The following papers published on Mendeley criticizes the MASF Gaussian
assumption and offer other methods (Tukey and
Relative Entropy) to detect anomalies statistically.

1. Statistical techniques for online anomaly detection in data centers

by , , , , ,

2. Online detection of utility cloud anomalies using metric distributions

*(BTW I tried to use the entropy analysis to capture performance anomalies - check my other post)*1. Statistical techniques for online anomaly detection in data centers

by , , , , ,

**Abstract**
Online anomaly detection is an important step in
data center management, requiring light-weight techniques that provide
sufficient accuracy for subsequent diagnosis and management actions.
This paper presents statistical techniques based on the Tukey and
Relative Entropy statistics, and applies them to data collected from a
production environment and to data captured from a testbed for
multi-tier web applications running on server class machines. The
proposed techniques are lightweight and improve over standard Gaussian
assumptions in terms of performance.

2. Online detection of utility cloud anomalies using metric distributions