Distributed service systems are ubiquitous, from server farms for cloud computing and charging stations for electric vehicles, to checkout lines at supermarkets and ICU beds in hospitals. The size of many of these systems has exploded over the past few years, which has created new challenges in the design of control policies. These new challenges, such as scalability, data locality, and server and task heterogeneity, have fueled a renewed interest in the study of these systems, and accelerated the introduction of more recent theoretical tools that opened new and exciting avenues of research around this topic. This workshop will focus on the application of new approaches and techniques from queueing theory, operations research, and machine learning to the control, design, and modeling of such distributed service systems.