Lookout for Metrics quotas - Amazon Lookout for Metrics

Lookout for Metrics quotas

Amazon Lookout for Metrics sets quotas for the amount of data that a detector can use to learn and detect anomalies. There are also quotas for data import intervals, records processing, and Amazon Lookout for Metrics API requests. Additionally, there are data requirements for data retention for re-training, coldstart anomaly detection, backtesting, time series, and record field key value pairs.

Quotas set by other services can impact operation. For information on quotas for other services such as Amazon CloudWatch, see AWS service quotas in the Amazon Web Services General Reference.

Adjustable quotas

The following quotas can be increased. For more information, see Requesting a quota increase in the Service Quotas User Guide.

Resource Default quota
Quotas for detectors

Maximum number of detectors

10

Maximum number of alerts for a detector

10

Maximum number of files you can upload per interval

5-minute interval

5 files

10-minute interval

5 files

1-hour interval

10 files

1-day interval

10 files

Maximum number of records Lookout for Metrics can process per interval

5-minute interval

15000 records

10-minute interval

24000 records

1-hour interval

150000 records

1-day interval

150000 records

The following adjustable Lookout for Metrics quotas apply per AWS Region and are for Lookout for Metrics API requests.

Resource Default Quota

Maximum rate of total API requests

10/second

Maximum rate of CreateAnomalyDetector API requests

1/second

Maximum rate of UpdateAnomalyDetector API requests

1/second

Maximum rate of DeleteAnomalyDetector API requests

1/second

Maximum rate of ListAnomalyDetectors API requests

2/second

Maximum rate of DescribeAnomalyDetector API requests

2/second

Maximum rate of ActivateAnomalyDetector API requests

1/second

Maximum rate of BackTestAnomalyDetector API requests

1/second

Maximum rate of DescribeAnomalyDetectionExecutions API requests

2/second

Maximum rate of ListAnomalyGroupSummaries API requests

2/second

Maximum rate of ListAnomalyGroupTimeSeries API requests

2/second

Maximum rate of GetAnomalyGroup API requests

2/second

Maximum rate of CreateMetricSet API requests

1/second

Maximum rate of DescribeMetricSet API requests

2/second

Maximum rate of ListMetricSets API requests

2/second

Maximum rate of UpdateMetricSet API requests

1/second

Maximum rate of CreateAlert API requests

1/second

Maximum rate of DeleteAlert API requests

1/second

Maximum rate of DescribeAlert API requests

2/second

Maximum rate of ListAlerts API requests

2/second

Maximum rate of GetDataQualityMetrics API requests

2/second

Maximum rate of GetSampleData API requests

2/second

Maximum rate of PutFeedback API requests

1/second

Maximum rate of GetFeedback API requests

2/second

Maximum rate of TagResource API requests

1/second

Maximum rate of UntagResource API requests

1/second

Maximum rate of ListTagsForResource API requests

1/second

Fixed quotas

The following quotas cannot be changed.

Resource Quota

Maximum number of datasets for a detector

1 dataset

Quotas for datasets

Maximum number of dimensions for a dataset

5 dimensions

Maximum number of measures for a dataset

5 measures

Quotas for historical data

Maximum intervals (continuous mode)

2500

Maximum intervals (backtest mode)

3000

Maximum number of files in historical data

3000

Maximum number of metrics Lookout for Metrics can process per detector

5-minute interval

5000 metrics

10-minute interval

10000 metrics

1-hour interval

50000 metrics

1-day interval

50000 metrics

Data retention time periods for re-training

The amount of time you should retain your data for re-training depends on the interval of your data collection as follows:

Interval Maximum time Average time
5 minutes 9 days 4.5 days
10 minutes 18 days 9 days
1 hour 3.4 months 2 months
1 day 5 years 2 years

Coldstart anomaly detection

For coldstart anomaly detection (no historical data), the amount of time it takes for Lookout for Metrics to detect anomalies depends on the interval of your data collection as follows:

  • 5 minute interval – 25 hours

  • 10 minute interval – 50 hours

  • 1 hour interval – 4 days

  • 1 day interval – 14 days

File size

The amount of data that the detector can process for an interval is limited. You can reduce the size of files by aggregating records or by removing fields that are not used as measures or dimensions.

  • 5 minute interval – 200 MB

  • 10 minute interval – 200 MB

  • 1 hour interval – 200 MB

  • 1 day interval – 200 MB

Backtesting data requirements

The ratio of training and testing data used for backtesting is 70% training and 30% testing. The maximum number of data points you will see is 900, and the number of days of data Lookout for Metrics considers for backtesting depends on the interval of your data collection as follows:

  • 5 minute interval – 3.125 days, with 12 data points per hour and 288 data points per day.

  • 10 minute interval – 6.25 days, with 6 data points per hour and 144 data points per day.

  • 1 hour interval – 37.5 days, with 1 data point per hour and 24 points per day.

  • 1 day interval – 900 days, with 1 data point per day.

The minimum amount of data required for backtesting depends on the interval of your data collection as follows:

  • 5 minute interval – ~1 day of data.

  • 10 minute interval – 1.9 days of data.

  • 1 hour interval – 11.8 days of data.

  • 1 day interval – 285 days of data.

Record field key-value pair character limits

Character limits for record field key value pairs are as follows:

  • Dimensions key – 63 characters

  • Dimension value – 40 characters

  • Timestamp key – 63 characters

  • Measure value – 10^15 with precision of 4 after decimal point