Testing Production Forecasting Models: How Chronos and Toto Handle Real-World Telemetry

While most forecasting benchmarks focus on prediction accuracy alone, this comparison reveals why operational forecasting requires uncertainty bands that guide capacity planning and alert thresholds in spike-prone systems. Long-horizon forecasts with calibrated quantiles replace naive baselines and point predictions with confidence ranges teams can actually deploy. The zero-shot evaluation demonstrates that these models generalize effectively without labeled training data, making them immediately applicable to new monitoring systems.