In the environment of energy saving and fierce peer competition， it is very urgent to optimize the power and performance optimization of application server clusters. Aiming at the deficiencies of the existing research in performance indicators and real-time performance， a real-time optimization scheme of cluster power and performance was proposed. This scheme combined the linear weighting method and the master objective method to optimize the cluster power and request drop rate， so converting the bi-objective optimization into a single-objective constrainted optimization. Firstly， based on the server load-power model in the CPU frequency equivalent continuous adjustment mode， the cluster optimization was described as a mixed integer quadratic programming problem by defining few variables. Then， variable splitting and variable conversion were used to transform the problem into a MILP （mixed integer linear programming） problem， and we introduced an SOS （special-Ordered set） constraint. Finally， the Gurobi optimizer was used to solve the MILP problem. Through further optimization of CPU frequency adjustment， the switching of CPU frequency was greatly reduced. Tests in various scenarios showed that the average solution time of the scheme was approximately 10 ms and the introduction of SOS constraint made the solution time more stable， which can ensure the real-time optimization.