It was difficult to balance the efficiency and accuracy of multi-mode life RBDO(reliability-based design optimization) of turbine blades with film holes in the presence of random uncertainty, a quasi-sequence decoupling method of RBDO based on adaptive Kriging surrogate model was proposed. The construction process of the limit state surface surrogate model in reliability constraint was updated in real time with the search iteration of the design parameters, and the surrogate model strictly ensured the accuracy of surrogate model and feasible region judgment in each iteration step. The proposed method avoided updating the limit state surface in non-access domain of design parameters, so that obtaining a high convergence speed and strong robustness. The embedded real-time update strategy builds a cooperative surrogate model in the extended space and shares training sample points, and adaptively trains the Kriging model of the objective function until convergence, so that it is able to ensure the surrogate accuracy and significantly improve the optimization efficiency. In addition, an integrated and automatic simulation system for life reliability optimization is developed, which verifies the high efficiency and engineering feasibility of the proposed method and software in the turbine blade life RBDO problem.