On Anomaly Detection and Root Cause Analysis of Microservice Systems

Autor:	Pengfei Chen, Jinjin Lin, Zijie Guan
Rok vydání:	2019
Předmět:	Causal graph Source code Computer science media_common.quotation_subject Inference Monitoring system Root cause computer.software_genre Graph (abstract data type) Anomaly detection Data mining Root cause analysis computer media_common
Zdroj:	Lecture Notes in Computer Science ISBN: 9783030176419 ICSOC Workshops
DOI:	10.1007/978-3-030-17642-6_45
Popis:	In this demonstration, we design and implement a prototype of proof for causal graph building, anomaly detection and root cause analysis of microservice systems. The system comprises two core functionalities: (i) monitoring of systems and services; (ii) Application anomaly detection and root cause analysis. In the first part, the key metrics for the health of a system and an application, are collected by backend and plotted with dynamic charts in the frontend, which can help operators spot the overall system status. In the second part, the system can automatically build a causal graph of the microservice applications, indicating the dependencies between different modules, without instrumenting any source code. When an anomaly of a service instance is detected, it will be highlighted in the graph. A root cause inference function is also applied to analyze the root cause and returns a ranked list of root cause candidates to operators.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::455938796396c65023e702cbfcc92e60 https://doi.org/10.1007/978-3-030-17642-6_45 Zobrazit plný text záznamu