chore.py

import numpy as np
from statsmodels.tsa.holtwinters import ExponentialSmoothing

def forecast_storage_demand(historical_usage, periods_ahead=24):
    """
    Forecast storage utilization for the next N hours using
    Holt-Winters exponential smoothing.
    """
    model = ExponentialSmoothing(
        historical_usage,
        trend="add",
        seasonal="add",
        seasonal_periods=24
    ).fit()

    forecast = model.forecast(periods_ahead)
    return forecast

def should_scale(forecast, current_capacity, safety_margin=0.15):
    peak_demand = np.max(forecast)
    threshold = current_capacity * (1 - safety_margin)
    return peak_demand > threshold

# Example usage
historical_usage = load_hourly_usage_metrics()  # returns array of TB used per hour
forecast = forecast_storage_demand(historical_usage)

if should_scale(forecast, current_capacity=500):
    provision_additional_capacity(target_tb=100)