We use a stochastic fluid model (SFM) for a communication network node with finite buffer capacity processing two classes of traffic: one is uncontrolled and the other is subject to threshold-based buffer control. We derive gradient estimators for class-dependent packet loss and workload related performance metrics with respect to the threshold parameter. These estimators are shown to be unbiased and directly observable from a sample path without any knowledge of underlying stochastic characteristics of the traffic processes. This renders them computable in on-line environments and easily implementable for network management and control.