Models and Technologies for Autoscaling Based on Machine Learning for Microservices Architecture

- Semerikov, Serhiy O. (orcid.org/0000-0003-0789-0272), Zubov, Dmytro (orcid.org/0000-0002-5601-7827), Kupin, Andrey (orcid.org/0000-0001-7569-1721), Kosei, Maxim (orcid.org/0009-0008-3445-5675) and Holiver, Vladyslav P. (orcid.org/0000-0002-8276-5992) (2024) Models and Technologies for Autoscaling Based on Machine Learning for Microservices Architecture Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Systems. Lviv, Ukraine, April 12-13, 2024, 1 (3664). pp. 316-330. ISSN 1613-0073

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Abstract

The subject of the research in the article is machine learning processes in web service systems used for providing online services. The subject of the study is methods and tools for auto-scaling these web services using machine learning. The evolution of web services, their structure including development history, scaling options, key concepts of microservices architecture, and general principles of artificial intelligence and machine learning are analyzed, providing an important foundation for understanding technological innovations and potential enhancements for web services. The most significant aspects of applying machine learning in microservices architecture are identified, including various design patterns and machine learning models, which form the basis for improving the efficiency and capabilities of complex systems. Relevant mathematical models and necessary software are proposed.

Item Type:	Article
Keywords:	Microservices architecture, artificial intelligence, machine learning, deep learning, SAGA, CRUD, CQRS, API gateway, circuit breaker, Python, containers, Docker, Ubuntu.
Subjects:	Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.4 Software Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.7 Computer communication. Computer networks
Divisions:	Institute for Digitalisation of Education > Department of the Cloud-Вased Systems of ICT in Education
Depositing User:	Сергій Олексійович Семеріков
Date Deposited:	18 Jul 2024 16:34
Last Modified:	18 Jul 2024 16:36
URI:	https://lib.iitta.gov.ua/id/eprint/741772

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