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Add kafka-streams module: fraud detection topology tested with TopologyTestDriver

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Similarity scoring, a 5-minute windowed count that alerts once, and a KTable
blocklist join, with the Spring wiring on Spring Boot 4.1.1 and Kafka Streams 4.2.1.

Co-Authored-By: Claude Sonnet 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01RjfyTgmERTWLqzafu34Cth
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asmhatre
2026-10-14 06:44:56 +00:00
co-authored by Claude Sonnet 5.5
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README.md
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@@ -16,6 +16,7 @@ directly under `output/` instead, with the equivalent depth in the article's own
| [`broker-comparison/`](broker-comparison/README.md) | [Kafka vs RabbitMQ vs Pulsar for Java Teams: A Decision Framework with Benchmarks](https://ankurm.com/kafka-vs-rabbitmq-vs-pulsar-java-decision-framework/) | The three brokers measured side by side on ordering, replay, consumer scaling and operational footprint, ending in a decision table where every row has a transcript behind it |
| [`saga/`](saga/README.md) | Saga Pattern in Spring Boot: Orchestration vs Choreography with Kafka | The same order/payment/inventory saga built twice against a real broker &mdash; choreography and orchestration &mdash; driven through the same inventory failure so the compensating transaction can be compared side by side, plus a real duplicate-delivery test for the idempotent-consumer problem |
| [`share-groups/`](share-groups/README.md) | [Queues for Kafka: Share Groups with Spring for Apache Kafka 4](https://ankurm.com/kafka-share-groups-spring-kafka-4-queues-for-kafka/) | Share groups against a real Kafka 4.3.1 broker: six consumers on two partitions, the acquire mode that decides whether they really share, the three acknowledgement types, a group that starts at the end of the topic, and the ordering you give up |
| [`kafka-streams/`](kafka-streams/README.md) | Kafka Streams with Spring Boot 4: Real-Time Fraud Detection with Vector Similarity | A fraud topology tested entirely under `TopologyTestDriver`: cosine-similarity scoring, a 5-minute windowed count that alerts exactly once, and a KTable blocklist join with a tombstone, plus the Spring wiring that needs no broker to load |
The brokers make an instructive set. Kafka's consumer holds an offset and the broker remembers
nothing about individual records; RabbitMQ's broker owns the message until it is acknowledged and