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What We’re Building Today
Consumer group architecture with automatic partition assignment and rebalancing
Offset management strategies implementing at-least-once and exactly-once semantics
Multi-threaded processing pipeline with parallel log transformation and enrichment
Dead letter queue pattern for poison pill messages and retry exhaustion handling
Why This Matters
Consumer implementation determines your system’s throughput, reliability, and operational complexity. While producers are relatively simple—fire and forget with acks—consumers manage offset commits, rebalancing coordination, and state consistency across failures. At Netflix, consumer lag spikes directly correlate with degraded user experience as recommendations stale. Uber’s geospatial processing consumers must maintain exactly-once semantics to prevent duplicate ride assignments. The difference between naive polling loops and production consumer patterns is the gap between prototypes that process 500 events/second and systems handling 500,000 events/second with zero data loss.
