This Time is Different An Perspective on Time Series Foundation Models

We introduce TOTO, a time series forecasting foundation model with 151 million parameters. TOTO uses a modern decoder-only architecture coupled with architectural innovations designed to account for specific challenges found in multivariate observability time series data. TOTO's pre-training corpus is a mixture of observability data, open datasets, and synthetic data, and is 4-10 larger than those of leading time series foundation models. Additionally, we introduce BOOM, a large-scale benchmark consisting of 350 million observations across 2,807 real-world time series. For both TOTO and BOOM, we source observability data exclusively from Datadog's own telemetry and internal observability metrics. Extensive evaluations demonstrate that TOTO achieves state-of-the-art performance on both BOOM and on established general purpose time series forecasting benchmarks.