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Today, virtualization technologies play a critical role in the information technology sector, enabling businesses to manage their infrastructures more efficiently and flexibly. However, the complex structure and extensive feature set of virtualization programs often lead users to encounter error codes and technical issues. This can result in significant time losses and decreases in productivity, especially for inexperienced users. To address these challenges quickly and effectively, the IT sector is increasingly focusing on integrated solutions developed with artificial intelligence and smart assistant technologies. This study introduces the "VMware Assistant" software, designed to address technical issues related to VMware products. VMware Assistant utilizes pre-trained AI models, APIs from various websites, and comprehensive error and warning datasets to automatically detect and provide real-time solutions for user issues. The system aims to alleviate the complexities associated with virtualization programs and offer practical support to users. VMware Assistant consolidates error and warning data from multiple sources, enabling users to swiftly access the information they need. As a result, it accelerates the resolution process for technical issues encountered in virtualized environments, allowing users to maintain workflow continuity. VMware Assistant was developed to facilitate the use of virtualization technologies, potentially enhancing productivity in the IT sector and contributing to technical support processes.
API integration Artificial intelligence Error detection Virtualization VMware.
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Birincil Dil | İngilizce |
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Konular | Bilgi Temsili ve Akıl Yürütme, Planlama ve Karar Verme |
Bölüm | Araştırma Makalesi |
Yazarlar | |
Proje Numarası | 1 |
Yayımlanma Tarihi | 30 Aralık 2024 |
Gönderilme Tarihi | 14 Kasım 2024 |
Kabul Tarihi | 28 Aralık 2024 |
Yayımlandığı Sayı | Yıl 2024 Cilt: 4 Sayı: 2 |
Advances in Artificial Intelligence Research is an open access journal which means that the content is freely available without charge to the user or his/her institution. All papers are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which allows users to distribute, remix, adapt, and build upon the material in any medium or format for non-commercial purposes only, and only so long as attribution is given to the creator.
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