PROACTIVE RESOURCE MANAGEMENT IN A KUBERNETES CLUSTER USING AI-BASED RESOURCE USAGE PREDICTION IN THE CLOUD ENVIRONMENT

Authors

DOI:

https://doi.org/10.30890/2709-2313.2024-34-00-015

Keywords:

Kubernetes, proactive resource management, artificial intelligence, Prophet, LSTM, HPA, VPA, time series, cloud computing, load forecasting.

Abstract

The paper considers proactive resource management in a Kubernetes cluster using artificial intelligence methods, in particular, Prophet and LSTM algorithms. The relevance of the study is due to the shortcomings of traditional resource management mechanism

Metrics

Metrics Loading ...

Downloads

Published

2024-11-30

How to Cite

Tolbatov, A., Lozova, I., Tolbatova, O., Kukulevskyi, I., & Sokyrka, I. (2024). PROACTIVE RESOURCE MANAGEMENT IN A KUBERNETES CLUSTER USING AI-BASED RESOURCE USAGE PREDICTION IN THE CLOUD ENVIRONMENT. European Science, 2(sge34-02), 43–53. https://doi.org/10.30890/2709-2313.2024-34-00-015

Issue

No. sge34-02 (2024): Scientific research in modern conditions of instability '2024

Section

Chapters

License

Copyright (c) 2024 Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.