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https://doi.org/10.21256/zhaw-29334Langanzeige der Metadaten
| DC Element | Wert | Sprache |
|---|---|---|
| dc.contributor.advisor | Wiedemann, Anna | - |
| dc.contributor.advisor | Scheppler, Björn | - |
| dc.contributor.author | Locher, Mario Gian | - |
| dc.date.accessioned | 2023-12-08T13:36:48Z | - |
| dc.date.available | 2023-12-08T13:36:48Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.uri | https://digitalcollection.zhaw.ch/handle/11475/29334 | - |
| dc.description.abstract | Digitalization and the accompanying technological change are forcing companies to constantly evolve. This also applies to IT operations, which must transform digitally. As cloud computing and infrastructure virtualization are standard in today’s IT environments, IT operations teams are faced with increased complexity. The vast amount of data produced cannot be managed by humans. Hence, they need to leverage advanced technologies to prevent and manage incidents that threaten the IT operation and thus also the company. Artificial Intelligence for IT Operations (AIOps) promises to solve today’s challenges in IT operations by incorporating Artificial Intelligence (AI) into widely used solutions in IT operations. AIOps should allow operations to move from a reactive to a proactive approach, identifying and managing incidents before they occur, while also allowing teams to build resilience into the system. The aim of this Master Thesis was to show how companies can benefit from using AIOps on their mission critical applications. Besides that, it should be shown how AIOps can be implemented in established IT departments. To provide a holistic view on the topic, challenges and limitations were also considered. As applying AI to IT operations does not in itself solve a business problem, a business AIOps alignment model is presented that should provide guidance for companies considering AIOps. To answer the research questions, a single case study was conducted in addition to a multivocal literature review on AIOps. The case study focused on a provider of AIOps solutions and its implementation partners. The interviews provided insight in the real-world adoption of AIOps. The findings of this work show that AIOps should rather be seen as a journey than as a specific technology. AIOps allows companies to move from a reactive IT operations approach to a proactive one. By freeing up time from operations teams, companies can focus on building resilience into the system, which is seen as the most successful incident prevention strategy. Although technology is already capable of predicting incidents in advance, this capability has not yet caught on in the market, largely because the data, processes, culture, and tools in organizations are not ready. Successfully adopting AIOps requires alignment to the business strategy which can be achieved using the presented business AIOps alignment model. Although aiming to solve today’s IT operations challenges, implementing AIOps holds organizational, cultural, and technological challenges. These challenges must be considered and overcome to successfully deploy AIOps and fully realize its potential. Properly implemented and deployed, AIOps helps organizations reduce the highly negative impact of incidents in their mission-critical applications. | de_CH |
| dc.format.extent | 94 | de_CH |
| dc.language.iso | en | de_CH |
| dc.publisher | ZHAW Zürcher Hochschule für Angewandte Wissenschaften | de_CH |
| dc.rights | http://creativecommons.org/licenses/by-nc-nd/4.0/ | de_CH |
| dc.subject.ddc | 004: Informatik | de_CH |
| dc.subject.ddc | 658: Allgemeines Management | de_CH |
| dc.title | Optimizing IT operations with AIOps : an investigation into the opportunities and challenges for enterprise adoption | de_CH |
| dc.type | Thesis: Master | de_CH |
| dcterms.type | Text | de_CH |
| zhaw.departement | School of Management and Law | de_CH |
| zhaw.publisher.place | Winterthur | de_CH |
| dc.identifier.doi | 10.21256/zhaw-29334 | - |
| zhaw.originated.zhaw | Yes | de_CH |
| Enthalten in den Sammlungen: | MSc Wirtschaftsinformatik | |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2023_Locher_Mario_MSc_IWI.pdf | 924.17 kB | Adobe PDF |  Öffnen/Anzeigen |
Zur Kurzanzeige
Locher, M. G. (2023). Optimizing IT operations with AIOps : an investigation into the opportunities and challenges for enterprise adoption [Master’s thesis, ZHAW Zürcher Hochschule für Angewandte Wissenschaften]. https://doi.org/10.21256/zhaw-29334
Locher, M.G. (2023) Optimizing IT operations with AIOps : an investigation into the opportunities and challenges for enterprise adoption. Master’s thesis. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. Available at: https://doi.org/10.21256/zhaw-29334.
M. G. Locher, “Optimizing IT operations with AIOps : an investigation into the opportunities and challenges for enterprise adoption,” Master’s thesis, ZHAW Zürcher Hochschule für Angewandte Wissenschaften, Winterthur, 2023. doi: 10.21256/zhaw-29334.
LOCHER, Mario Gian, 2023. Optimizing IT operations with AIOps : an investigation into the opportunities and challenges for enterprise adoption. Master’s thesis. Winterthur: ZHAW Zürcher Hochschule für Angewandte Wissenschaften
Locher, Mario Gian. 2023. “Optimizing IT Operations with AIOps : An Investigation into the Opportunities and Challenges for Enterprise Adoption.” Master’s thesis, Winterthur: ZHAW Zürcher Hochschule für Angewandte Wissenschaften. https://doi.org/10.21256/zhaw-29334.
Locher, Mario Gian. Optimizing IT Operations with AIOps : An Investigation into the Opportunities and Challenges for Enterprise Adoption. ZHAW Zürcher Hochschule für Angewandte Wissenschaften, 2023, https://doi.org/10.21256/zhaw-29334.
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