Online Phase Detection and Characterization of Cloud Applications

In this paper, we introduce a new methodology for automatic phase detection and characterization for applications running on the cloud. In contrast to existing approaches, our approach is novel in the fact that it is non-intrusive, more general (supports multiple programming languages), lightweight and can detect phase changes online as the application runs. We evaluate our approach for a number of C, C++ and Java application servers that are widely used in the cloud. Our method achieves a phase change detection accuracy upto 98.2% with an average detection delay of less than 0.01 seconds after the start or end of a phase. We also show a sample use case of our phase detection and characterization method for anomaly detection in the cloud.