tods/datasets/NAB

• NAB Data Corpus
• • Real data
  • Artificial data

NAB Data Corpus

Data are ordered, timestamped, single-valued metrics. All data files contain anomalies, unless otherwise noted.

Real data

• realAWSCloudwatch/

  AWS server metrics as collected by the AmazonCloudwatch service. Example metrics include CPU Utilization, Network Bytes In, and Disk Read Bytes.

• realAdExchange/

  Online advertisement clicking rates, where the metrics are cost-per-click (CPC) and cost per thousand impressions (CPM). One of the files is normal, without anomalies.

• realKnownCause/

  This is data for which we know the anomaly causes; no hand labeling.

  • ambient_temperature_system_failure.csv: The ambient temperature in an office
    setting.
  • cpu_utilization_asg_misconfiguration.csv: From Amazon Web Services (AWS)
    monitoring CPU usage – i.e. average CPU usage across a given cluster. When
    usage is high, AWS spins up a new machine, and uses fewer machines when usage
    is low.
  • ec2_request_latency_system_failure.csv: CPU usage data from a server in
    Amazon's East Coast datacenter. The dataset ends with complete system failure
    resulting from a documented failure of AWS API servers. There's an interesting
    story behind this data in the Numenta
    blog.
  • machine_temperature_system_failure.csv: Temperature sensor data of an
    internal component of a large, industrial mahcine. The first anomaly is a
    planned shutdown of the machine. The second anomaly is difficult to detect and
    directly led to the third anomaly, a catastrophic failure of the machine.
  • nyc_taxi.csv: Number of NYC taxi passengers, where the five anomalies occur
    during the NYC marathon, Thanksgiving, Christmas, New Years day, and a snow
    storm. The raw data is from the NYC Taxi and Limousine Commission.
    The data file included here consists of aggregating the total number of
    taxi passengers into 30 minute buckets.
  • rogue_agent_key_hold.csv: Timing the key holds for several users of a
    computer, where the anomalies represent a change in the user.
  • rogue_agent_key_updown.csv: Timing the key strokes for several users of a
    computer, where the anomalies represent a change in the user.

• realTraffic/

  Real time traffic data from the Twin Cities Metro area in Minnesota, collected
  by the
  Minnesota Department of Transportation.
  Included metrics include occupancy, speed, and travel time from specific
  sensors.

• realTweets/

  A collection of Twitter mentions of large publicly-traded companies
  such as Google and IBM. The metric value represents the number of mentions
  for a given ticker symbol every 5 minutes.

Artificial data

• artificialNoAnomaly/

  Artificially-generated data without any anomalies.

• artificialWithAnomaly/

  Artificially-generated data with varying types of anomalies.