Cloud computing and AI workloads are driving unprecedented demand for efficient communication within and across datacenters. However, the coexistence of intra- and inter-datacenter traffic within datacenters plus the disparity between the RTTs of intra- and inter-datacenter networks complicates congestion management and traffic routing. Particularly, faster congestion responses of intra-datacenter traffic causes rate unfairness when competing with slower inter-datacenter flows. Additionally, inter-datacenter messages suffer from slow loss recovery and, thus, require reliability. Existing solutions overlook these challenges and handle inter- and intra-datacenter congestion with separate control loops or at different granularities. We propose Uno, a unified system for both inter- and intra-DC environments that integrates a transport protocol for rapid congestion reaction and fair rate control with a load balancing scheme that combines erasure coding and adaptive routing. Our findings show that Uno significantly improves the completion times of both inter- and intra-DC flows compared to state-of-the-art methods such as Gemini.

This paper proposes and studies a system, called CloudFlex, which transparently taps cloud resources to serve application requests that exceed capacity of internal infrastructure. CloudFlex operates as a feedback control system with two key interacting components: load balancer and controller. We focus on operational optimality and stability of the system, highlight the tradeoffs between cost and responsiveness, and address important design considerations such as choke point detection that are critical in avoiding pathological system operations. For evaluation, we develop a prototype of CloudFlex on our testbed comprising servers of our enterprise data center and Amazon EC2 instances.