  We consider a queue with renewal arrivals and n exponential servers in the
Halfin-Whitt heavy traffic regime, where n and the arrival rate increase
without bound, so that a critical loading condition holds. Server k serves at
rate $\mu_k $, and the empirical distribution of the $\mu_k $ is assumed to
converge weakly. We show that very little information on the service rates is
required for a routing mechanism to perform well. More precisely, we construct
a routing mechanism that has access to a single sample from the service time
distribution of each of $n$ to the power of $1/2 + \epsilon $ randomly selected
servers, but not to the actual values of the service rates, the performance of
which is asymptotically as good as the best among mechanisms that have the
complete information on $ \mu_k $.
