System Limits

In order to provide a robust, reliable service, Amazon ML imposes certain limits on the requests you make to the system. Most ML problems fit easily within these constraints. However, if you do find that your use of Amazon ML is being restricted by these limits, you can contact AWS customer service and request to have a limit raised. For example, you might have a limit of five for the number of jobs that you can run simultaneously. If you find that you often have jobs queued that are waiting for resources because of this limit, then it probably makes sense to raise that limit for your account.

The following table shows default per-account limits in Amazon ML. Not all of these limits can be raised by AWS customer service.

Limit Type	System Limit
Size of each observations	100 KB
Size of training data *	100 GB
Size of batch prediction input	1 TB
Size of batch prediction input (number of records)	100 million
Number of variables in a data file (schema)	1,000
Recipe complexity (number of processed output variables)	10,000
TPS for each real-time prediction endpoint	200
Total TPS for all real-time prediction endpoints	10,000
Total RAM for all real-time prediction endpoints	10 GB
Number of simultaneous jobs	25
Longest run time for any job	7 days
Number of classes for multiclass ML models	100
ML model size	Minimum of 1 MB, maximum of 2 GB
Number of tags per object	50

• The size of your data files is limited to ensure that jobs finish in a timely manner. Jobs that have been running for more than seven days will be automatically terminated, resulting in a FAILED status.