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/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
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
| Originalsprache | Englisch |
|---|---|
| Titel | ICSEA 2022 |
| Redakteure/-innen | Luigi Lavazza |
| Herausgeber (Verlag) | IARIA - International Academy, Research, and Industry Association |
| Seiten | 93-101 |
| Seitenumfang | 9 |
| ISBN (elektronisch) | 978-1-61208-997-3 |
| Publikationsstatus | Veröffentlicht - 16 Okt. 2022 |
| Peer-Review-Status | Ja |
Publikationsreihe
| Reihe | ICSEA: International Conference on Software Engineering Advances |
|---|---|
| ISSN | 2833-8529 |
Konferenz
| Titel | 17th International Conference on Software Engineering Advances |
|---|---|
| Kurztitel | ICSEA 2022 |
| Veranstaltungsnummer | 17 |
| Dauer | 16 - 20 Oktober 2022 |
| Webseite | |
| Bekanntheitsgrad | Internationale Veranstaltung |
| Ort | Mercure Lisboa |
| Stadt | Lisboa |
| Land | Portugal |
Externe IDs
| ORCID | /0009-0009-9342-629X/work/193863860 |
|---|
Schlagworte
Forschungsprofillinien der TU Dresden
DFG-Fachsystematik nach Fachkollegium
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