Cloud Cost Optimization via Kubernetes Autoscaling and ARIMA Workload Prediction
DOI:
https://doi.org/10.5555/audhighasu.v1i2.6Keywords:
cloud computing, Kubernetes, autoscaling, ARIMA, cost optimizationAbstract
Cloud infrastructure costs often inflate due to over-provisioning. This study integrates ARIMA workload prediction with Kubernetes Horizontal Pod Autoscaler for proactive capacity adjustment. Experiments on a production cluster show 31.5% compute cost reduction without degrading the 99.9% availability SLA.
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Published
2024-12-20
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Copyright (c) 2024 Audhighasu Journal of Informatics
This work is licensed under a Creative Commons Attribution 4.0 International License.