Pooria Namyar and Arvin Ghavidel, University of Southern California; Daniel Crankshaw, Daniel S. Berger, Kevin Hsieh, and Srikanth Kandula, Microsoft; Ramesh Govindan, University of Southern California; Behnaz Arzani, Microsoft
Cloud providers install mitigations to reduce the impact of network failures within their datacenters. Existing network mitigation systems rely on simple local criteria or global proxy metrics to determine the best action. In this paper, we show that we can support a broader range of actions and select more effective mitigations by directly optimizing end-to-end flow-level metrics and analyzing actions holistically. To achieve this, we develop novel techniques to quickly estimate the impact of different mitigations and rank them with high fidelity. Our results on incidents from a large cloud provider show orders of magnitude improvements in flow completion time and throughput. We also show our approach scales to large datacenters.
