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  -