Snapping shrimp dominate the high-frequency soundscape in warm coastal waters. The extremely impulsive and loud noise generated by these small creatures is a result of the collapse of cavitation bubbles they produce. With millions of snapping shrimp in most tropical coastal environments, the resulting cacophony disrupts underwater acoustic communication systems, sonars, and sensing systems. The resulting ambient noise is highly non-Gaussian, but can be modeled accurately by symmetric α-stable distributions. Optimal signal processing in such ambient noise is computationally infeasible, but near-optimal detectors and communication algorithms that we have developed over the past decades can help mitigate the effects of these noisy creatures on acoustic systems operating in warm shallow waters. The gains from use of such near-optimal algorithms is huge — in some cases yielding as much as 15-25 dB improvements in signal-to-noise ratio (SNR), as compared to using traditional Gaussian noise based signal processing algorithms.