The advent of cloud computing as a means of offering virtualized computing and storage resources has radically transformed how modern enterprises run their business and has also fundamentally changed how today’s large cloud providers operate. For example, as these large cloud providers offer an increasing number of ever-more bandwidth-hungry cloud services, they end up carrying a significant fraction of today’s Internet traffic. In response, they have started to build-out and operate their private backbone networks and have expanded their service infrastructure by establishing a presence in a growing number of colocation facilities at the Internet’s edge. As a result, more and more enterprises across the globe can directly connect (i.e. peer) with any of the large cloud providers so that much of the resulting traffic will traverse these providers’ private backbones instead of being exchanged over the public Internet. Furthermore, to reap the benefits of the diversity of these cloud providers’ service offerings, enterprises are rapidly adopting multi-cloud deployments in conjunction with multi-cloud strategies (i.e., end-to-end connectivity paths between multiple cloud providers).

While prior studies have focused mainly on various topological and performance-related aspects of the Internet as a whole, little to no attention has been given to how these emerging cloud-based developments impact connectivity and performance in today’s cloud traffic-dominated Internet. This dissertation presents the findings of an active measurement study of the cloud ecosystem of today’s Internet. In particular, the study explores the connectivity options available to modern enterprises and examines the performance of the cloud traffic that utilizes the corresponding end-to-end paths. The study’s main contributions include (i) studying the locality of traffic for major content providers (including cloud providers) from the edge of the network (ii) capturing and characterizing the peering fabric of a major cloud provider, (iii) characterizing the performance of different multi-cloud strategies and associated end-to-end paths, and (iv) designing a cloud measurement platform and decision support framework for the construction of optimal multi-cloud overlays.