Splunk Machine Learning Toolkit version dependencies
The Splunk Machine Learning Toolkit (MLTK) releases updates on a regular schedule. Keep your instance of MLTK and affiliated add-ons up-to-date to access the latest features.
- For a list view of features included by release version, see What's new in the Splunk Machine Learning Toolkit.
- For installation information including links to Splunkbase for required add-ons, see Upgrade the Splunk Machine Learning Toolkit.
About the PSC add-on
MLTK requires installation of the Python for Scientific Computing (PSC) add-on.
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 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.
Version 3.0.2 of the Python for Scientific Computing (PSC) add-on is limited to bug fixes only. Version 3.0.1 of the Python for Scientific Computing (PSC) add-on is limited to configuration updates for deployment on Splunk Cloud Platform.
Version 3.0.0 of the Python for Scientific Computing (PSC) add-on brings updates to several libraries in the package. In particular, Numpy, Scipy, scikit-learn, Statsmodels, and Networkx are upgraded to their latest available versions.
If you have 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.
Version matrix
See the following table for the compatible combinations of MLTK, the PSC add-on, Python, and the Splunk platform:
MLTK version | PSC add-on version | Python version | Splunk platform version | Notes |
---|---|---|---|---|
5.4.0 | 4.1.2 | 3 | Splunk Enterprise 9.2.x or Splunk Cloud Platform |
Version 3.1.0, 4.1.0, or 4.1.2 of the PSC add-on is required to use the upload ONNX models feature. |
3.1.0, 4.1.0, or 4.1.2 | 3 | Splunk Enterprise 8.1.x, 8.2.x, 9.0.0, 9.0.1, 9.0.5, or 9.1.0 or Splunk Cloud Platform |
Version 3.1.0, 4.1.0, or 4.1.2 of the PSC add-on is required to use the upload ONNX models feature. | |
5.3.3 | 3.0.2, 3.1.0, 4.0.0, 4.1.0, or 4.1.2 | 3 | Splunk Enterprise 8.1.x, 8.2.x, or 9.0.0 or Splunk Cloud Platform |
Version 4.0.0 of the PSC add-on requires additional installation steps. See, Install version 4.0.0 of the PSC add-on. Deprecated support of Internet Explorer. |
5.3.1 | 3.0.0, 3.0.1, or 3.0.2 | 3 | Splunk Enterprise 8.0.x, 8.1.x, 8.2.x, or 9.0.0 or Splunk Cloud Platform |
Version 3.0.2 of the PSC add-on is limited to bug fixes. |
5.3.0 | 3.0.0, 3.0.1, or 3.0.2 | 3 | Splunk Enterprise 8.0.x, 8.1.x, 8.2.x, or 9.0.0 or Splunk Cloud Platform |
This version of MLTK requires version 3.0.0, 3.0.1, or 3.0.2 of the PSC add-on. Users upgrading to this version must retrain models created in earlier versions of MLTK. |
5.2.2 | 2.0.0, 2.0.1, or 2.0.2 | 3 | Splunk Enterprise 8.0.x, 8.1.x, or 8.2.0 or Splunk Cloud Platform |
This version of MLTK is limited to a minor enhancement. |
5.2.1 | 2.0.0, 2.0.1, or 2.0.2 | 3 | Splunk Enterprise 8.0.x, 8.1.x, or 8.2.0 or Splunk Cloud Platform |
This version of MLTK is limited to a minor enhancement. |
5.2.0 | 2.0.0, 2.0.1, or 2.0.2 | 3 | Splunk Enterprise 8.0.x, 8.1.x, or 8.2.0 or Splunk Cloud Platform |
This version of MLTK is available with Splunk Enterprise version 8.0.x, 8.1.x, or 8.2.0. |
5.1.0 | 2.0.0, 2.0.1, or 2.0.2 | 3 | Splunk Enterprise 8.0.x or 8.1.x or Splunk Cloud Platform |
This version of MLTK is available with Splunk Enterprise version 8.0.x or 8.1.x. |
5.0.0 | 2.0.0, 2.0.1, or 2.0.2 | 3 | Splunk Enterprise 8.0.x or 8.1.x or Splunk Cloud Platform |
This version of MLTK is only available with Splunk Enterprise version 8.0.x or 8.1.x. Users upgrading to this version must retrain models created in earlier versions of MLTK. The file extension for models has changed from .csv to .mlmodel .
|
4.5.0 | 1.4 | 2.x | Splunk Enterprise 7.x or Splunk Cloud Platform |
This version includes all the features of version 5.0.0 barring the support of the random_state parameter of the DensityFunction anomaly detection algorithm. Models created in earlier versions of MLTK maintain compatibility and do not require retraining.
|
Upgrade the Splunk Machine Learning Toolkit | Preparing your data for machine learning |
This documentation applies to the following versions of Splunk® Machine Learning Toolkit: 5.4.0
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