High-volume alert systems are deceptively complex. At small scale, correlating alerts into incidents feels straightforward: group similar events within a time window and move on. But as throughput increases and distributed systems enter the picture, subtle sources of nondeterminism begin to creep in.
Events arrive out of order. Clocks drift. Network latency fluctuates. Goroutine scheduling changes across runs. Even Go’s randomized map iteration can alter decision paths. The result? The same set of alerts can produce different incident groupings depending on timing and execution order.