Open AccessTelemetry Based Anomaly Detection and Correlation in Data Center
Author(s) -
Arun S Jois,
Jayasimha S. R
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.a2725.059120
Subject(s) - anomaly detection , downtime , telemetry , server , computer science , data center , anomaly (physics) , cloud computing , service (business) , real time computing , data mining , database , computer network , operating system , telecommunications , physics , economy , economics , condensed matter physics
Data center is a complex amalgamation of servers where there are thousands of services, storage, networking, routers, switches and softwares providing services 24x7 to cus- tomers. Services provided can range from websites, storage, cloud platform, Email marketing etc. A team is established to detach the anomaly generated from the monitoring system. Anomaly or issues in servers cause high downtime of service. Detecting these anomalies with high accuracy and performing Root cause analysis has been a major issue. The team often remediates the symptom than the anomaly. With the use of Artificial Neural networks a trained model can provide solutions with high accuracy and scalablility which result in higher uptime and reduced MTTR for customers.