Deep Learning Toolkit for Splunk v4

Deep Learning Toolkit for Splunk (DLTK) is a Splunk App that allows users to better deploy, observe and scale advanced data science and machine learning projects with Splunk. In a cloud-native way, DLTK lets you elastically and dynamically deploy models to CPU and GPU based container environments such as Docker, Kubernetes or OpenShift to run algorithms in libraries like Spark, TensorFlow, PyTorch, Rapids and Dask.

🔴 Important Note 🔴

This project (DLTK v4) was created in 2020 as a new app architecture for DLTK. Due to various reasons - low traction in the open source world - this project in currently not considered to be actively maintained and continued. However, DLTK version 3.x is available on Splunkbase and is actively maintained and developed. Parts of the v4 project may be ported into the splunkbase version of DLTK. If you want to get started with DLTK we recommend to use DLTK 3.x from splunkbase. If you are using this app version v4 you might want to consider migrating it to the splunkbase version. Finally, if you want to install DLTK v4 from this repository, please see the Installation Guide.

Documentation

This repository is used to build DLTK. If you are looking for documentation, please see the following:

• User Guide
• Administrator Guide
• Developer Guide

Community Supported

Deep Learning Toolkit for Splunk is an open source project developed by Splunkers with contributions from the community of partners and customers. It will be enhanced, maintained and supported by the community, led by Splunkers with deep subject matter expertise. This is not an official Splunk supported product.

License

See LICENSE.

Contributors

Andreas Greeske, Anthony Tellez, Greg Ainslie-Malik, Philipp Drieger, Robert Fujara

If you are interested in contributing to this project, please see the Contributing Guidelines.