How to Scale an Integration Pipeline Without Breaking Correctness

A practitioner's account of scaling an enterprise integration pipeline from 500 to 8,000 events per second without sacrificing correctness. Two invariants anchor everything: version-based last-write-wins to prevent stale overwrites, and transactionally-coupled dedup logging to guarantee exactly-once semantics. Techniques covered include entity-keyed partitioning with adaptive sub-partitioning for hot entities, micro-batching (100 records or 50ms) with per-record savepoints, and three-tier backpressure (self-throttling consumers, producer rate limits, priority-based load shedding). A real incident walkthrough shows circuit breakers, backpressure, and shedding working together during an ERP outage, with a reconciliation report of 23,000 events, 22,987 auto-replayed, 13 in DLQ, zero data loss. Closes by tying the approach to academic literature on skewed key partitioning, effectively-once semantics, and reactive backpressure.

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