Implementing Predictive Scaling with Adaptive Neural Networks

## The Problem with Reactive Autoscaling Traditional CPU- and memory-threshold autoscaling reacts after performance degradation has already started. In enterprise software, sudden bursts in user activity or scheduled batch jobs demand proactive capacity provisioning. ## Adaptive Forecasting By training time-series neural networks on historical traffic shapes, seasonality, and calendar schedules, our platforms predict traffic surges 15 to 30 minutes in advance, spinning up isolated worker nodes before latency spikes occur.