DOI: 10.5281/zenodo.17981352
title: OS-Metrics: Performance Time Series (PTS) Dataset for Anomaly Detection and Change Point Detection

description: OS-Metrics is a 7-day, 15-second resolution, causally annotated performance time series dataset, used to evaluate anomaly detection and change point detection algorithms. It contains 6 metric files and 3 event log files.

1. Files

Performance Metrics Data




File Name
Description
Data Volume


Invalid Data Volume





/cpu_usage.csv
CPU usage (percentage)
40320
0


/memory_usage.csv
Memory usage (percentage)
40320
0


/memory_used.csv
Used memory capacity (MB)
40320
0


/network_response_time_a.csv
HTTP response time (milliseconds) observed by DCS-A
40320
1


/network_response_time_b.csv
HTTP response time (milliseconds) observed by DCS-B
40320
12


/network_response_time_diff.csv
The pointwise difference (in milliseconds) between network_response_time_b.csv and network_response_time_a.csv
40320
13




Invalid data is marked as -99999, which is caused by packet loss due to network fluctuations.

Event Logs




File Name
Description
Data volume




/event_logs/event_logs_cpu.csv
CPU Disturbance Event Log
13


/event_logs/event_logs_memory.csv
Memory Disturbance Event Log
12


/event_logs/event_logs_network.csv
Network Disturbance Event Log
17




2. File Structure

Performance Metrics Data Files

All metric files share identical structure:




Column
Type
Description




Time
ISO 8601 datetime string (UTC), format YYYY-MM-DD HH:MM:SS
Timestamp of observation


Value
numeric
Observed metric value




Event Logs Files

All event log files share identical structure:




Column
Type
Description




id
string
Unique event identifier


flag
string
Execution status


start_time
ISO 8601 datetime string (UTC), format YYYY-MM-DDTHH:MM:SS.SSSZ
datetime string (UTC) when disturbance event began


end_time
ISO 8601 datetime string (UTC), format YYYY-MM-DDTHH:MM:SS.SSSZ
datetime string (UTC) when disturbance event ended


start_point
integer
Zero-based index of first affected data point in corresponding metric time series


end_point
integer
Zero-based index of last affected data point (inclusive) in corresponding metric time series


type
string
Disturbance category: cpu, memory, or network


mode
string
Disturbance mode: `stable`, fluctuation, burst, or gradual


intensity
numeric
Target disturbance strength; unit: percentage for cpu/memory, milliseconds for network


duration
integer
Nominal duration in seconds (end_time − start_time, rounded down)


ramp_up
integer
Duration in seconds of upward transition phase (0 if none)


ramp_down
integer
Duration in seconds of downward transition phase (0 if none)


duration_total
integer
Total effective duration in seconds (ramp_up + duration + ramp_down)




3. Remark



OS-Metrics is evaluation-ready: all 42 disturbance events are causally annotated with start/end time, intensity, mode, and affected metrics.

Metrics are sampled at 15-second intervals over 7 consecutive days.

Event logs use zero-based indexing (start_point, end_point) aligned to the metric time series (first row = index 0).

Remote observation bias (network_response_time_diff.csv) reflects real network path asymmetry, not artifact or error.

All timestamps are in UTC; no daylight saving adjustments applied.