A Case for Performance- and Cost-Aware Multi-Cloud Overlays

Modern enterprises are increasingly adopting multicloud strategies (i.e. connecting islands of resources from disparate public cloud providers, or CPs for short) due to benefits such as competitive pricing, global expansion, or improved reliability. While these benefits are compelling in their own right, what is critically lacking is a framework for establishing optimized multi-cloud overlays atop individual CP backbones in a performance- and cost-aware manner. A key challenge is that we have little understanding of the performance characteristics of CPs' private backbones in light of multi-cloud overlays. To address this challenge, we present a third-party, cloud-centric study to understand and examine the path, delay, and traffic-cost characteristics of CP backbones by deploying VMs in three global-scale CPs (i.e. AWS, Azure, and GCP). Our measurements reveal new insights including the “optimal backbone of cloud backbones” and a lack of path and delay asymmetries in it. Next, we report on several instances where performance-awareness of multi-cloud paths offer better latency reductions than default paths provided by CPs. While these results make a strong case for performance-aware multi-cloud overlays, the problem is further complicated by the varying transit costs/pricing models of CPs across different geographic regions. Based on our findings, we propose a research agenda for creating performance- and cost-aware multi-cloud overlays that deals with issues such as egress costs, considering IXPs as relays, using cloud auctions for transit cost pricing, and improving the performance of cloud-native applications.