Transforming from perpetual licence-based products to cloud-based services
Veljo, Mika (2024-11-14)
Veljo, Mika
M. Veljo
14.11.2024
© 2024 Mika Veljo. Ellei toisin mainita, uudelleenkäyttö on sallittu Creative Commons Attribution 4.0 International (CC-BY 4.0) -lisenssillä (https://creativecommons.org/licenses/by/4.0/). Uudelleenkäyttö on sallittua edellyttäen, että lähde mainitaan asianmukaisesti ja mahdolliset muutokset merkitään. Sellaisten osien käyttö tai jäljentäminen, jotka eivät ole tekijän tai tekijöiden omaisuutta, saattaa edellyttää lupaa suoraan asianomaisilta oikeudenhaltijoilta.
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202411146744
https://urn.fi/URN:NBN:fi:oulu-202411146744
Tiivistelmä
Software as a Service model provides numerous advantages compared to the classic on premise model. However, transforming an organization’s applications and data to a cloud model might not be a straightforward task. There are several technical, business, organizational and process issues to consider. In this thesis, the aim is to research what guidelines the literature provides for migrating to a cloud model and to explore how these guidelines could be integrated in a Decision Support System (DSS) that help making informed choices in the migration process.
To achieve this aim, the thesis consists of literature review on Software as a Service, cloud migration, and cloud selection methods to identify critical issues and guidelines for cloud migration. The research method used in this thesis is Design Science Research Method (DSRM). As a result of that method, an artefact is designed and created to monitor cloud services. In addition, a quality model, guidelines and a model for cloud migration process are presented. The models are results of literature review, but the literature review itself is part of the DSRM cycle. In addition, the guidelines and migration model also include some ideas and suggestions by the author of this thesis based on his own experience and observations.
The main results show that the artefact can provide assistance in the cloud selection process. Especially, it can be helpful when making decisions on what service provider and/or service to choose. The quality model presents a way of categorizing the data collected by the artefact. The guidelines offer some advice on technical, business, organizational and process related issues of cloud migration. They can be useful especially when considering starting the cloud migration process. The migration model divides cloud migration process into manageable steps, and it can be used as a basis for the migration project.
As suggested as future work, the best outcome of the artefact can be achieved when connected to more, for instance detailed data, as well as to advanced artificial intelligence (AI) methods for analysing this data, such as text-mining, or other suitable AI-based data analysis.
To achieve this aim, the thesis consists of literature review on Software as a Service, cloud migration, and cloud selection methods to identify critical issues and guidelines for cloud migration. The research method used in this thesis is Design Science Research Method (DSRM). As a result of that method, an artefact is designed and created to monitor cloud services. In addition, a quality model, guidelines and a model for cloud migration process are presented. The models are results of literature review, but the literature review itself is part of the DSRM cycle. In addition, the guidelines and migration model also include some ideas and suggestions by the author of this thesis based on his own experience and observations.
The main results show that the artefact can provide assistance in the cloud selection process. Especially, it can be helpful when making decisions on what service provider and/or service to choose. The quality model presents a way of categorizing the data collected by the artefact. The guidelines offer some advice on technical, business, organizational and process related issues of cloud migration. They can be useful especially when considering starting the cloud migration process. The migration model divides cloud migration process into manageable steps, and it can be used as a basis for the migration project.
As suggested as future work, the best outcome of the artefact can be achieved when connected to more, for instance detailed data, as well as to advanced artificial intelligence (AI) methods for analysing this data, such as text-mining, or other suitable AI-based data analysis.
Kokoelmat
- Avoin saatavuus [38865]