Incidents and outages dramatically degrade the availability of large-scale cloud computing systems such as AWS, Azure, and GCP. In current incident response practice, each team has only a partial view of the entire system, which makes the detection of incidents like fighting in the \u201cfog of war”. As a result, prolonged mitigation time and more finance loss are incurred. In this work, we propose an automatic incident detection system, namely Warden, as a part of the Incident Management (IcM) platform.Warden collects alerts from different services and detects the occurrence of incidents from a global perspective. For each detected potential incident, Warden notifies relevant on-call engineers so that they could properly prioritize their tasks and initiate cross-team collaboration. We implemented and deployed Warden in the IcM platform of Azure. Our evaluation results based on data collected in an 18-month period from 26 major services show that Warden is effective and outperforms the baseline methods. For the majority of successfully detected incidents ( 68%), Warden is faster than human, and this is particularly the case for the incidents that take long time to detect manually.<\/p>\n","protected":false},"excerpt":{"rendered":"
Incidents and outages dramatically degrade the availability of large-scale cloud computing systems such as AWS, Azure, and GCP. In current incident response practice, each team has only a partial view of the entire system, which makes the detection of incidents like fighting in the \u201cfog of war”. As a result, prolonged mitigation time and more 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