Splunk® Machine Learning Toolkit


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This documentation does not apply to the most recent version of Splunk® Machine Learning Toolkit. For documentation on the most recent version, go to the latest release.
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Custom algorithms and PSC libraries version dependencies

Running version 5.4.0 of MLTK requires Splunk Enterprise 8.1.x or higher or Splunk Cloud Platform.

The Splunk Machine Learning Toolkit requires installation of the correct version of the Python for Scientific Computing (PSC) add-on from Splunkbase.

Versions 4.1.2, 4.1.0, and 3.1.0 of the Python for Scientific Computing (PSC) add-on include the ONNX library. Version 4.1.2, 4.1.0, or 3.1.0 of the PSC add-on are required to bring pre-trained ONNX models into MLTK. This ONNX model feature is only available with MLTK version 5.4.0. See, Upload and inference pre-trained ONNX models in MLTK.

Version 4.0.0 of the Python for Scientific Computing (PSC) add-on provides updates and adds several libraries in the package. In particular, Pytorch, cpuonly, transformers, onnxruntime, pydantic, and watchdog. Version 4.0.0 of PSC is only available when using MLTK version 5.3.3. Version 4.0.0 of the PSC add-on requires additional installation steps.

The build size of the PSC add-on version 4.0.0 might exceed the default value of max_upload_size which can prevent you from installing the package using the Install app from file option under Manage Apps. To install PSC 4.0.0 you must create a web.conf file , update max_upload_size to a higher value, and restart Splunk from your terminal. See Install version 4.0.0 of the Python for Scientific Computing add-on.

Before you upgrade to a new version

Any algorithms that have been imported from the PSC add-on into the Machine Learning Toolkit are overwritten when the MLTK app is updated to a new version. Prior to upgrading the MLTK, save your custom algorithms and re-import them manually after the upgrade.

If you have written any custom algorithms that rely on the PSC libraries, upgrading the PSC add-on will impact those algorithms. You must re-train any models (re-run the search that used the fit command) using those algorithms after you upgrade the PSC add-on.

Algorithms are stored in $SPLUNK_HOME/etc/apps/Splunk_ML_Toolkit/bin/algos on Unix-based systems and %SPLUNK_HOME%\etc\apps\Splunk_ML_Toolkit\bin\algos on Windows systems.

Specific version dependencies

For version information that includes MLTK, the PSC add-on, Python, and Splunk platform, see Machine Learning Toolkit version dependencies matrix.

MLTK version PSC version
5.4.0 3.1.0, 4.1.0, or 4.1.2
5.3.3 3.0.2, 3.1.0, 4.0.0, 4.1.0, or 4.1.2
5.3.1 3.0.0, 3.0.1, or 3.0.2
5.3.0 3.0.0, 3.0.1, or 3.0.2
5.2.2 2.0.0, 2.0.1, or 2.0.2
5.2.1 2.0.0, 2.0.1, or 2.0.2
5.2.0 2.0.0, 2.0.1, or 2.0.2
5.1.0 2.0.0
5.0.0 2.0.0
4.5.0 1.4
4.4.2 1.3 or 1.4
4.4.1 1.3 or 1.4
4.4.0 1.3 or 1.4
4.3.0 1.3 or 1.4
4.2.0 1.3 or 1.4
4.1.0 1.3
4.0.0 1.3
3.4.0 1.3
3.3.0 1.2 or 1.3
3.2.0 1.2 or 1.3
3.1.0 1.2
Last modified on 20 July, 2023
Savitzky-Golay Filter example
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This documentation applies to the following versions of Splunk® Machine Learning Toolkit: 5.4.0

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