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Maelstrom: Mitigating Datacenter-level Disasters by Draining Interdependent Traffic Safely and Efficiently | USENIX

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Kaushik Veeraraghavan, Justin Meza, Scott Michelson, Sankaralingam Panneerselvam, Alex Gyori, David Chou, Sonia Margulis, Daniel Obenshain, Shruti Padmanabha, Ashish Shah, and Yee Jiun Song, Facebook; Tianyin Xu, Facebook and University of Illinois at Urbana-Champaign We present Maelstrom, a new system for mitigating and recovering from datacenter-level disasters. Maelstrom provides a traffic management framework with modular, reusable primitives that can be composed to safely and efficiently drain the traffic of interdependent services from one or more failing datacenters to the healthy ones. Maelstrom ensures safety by encoding inter-service dependencies and resource constraints. Maelstrom uses health monitoring to implement feedback control so that all specified constraints are satisfied by the traffic drains and recovery procedures executed during disaster mitigation. Maelstrom exploits parallelism to drain and restore independent traffic sources efficiently. We verify the correctn

Kaushik Veeraraghavan, Justin Meza, Scott Michelson, Sankaralingam Panneerselvam, Alex Gyori, David Chou, Sonia Margulis, Daniel Obenshain, Shruti Padmanabha, Ashish Shah, and Yee Jiun Song, Facebook; Tianyin Xu, Facebook and University of Illinois at Urbana-Champaign We present Maelstrom, a new system for mitigating and recovering from datacenter-level disasters. Maelstrom provides a traffic management framework with modular, reusable primitives that can be composed to safely and efficiently drain the traffic of interdependent services from one or more failing datacenters to the healthy ones.

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