The main objective of decision-making in a self-adaptive system (SAS) is to continuously satisfy its requirements under environmental uncertainty. As the run-time context changes, the system may need to re-configure itself by making trade-offs between the non-functional requirements (NFRs) based on their individual priorities for satisfaction. We demonstrate Pri-AwaRE as an approach to support priority-aware decision-making in SASs by providing explicit runtime modelling and reasoning of individual priorities of NFRs. The approach also supports autonomous tuning of the priorities under dynamic situations to maintain the required satisfaction levels of NFRs. In this paper, we showcase how Pri-AwaRE is used in a substantial industrial case study of Remote Mirroring using a simulation tool called RDMSim. Our results show that Pri-AwaRE offers the required satisfaction levels of NFRs by autonomously tuning of NFRs’ priorities according to new environmental contexts based on the data gathered at runtime.