Step length adaptation is central to evolutionary algorithms in real-valued search spaces. This talk contrasts several step length adaptation algorithms for evolution strategies on a family of ridge functions. The algorithms considered are cumulative step length adaptation, a variant of mutative self-adaptation, two-point adaptation, and hierarchically organised strategies. In all cases, analytical results are derived that yield insights into scaling properties of the algorithms.