Balancing plays a vital role in cloud data centers to distribute traffic among instances of network functions or services. State-of-the-art load balancers dispatch traffic obliviously without considering the real-time utilization of service instances and therefore can lead to uneven load distribution and sub-optimal performance.In this paper, we design and implement Spotlight, a scalable and distributed load balancing architecture that maintains connection-to-instance mapping consistency at the edge of data center networks. Spotlight uses a new stateful flow dispatcher which periodically polls instances' load and dispatches incoming connections to instances in proportion to their available capacity. Our design utilizes a distributed control plane and in-band flow dispatching; thus, it scales horizontally in data center networks. Through extensive flow-level simulation and packet-level experiments on a testbed with HTTP traffic on unmodified Linux kernel, we demonstrate that compared to existing methods Spotlight distributes traffic more efficiently and has near-optimum performance in terms of overall service utilization. Compared to existing solutions, Spotlight improves aggregated throughput and average flow completion time by at least 20% with infrequent control plane updates. Moreover, we show that Spotlight scales horizontally as it updates the switches at O(100ms) and is resilient to lack of control plane convergence.
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