With M(t):=sups.[0, t]A(s).s denoting the running maximum of a fractional Brownian motion A(.) with negative drift, this paper studies the rate of convergence of .(M(t)>x) to .(M>x). We define two metrics that measure the distance between the (complementary) distribution functions .(M(t)>.) and .(M>.). Our main result states that both metrics roughly decay as exp(..t2.2H), where . is the decay rate corresponding to the tail distribution of the busy period in an fBm-driven queue, which was computed recently [Stochastic Process. Appl. (2006) 116 1269.1293]. The proofs extensively rely on application of the well-known large deviations theorem for Gaussian processes. We also show that the identified relation between the decay of the convergence metrics and busy-period asymptotics holds in other settings as well, most notably when Gärtner.Ellis-type conditions are fulfilled.