Name
Abstract | ||
|---|---|---|
•We explain the challenges related to root cause analysis in microservice architectures.•We design a framework to perform root cause analysis based on graph structures.•We show how our graph based approach is 19.41% more effective than a machine learning based method.•Our evaluation includes real experiments with three microservice architectures ranging from 25 to 56 containers. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.jss.2019.110432 | Journal of Systems and Software |
Keywords | Field | DocType |
SOA,Microservices,Root Cause Analysis,Containers,Graphs | Troubleshooting,Observability,Computer science,Root cause analysis,Testbed,Real-time computing,Software,Microservices,Knowledge base,Root cause,Distributed computing | Journal |
Volume | ISSN | Citations |
159 | 0164-1212 | 4 |
PageRank | References | Authors |
0.47 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alvaro Brandon | 1 | 6 | 1.85 |
| Marc Solé | 2 | 109 | 12.17 |
| Alberto Huélamo | 3 | 4 | 0.47 |
| David Solans | 4 | 4 | 0.47 |
| María S. Pérez | 5 | 403 | 47.42 |
| Victor Muntés-Mulero | 6 | 204 | 22.79 |