Chronos vs Toto: Zero-Shot Forecasting Benchmark Results
The article compares two forecasting models, Chronos and Toto, using telemetry data from Prometheus and OpenSearch. It evaluates their performance in a zero-shot setting, emphasizing the importance of accurate long-horizon forecasts for capacity planning. The analysis highlights the challenges of forecasting in observability due to the variability and unpredictability of real systems.
- ▪Chronos and Toto were tested on telemetry data to assess their forecasting capabilities.
- ▪The evaluation focused on point accuracy and the quality of uncertainty in forecasts.
- ▪Prometheus memory utilization showed stable behavior, while OpenSearch CPU demonstrated high volatility and frequent outliers.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3924679) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Parseable Team Posted on May 27 • Originally published at parseable.com Chronos vs Toto: Zero-Shot Forecasting Benchmark Results #chronos #dataengineering #observability Introduction Good forecasts help with capacity planning and quieter alerts. But one traffic spike or memory leak can make any forecast useless. The goal is simple: prove your forecast beats a naive baseline and stays reliable under uncertainty.
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