Virtualized cloud systems are prone to performance anomalies due to various reasons such as 
resource contentions, software bugs, and hardware failures. In this paper, we present a 
PREdictive Performance Anomaly pREvention (PREPARE) system that provides automatic performance 
anomaly prevention for virtualized cloud computing infrastructures. PREPARE integrates online 
anomaly prediction, learning-based prevention inference, and predictive prevention actuation to 
minimize the performance anomaly penalty without human intervention. We have implemented PREPARE 
on top of the Xen platform and tested it on the NCSU’s Virtual Computing Lab using a commercial 
data stream processing system (IBM System S) and an online auction benchmark (RUBiS). The experimental 
results show that PREPARE can effectively prevent performance anomalies while imposing low overhead 
to the cloud infrastructure.