TY - CONF AU - Mormul, Mathias AU - Hirmer, Pascal AU - Stach, Christoph AU - Mitschang, Bernhard A2 - Khan, Latifur A2 - Huang, Gang T1 - DEAR: Distributed Evaluation of Alerting Rules T2 - Proceedings of the IEEE 13ᵗʰ International Conference on Cloud Computing PB - IEEE AD - Beijing Y1 - 2020/october SP - 158 EP - 165 M3 - https://doi.org/10.1109/CLOUD49709.2020.00034 KW - cloud monitoring; agent-based; alerting N2 - Cloud computing passed the hype cycle long ago and firmly established itself as a future technology since then. However, to utilize the cloud as cost-efficiently as possible, a continuous monitoring is key to prevent an over- or under-commissioning of resources. In large-scaled scenarios, several challenges for cloud monitoring, such as high network traffic volume, low accuracy of monitoring data, and high time-to-insight, require new approaches in IT Operations while considering administrative complexity. To handle these challenges, we present DEAR, the Distributed Evaluation of Alerting Rules. DEAR is a plugin for monitoring systems which automatically distributes alerting rules to the monitored resources to solve the trade-off between high accuracy and low network traffic volume without administrative overhead. We evaluate our approach against requirements of today's IT monitoring and compare it to conventional agent-based monitoring approaches. ER -