In large-scale distributed execution environments such as multicluster systems and grids, resource availability may vary due to resource failures and because resources may be added to or withdrawn from such environments at any time. In addition, single sites in such systems may have to deal with workloads originating from both local users and from many other sources. As a result, application malleability, that is, the property of applications to deal with a varying amount of resources during their execution, may be very beneficial for performance. In this paper we present the design of the support of and scheduling policies for malleability in our Koala multicluster scheduler with the help of our Dynaco framework for application malleability. In addition, we show the results of experiments with scheduling malleable workloads with Koala in our DAS multicluster testbed.