In long-time running reliable software systems, as the demand for continuous execution time and task response speed increases, the redundant component needs to be instantly switched when failure occurs. However, reliability optimization is often conducted under the assumption that cold standby redundancy is only activated when all active components fail. This paper tackles the redundancy allocation problem for a mixed redundancy strategy with instant switching to ensure system reliability as well as performance. The redundancy allocation model is built to minimize redundancy configuration cost under the transient availability and job completion rate constraints. Two system performance metrics are analyzed on top of the state transition diagram using Markov-chain theory. A numerical method is used to compute the non-linear model, and a genetic algorithm is used to solve the optimization model based on the double-element encoding mechanism. Illustrative examples are presented to explain the analysis of system transient availability and job completion rate as well as the allocation result under constraints. Experiment results indicate that with the same redundancy, the job completion rate of systems with the new mixed strategy is higher than the systems with traditional strategy. Thus, different redundancy should be allocated for different kinds of redundancy strategies, even under the same constraints.