Strategy for Early Recognition and Proactive Handling of Disruptions Regarding the Service of Computer Centres and IT Infrastructures Based on Statistical Methods

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Abstract

Ensuring smooth operations of data centres is key to a company’s success. This endeavour is becoming more and more difficult. Given the continuously increasing amount of data, realtime demands and continuous system availability requirements, the Information Technology (IT) infrastructure is increasingly becoming more and more complex and unmanageable. Humans are not able to manually identify in time the breakdowns of the IT systems, let alone predict or avoid them. Hence, there is a need for an overall strategy regarding the early recognition or rather, the avoidance of outages. In the focus of our attention are technologies in the area of artificial intelligence, data analytics, anomaly detection, logging, and parsing, etc. We define an overall strategy in this regard, such that by automating and/or reducing routine activities the support team can concentrate its activity on setting up leading edge technologies rather than relying on the individual skills of some team members in fixing or preventing the failures. To conclude, our strategy supports a paradigm shift from more or less subjectively designed individualistic conceptions in handling of disruptions regarding the service of computer centres and IT infrastructures towards objectively established optimal solutions.

Details

Original languageEnglish
Title of host publicationICSEA 2022
EditorsLuigi Lavazza
PublisherIARIA - International Academy, Research, and Industry Association
Pages93-101
Number of pages9
ISBN (electronic)978-1-61208-997-3
Publication statusPublished - 16 Oct 2022
Peer-reviewedYes

Publication series

SeriesICSEA: International Conference on Software Engineering Advances
ISSN2833-8529

Conference

Title17th International Conference on Software Engineering Advances
Abbreviated titleICSEA 2022
Conference number17
Duration16 - 20 October 2022
Website
Degree of recognitionInternational event
LocationMercure Lisboa
CityLisboa
CountryPortugal

External IDs

ORCID /0009-0009-9342-629X/work/193863860

Keywords

Research priority areas of TU Dresden

Subject groups, research areas, subject areas according to Destatis

Keywords

  • Compute centre, Data Analytics, Statistical methods, Anomaly detection, Artificial Intelligence, Trend analysis, Failure diagnosis, Failure prevention, Monitoring system, Event logs