ──► topic R4
                                                                       │
GET /analytics  ◄── Server-Sent Events ◄── interactive query (state store)

Functional beans

BeanTypeJob
pageEvent1SupplierSupplierEmits PageEvent1 to topic R2 continuously
pageEvent1ConsumerConsumerConsumes & displays events
pageEvent1FunctionFunctionTransforms events
KStream1FunctionKStreamFilters, windows (5s), counts by page → R4

Highlights

  • ▸Stateful windowed aggregation with interactive queries over the state store
  • ▸Real-time analytics pushed to the UI via Server-Sent Events
  • ▸Kafka brokers spun up with Docker Compose for one-command local dev
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