I don't work in fintech. But I keep coming back to financial infrastructure breakdowns the same way a structural engineer might study bridge collapses — not because the domain is glamorous, but because the failure modes are instructive in ways that generic distributed systems theory rarely is.
Here's the specific thing that keeps pulling me in: stock market data pipelines are one of the few places where latency isn't a quality-of-life concern. It's a correctness concern. That distinction changes everything about how you design.
Speed Is the Easy Part. Consistency Is the Hard Part.
Most developers who start thinking about real-time pipelines fixate on throughput and latency first. That's reasonable — those are the visible metrics. What's harder to see is the consistency problem lurking underneath.
In market data systems, you're not just trying to move prices fast. You're trying to guarantee that every subscriber sees every tick, in order, exactly once. Drop a message and a trading algorithm makes a decision on stale state. Deliver a duplicate and you might trigger a double execution. Deliver things out of order and the whole downstream model is operating on fiction.
