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The paper presents DeepScaling, an auto-scaling framework designed to optimize CPU utilization in large-scale cloud systems while meeting Service Level Objectives (SLOs). It introduces innovative components such as a workload forecaster and a CPU utilization estimator, improving upon traditional rule-based and learning-based auto-scaling methods. Experimental results demonstrate that DeepScaling significantly outperforms existing approaches, achieving stable CPU utilization and resource savings in real micr
- Author
- Yi Zheng
- Language
- EN