  Efficiently exploiting servers in data centers requires performance analysis
methods that account not only for the stochastic nature of demand but also for
server heterogeneity. Although several recent works proved optimality results
for heterogeneity-aware variants of classical load-balancing algorithms in the
many-server regime, we still lack a fundamental understanding of the impact of
heterogeneity on performance in finite-size systems. In this paper, we consider
a load-balancing algorithm that leads to a product-form queueing model and can
therefore be analyzed exactly even when the number of servers is finite. We
develop new analytical methods that exploit its product-form stationary
distribution to understand the joint impact of the speeds and buffer lengths of
servers on performance. These analytical results are supported and complemented
by numerical evaluations that cover a large variety of scenarios.
