What question did this study set out to answer?

To develop a predictive auto-scaling system on AWS that utilizes machine learning for improved resource management.

April 27, 2026Open Access

ML-Based Predictive Autoscaling on Aws

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Randomized trial demonstrates enhanced resource allocation in cloud computing, suggesting improved efficiency.

To develop a predictive auto-scaling system on AWS that utilizes machine learning for improved resource management.
Utilized Long Short-Term Memory (LSTM) models to analyze historical and real-time workload data.
Employed federated learning to train models across distributed cloud nodes without sharing raw data.
Proactively scaled AWS EC2 instances using Auto Scaling Groups based on workload predictions.
Improved application responsiveness and reduced latency observed.
Optimized resource utilization while lowering operational costs observed through implementation.
Achieved a more efficient and privacy-preserving solution for cloud resource management.

Panchetti et al. (2026) studied this question.

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