Contamination Map Methodology

Time series / Dataset

Pooled Server Metrics (PSM)

Multivariate server metrics collected internally from multiple application server nodes at eBay, released by eBay with RANSynCoders (Abdulaal et al., KDD 2021). The repository provides train.csv (no labels), test.csv and test_label.csv; the csv files have a minute timestamp column and 25 anonymised features (feature_0 to feature_24).

Also known as
PSM, Pooled Server Metrics, eBay PSM
Domain
IT operations (server monitoring)
License
CC BY 4.0 (data files; code BSD-3)
Test items from
2021-05-20
Evidence
“"created_at":"2021-05-20T20:36:21Z"”
api.github.com · code · GitHub API: repository creation date · retrieved 2026-10-15
“Pooled Server Metrics (PSM) dataset is in the folder `data`.”
raw.githubusercontent.com · readme · Get data · retrieved 2026-10-15
Homepage
github.com

Exposure by model

BenchmarkModelLevelReason
Time-series anomaly detection Chronos-2-Synth Not seen absent from the complete list of training data
Time-series anomaly detection Chronos-2 Not seen absent from the complete list of training data
Time-series anomaly detection Chronos-Bolt Unknown training data not disclosed in enough detail
Time-series anomaly detection Chronos (T5) Not seen absent from the complete list of training data
Time-series anomaly detection DADA (General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders) Not seen the authors state the dataset was excluded from training
Time-series anomaly detection Granite-TimeSeries-TTM-R1 Not seen absent from the complete list of training data
Time-series anomaly detection Granite-TimeSeries-TTM-R2.1 Not seen absent from the complete list of training data
Time-series anomaly detection Granite-TimeSeries-TTM-R2 Not seen absent from the complete list of training data
Time-series anomaly detection Granite-TTM-R3 Unknown training data not disclosed in enough detail
Time-series anomaly detection Lag-Llama Not seen absent from the complete list of training data
Time-series anomaly detection Mantis (Mantis-8M) Unknown training data not disclosed in enough detail
Time-series anomaly detection Mantis+ (MantisPlus) Not seen absent from the complete list of training data
Time-series anomaly detection MantisV2 Not seen absent from the complete list of training data
Time-series anomaly detection Moirai-1.0-R Not seen absent from the complete list of training data
Time-series anomaly detection Moirai-1.1-R Unknown training data not disclosed in enough detail
Time-series anomaly detection Moirai-2.0-R Unknown training data not disclosed in enough detail
Time-series anomaly detection Moirai-MoE-1.0-R Not seen absent from the complete list of training data
Time-series anomaly detection MOMENT-1 Unknown training data not disclosed in enough detail
Time-series anomaly detection NuTime Not seen absent from the complete list of training data
Time-series anomaly detection Sundial (Timer 3.0) Unknown training data not disclosed in enough detail
Time-series anomaly detection Time-MoE Unknown training data not disclosed in enough detail
Time-series anomaly detection Time-RCD (TimeRCD) Not seen absent from the complete list of training data
Time-series anomaly detection Timer-S1 Unknown training data not disclosed in enough detail
Time-series anomaly detection Timer-XL (timer-base-84m) Unknown training data not disclosed in enough detail
Time-series anomaly detection Timer Not seen absent from the complete list of training data
Time-series anomaly detection TimeRadar Not seen the authors state the dataset was excluded from training
Time-series anomaly detection TimesFM 1.0 Unknown training data not disclosed in enough detail
Time-series anomaly detection TimesFM 2.0 Unknown training data not disclosed in enough detail
Time-series anomaly detection TimesFM 2.5 Unknown training data not disclosed in enough detail
Time-series anomaly detection TimesFM 3.0 Unknown training data not disclosed in enough detail
Time-series anomaly detection TiRex 1.1 (gifteval) Unknown training data not disclosed in enough detail
Time-series anomaly detection TiRex-2-fevbench (TiRex-2-f) Not seen absent from the complete list of training data
Time-series anomaly detection TiRex-2-gifteval-pretrain (TiRex-2-gp) Unknown training data not disclosed in enough detail
Time-series anomaly detection TiRex-2-gifteval-zs (TiRex-2-g) Not seen absent from the complete list of training data
Time-series anomaly detection TiRex-2 Unknown training data not disclosed in enough detail
Time-series anomaly detection TiRex Not seen absent from the complete list of training data
Time-series anomaly detection Toto-Open-Base-1.0 Unknown training data not disclosed in enough detail
Time-series anomaly detection Toto-2.0-2.5B-FT Unknown training data not disclosed in enough detail
Time-series anomaly detection Toto 2.0 Unknown training data not disclosed in enough detail
Time-series anomaly detection Toto (2024 technical report) Unknown training data not disclosed in enough detail
Time-series anomaly detection TSPulse r1 Not seen absent from the complete list of training data
Time-series anomaly detection TTM-R3 Unknown training data not disclosed in enough detail
Time-series anomaly detection Tiny Time Mixer (TTM) Research-Use R2 Not seen absent from the complete list of training data
Time-series anomaly detection UniTS few-shot anomaly detection checkpoints Training data seen in fine-tuning data: only the training split was used, not the benchmark's test data
Time-series anomaly detection UniTS Not seen absent from the complete list of training data

Notes

published_from = creation date of the RANSynCoders GitHub repository (commit history inside it starts 2021-02-12); the KDD 2021 paper (Practical Approach to Asynchronous Multivariate Time Series Anomaly Detection and Localization) was not accessible (ACM DL returned 403), so sizes and the train/test time ranges are not quoted from the paper. The 25 features were read from the header of train.csv.

Sources