Evaluating the Effectiveness of Autoscaling Mechanisms in Dynamic Cloud Workload Environments
Keywords:
Cloud Computing, Autoscaling, Resource Management, Workload Prediction, Elasticity, Cloud InfrastructureAbstract
Autoscaling is a critical feature in cloud computing that enables automatic resource provisioning in response to fluctuating workload demands. With the exponential growth in cloud-native applications, ensuring system responsiveness while minimizing resource waste has become an operational priority. This paper evaluates various autoscaling mechanisms, focusing on their adaptability, cost-effectiveness, and performance consistency under dynamic workloads. By comparing rule-based, reactive, and predictive approaches, this study identifies key trade-offs in latency, scalability, and provisioning efficiency. A mixed-method analysis is employed, using both simulated and real-world cloud workload traces to assess the efficacy of autoscaling strategies under volatile traffic conditions..
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