Sampling for the Commodities and Services (C&S) component of the U.S. Consumer Price Index involves selection of outlets from establishment frames and individual items from a highly stratified item frame. The methodology employed in this process relies primarily on models of survey operation costs and sampling variance. These, in turn, are used to find local solutions to a nonlinear programming problem as a first-stage sample resource allocation. Explicit constraints in this setting involve a total survey cost ceiling as well as minimum sample size requirements. However, there are additional important constraints that inform and challenge this process. This paper explores these constraints.