CENTILE: A Telemetry Foundation Model Evaluated by the Decisions It Drives
Modern computing and networking infrastructure emits telemetry continuously, yet operators convert it into decisions with a separate predictor per task, entity, and horizon. One generative model, pretrained once over an operator's own event streams, could replace this fleet, an approach that already scales to high-cardinality streams in recommendation systems. However, point-forecast error on operational telemetry saturates near simple last-value baselines, so lower error alone need not improve the decisions it feeds. To close this gap, we present \sys, a generative foundation model for network and systems telemetry, evaluated by replaying the decisions its calibrated conditional quantile...
| Authors | Zifan Zhang, Zhichao Hou, Tingxiang Ji et al. |
|---|---|
| Primary category | cs.NI |
| Published | 3 August 2026 |
| Last updated at source | 3 August 2026 |
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