Evolving stochastic process, when interrupted at random epochs and reset to its initial condition, reaches a new nonequilibrium stationary state. The approach to the stationary state is accompanied by an unusual `dynamical phase transition'. Moreever, the mean first-passage time to a fixed target becomes a minimum at an optimal value of the resetting rate. This makes the diffusive search process rather efficient. Resetting dynamics has been studied intensively in the last few years and is a rapidly emerging field in stochastic processes and nonequilibrium systems. In this talk, I'll give an overview of this evolving field.