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

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

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

OriginalspracheEnglisch
TitelICSEA 2022
Redakteure/-innenLuigi Lavazza
Herausgeber (Verlag)IARIA - International Academy, Research, and Industry Association
Seiten93-101
Seitenumfang9
ISBN (elektronisch)978-1-61208-997-3
PublikationsstatusVeröffentlicht - 16 Okt. 2022
Peer-Review-StatusJa

Publikationsreihe

ReiheICSEA: International Conference on Software Engineering Advances
ISSN2833-8529

Konferenz

Titel17th International Conference on Software Engineering Advances
KurztitelICSEA 2022
Veranstaltungsnummer17
Dauer16 - 20 Oktober 2022
Webseite
BekanntheitsgradInternationale Veranstaltung
OrtMercure Lisboa
StadtLisboa
LandPortugal

Externe IDs

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

Schlagworte

Forschungsprofillinien der TU Dresden

Fächergruppen, Lehr- und Forschungsbereiche, Fachgebiete nach Destatis

Schlagwörter

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