The original title is about distributed systems patterns learned from stock market data pipelines. Let me rewrite this for a mobile feed.

Short summary

Stock market data pipelines teach lessons applicable to any real-time system where downstream consumers make decisions: consistency matters as much as speed. Key patterns include fan-out with per-consumer sequencing, partitioning by logical identity to preserve causal order, and treating backpressure as a first-class design constraint. The article includes a sequence gap detection implementation showing how to catch dropped or duplicated messages explicitly.

• •Latency in market data pipelines is a correctness concern not just a performance metric
• •Fan-out with per-consumer sequencing and partitioning by logical identity preserves causal ordering
• •Backpressure must be explicit in the protocol to prevent unbounded buffers from becoming slow crashes

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