When a failure occurs in production systems, the highest priority is to quickly mitigate it. Despite its importance, failure mitigation is done in a reactive and ad-hoc way: taking some fixed actions only after a severe symptom is observed. For cloud systems, such a strategy is inadequate. In this paper, we propose a preventive and adaptive failure mitigation service, NARYA, that is integrated in a production cloud, Microsoft Azure\u2019s compute platform. Narya predicts imminent host failures based on multi-layer system signals and then decides smart mitigation actions. The goal is to avert VM failures. Narya\u2019s decision engine takes a novel online experimentation approach to continually explore the best mitigation action. Narya further enhances the adaptive decision capability through reinforcement learning. Narya has been running in production for 15 months. It on average reduces VM interruptions by 26% compared to previous static strategy.<\/p>\n","protected":false},"excerpt":{"rendered":"
When a failure occurs in production systems, the highest priority is to quickly mitigate it. Despite its importance, failure mitigation is done in a reactive and ad-hoc way: taking some fixed actions only after a severe symptom is observed. For cloud systems, such a strategy is inadequate. In this paper, we propose a preventive and 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