Event Stream Processor
High-throughput event ingestion with staged transforms, consumer scaling, and full lifecycle visibility.
A streaming pipeline that routes events through configurable processing stages, manages consumer groups, handles dead letters, and builds rolling aggregates — all observable in real time.
Problem Space
High-volume event streams require reliable ingestion, multi-stage processing, consumer coordination, and dead-letter handling — with visibility into lag, throughput, and processing health at every stage.
System Design
A streaming pipeline with visual stage-by-stage processing, consumer group management, DLQ handling, replay controls, and rolling window aggregation. Full lifecycle visibility from ingestion to output.
System Components
Live Prototype
Interactive prototype — all data generated client-side with deterministic seeds.
Reference Performance
Reference benchmark: 4 event types, 2 consumer groups, transform + filter + aggregate stages. Measured consumer lag recovery after burst and DLQ re-drive throughput.
Deterministic seed · 60s window · Simulated workload · Local environment