Splunk® Machine Learning Toolkit


Use custom logging

The Splunk Machine Learning Toolkit (MLTK) ships with utilities to make logging easy to manage.

MLTK relies on a different Python interpreter than the interpreter that ships with Splunk Enterprise.

To begin, import a logger. For more detailed logging, you can use a logger with a custom name as shown in the following example:

from cexc import get_logger

logger = get_logger('MyCustomLogging')

Logger messages are logged to $SPLUNK_HOME/var/log/mlspl.log.

Along with the name provided in get_logger, the function is also recorded:

1491862833.627798 2017-04-10 15:20:33,627 WARNING [mlspl.MyCustomLogging] [__init__] warning!
1491862833.627949 2017-04-10 15:20:33,627 ERROR [mlspl.MyCustomLogging] [__init__] error!
1491862833.628024 2017-04-10 15:20:33,628 DEBUG [mlspl.MyCustomLogging] [__init__] info!

If you cannot find messages using the logger, you can also look in the search.log.

Last modified on 31 January, 2024
Create user facing messages   Adding Python 3 libraries

This documentation applies to the following versions of Splunk® Machine Learning Toolkit: 5.1.0, 5.2.0, 5.2.1, 5.2.2, 5.3.0, 5.3.1, 5.3.3, 5.4.0, 5.4.1

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