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📨 Apache Kafka and Event-Driven Architecture

Interactive 3D pipeline of producers writing events onto a Kafka topic log and multiple consumers replaying them at their own offsets, with sliders for partition count and consumer lag.

Data Science3DModerate60 FPS

Producers write events onto a partitioned, append-only Kafka topic log while two independent consumers replay it at their own pace — watch a lagging consumer fall behind and get reset when it drops outside the retention window.

🔬 What It Demonstrates

Each partition is an ordered, offset-indexed log. Consumers never remove data — they just track a read offset, so a fast consumer and a slow one can read the exact same log independently, which is the essence of event-driven decoupling.

🎮 How to Use

Adjust the partition count, producer rate and the slow consumer's processing speed. Shrink the retention window or starve Consumer B to watch its offset expire and reset — a real Kafka failure mode called an offset out-of-range reset.

💡 Did You Know?

Kafka can sustain millions of events per second because partitions parallelize both writes and reads — each partition is only ever appended to by one producer thread and read independently by each consumer group.

⚙ Under the hood

Interactive 3D pipeline of topics, partitions and consumer groups where publishing events shows how Kafka's replayable log powers event-driven architecture.

apache-kafkaevent-driven-architecturemessage-queuesdata-streamingdistributed-systemspub-subdata-science

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install