TY - GEN
T1 - Using Service Dependency Graph to Analyze and Test Microservices
AU - Ma, Shang Pin
AU - Fan, Chen Yuan
AU - Chuang, Yen
AU - Lee, Wen Tin
AU - Lee, Shin Jie
AU - Hsueh, Nien Lin
PY - 2018/6/8
Y1 - 2018/6/8
N2 - Microservice architecture (MSA) is an emerging software architectural style, which differs fundamentally from the monolithic, layered architecture. MSA is based on microservices to provide several advantages, such as autonomy, composability, scalability, and fault-tolerance. However, how to manage complex 'call' relationships between microservices is still a big issue that needs to be addressed. In this paper, we propose an approach for assisting the development of MSA-based systems, referred to as GMAT (Graph-based Microservice Analysis and Testing). GMAT can automatically generate 'Service Dependency Graph (SDG)' to analyze and visualize the dependency relationships between microservices. Using GMAT, people are able to detect anomalies by analyzing risky service invocation chains in early stage of development, and trace the linkages between services when developing a new version of a target system. Experiments show that GMAT is able to work well for both small-scale and large-scale MSA-based systems.
AB - Microservice architecture (MSA) is an emerging software architectural style, which differs fundamentally from the monolithic, layered architecture. MSA is based on microservices to provide several advantages, such as autonomy, composability, scalability, and fault-tolerance. However, how to manage complex 'call' relationships between microservices is still a big issue that needs to be addressed. In this paper, we propose an approach for assisting the development of MSA-based systems, referred to as GMAT (Graph-based Microservice Analysis and Testing). GMAT can automatically generate 'Service Dependency Graph (SDG)' to analyze and visualize the dependency relationships between microservices. Using GMAT, people are able to detect anomalies by analyzing risky service invocation chains in early stage of development, and trace the linkages between services when developing a new version of a target system. Experiments show that GMAT is able to work well for both small-scale and large-scale MSA-based systems.
UR - http://www.scopus.com/inward/record.url?scp=85055577947&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85055577947&partnerID=8YFLogxK
U2 - 10.1109/COMPSAC.2018.10207
DO - 10.1109/COMPSAC.2018.10207
M3 - Conference contribution
AN - SCOPUS:85055577947
T3 - Proceedings - International Computer Software and Applications Conference
SP - 81
EP - 86
BT - Proceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018
A2 - Demartini, Claudio
A2 - Reisman, Sorel
A2 - Liu, Ling
A2 - Tovar, Edmundo
A2 - Takakura, Hiroki
A2 - Yang, Ji-Jiang
A2 - Lung, Chung-Horng
A2 - Ahamed, Sheikh Iqbal
A2 - Hasan, Kamrul
A2 - Conte, Thomas
A2 - Nakamura, Motonori
A2 - Zhang, Zhiyong
A2 - Akiyama, Toyokazu
A2 - Claycomb, William
A2 - Cimato, Stelvio
PB - IEEE Computer Society
T2 - 42nd IEEE Computer Software and Applications Conference, COMPSAC 2018
Y2 - 23 July 2018 through 27 July 2018
ER -