What does this equation mean?

Server-side deduplication only pays off if the retry that triggers it is well behaved, and naive retry timing defeats itself. If every failed client retries after exactly the same fixed delay, the retries arrive in synchronized waves and can overload a server that was only briefly struggling. AWS’s widely adopted answer is to randomise the delay rather than only grow it, and the simplest of the algorithms it documents, full jitter, is stated as $t_n = \mathrm{random}\!\left(0,\ \min\!\left(t_{\max},\ t_{\mathrm{base}} \cdot 2^{n}\right)\right)$. drawing the wait before attempt n uniformly between zero and a capped exponential ceiling, rather than sleeping for the ceiling itself [ 8 ] . The reasoning given is about contention, not just delay: without jitter, “N clients compete in the first round, N-1 in the second round” and so on, and even adding plain exponential backoff on top just moves the pile-up rather than removing it, since “there are still clusters of calls” — spikes at each retry boundary instead of one continuous overload [ 8 ] . Full jitter spreads those clusters into “an approximately constant rate of calls,” which is the property that actually protects a server under a retry storm [ 8 ] . The assumption this formula exposes is worth stating plainly: idempotency keys make a retry safe to execute twice; jitter is what keeps a wave of safe retries from arriving as a second incident in its own right.