Title
A Framework of Virtual War Room and Matrix Sketch-Based Streaming Anomaly Detection for Microservice Systems.
Abstract
Recently, microservice has been a popular architecture to construct cloud-native systems. This novel architecture brings agility and accelerates the software development process significantly. However, it is not easy to manage and operate microservice systems due to their scale and complexity. Many approaches are proposed to automatically operate microservice systems such as anomaly detection. Nevertheless, those methods cannot be sufficiently validated and compared due to a lack of real microservice systems, which leads to the slow process of intelligent operation. These challenges inspire us to build a system named & x201C;VWR & x201D;, a framework of Virtual War Room for operating microservice applications which allows users to simulate their microservice architectures with low overhead and inject multiple types of faults into the microservice system with chaos engineering. VWR can mimic user requests and record the end-to-end tracing data (i.e., service call chains) for each request in a way consistent with OpenTracing. With easily designed tests and the produced streaming tracing data, the users can validate the performance of their intelligent operation algorithms and improve the algorithms as needed. Besides, based on the streaming tracing data generated by VWR, we introduce a novel unsupervised anomaly detection algorithm based on Matrix Sketch and set it as a default intelligent operation algorithm in VWR. This algorithm can detect anomalies by analyzing high-dimensional performance data collected from a microservice system in a streaming manner. The experimental result in VWR shows that the matrix sketch based method can precisely detect anomalies in microservice systems and outperform some widely used anomaly detection methods such as isolation forest in some scenario. We believe more approaches on the intelligent operation of microservice systems can be constructed based on VWR.
Year
DOI
Venue
2020
10.1109/ACCESS.2020.2977464
IEEE ACCESS
Keywords
DocType
Volume
Anomaly detection,Benchmark testing,Computer architecture,Complexity theory,Tools,Cloud computing,Microservice,virtual war room,matrix sketch,anomaly detection,chaos engineering
Journal
8
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Hongyang Chen157043.33
Pengfei Chen26213.05
Guangba Yu3112.61