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Discovery of Cloud Applications from Logs.

Authors :
Harutyunyan, Ashot
Poghosyan, Arnak
Bunarjyan, Tigran
Haroyan, Andranik
Harutyunyan, Marine
Harutyunyan, Lilit
Baloian, Nelson
Source :
Future Internet; Jun2024, Vol. 16 Issue 6, p216, 14p
Publication Year :
2024

Abstract

Continuous discovery and update of applications or their boundaries running in cloud environments in an automatic way is a highly required function of modern data center operation solutions. Prior attempts to address this problem within various products or projects were/are applying rule-driven approaches or machine learning techniques on specific types of data–network traffic as well as property/configuration data of infrastructure objects, which all have their drawbacks in effectively identifying roles of those resources. The current proposal (ADLog) leverages log data of sources, which contain incomparably richer contextual information, and demonstrates a reliable way of discriminating application objects. Specifically, using native constructs of VMware Aria Operations for Logs in terms of event types and their distributions, we group those entities, which then can be potentially enriched with indicative tags automatically and recommended for further management tasks and policies. Our methods differentiate not only diverse kinds of applications, but also their specific deployments, thus providing hierarchical representation of the applications in time and topology. For several applications under Aria Ops management in our experimental test bed, we discover those in terms of similarity behavior of their components with a high accuracy. The validation of the proposal paves the path for an AI-driven solution in cloud management scenarios. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19995903
Volume :
16
Issue :
6
Database :
Complementary Index
Journal :
Future Internet
Publication Type :
Academic Journal
Accession number :
178186790
Full Text :
https://doi.org/10.3390/fi16060216