Blooming article · Vol 1 No 2 (2024)

Cloud Cost Optimization via Kubernetes Autoscaling and ARIMA Workload Prediction

DOI:

https://doi.org/10.5555/audhighasu.v1i2.6

Keywords:

cloud computing, Kubernetes, autoscaling, ARIMA, cost optimization

Abstract

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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Author Biography

  • Fajar Nugroho, Telkom University
    Spesialis cloud dan DevOps.