Machine Learning Toolkit and Showcase
The Machine Learning Toolkit and Showcase App (preview) delivers showcases, new SPL commands, and examples to explore a variety of machine learning concepts. Each showcase includes end-to-end examples with sample datasets, plus the ability to apply the showcases and SPL commands to your own data. You can inspect the showcase panels and underlying code to see how it all works and then create custom dashboards to suit your needs. Showcases: * Predict Numeric Fields (Linear Regression): e.g. predict median house values. * Predict Categorical Fields (Logistic Regression): e.g. predict customer churn. * Detect Numeric Outliers (distribution statistics): e.g. detect outliers in IT Ops data. * Detect Categorical Outliers (probabilistic measures): e.g. detect outliers in diabetes patient records. * Forecast Time Series: e.g. forecast data center growth and capacity planning. * Cluster Events (K-means, DBSCAN, Spectral Clustering, BIRCH). New SPL commands: fit, apply, summary, listmodels, and deletemodel
MQTT Modular Input
This is a Splunk Modular Input Add-On for indexing messages from a MQTT Broker.
Google Maps Add-on for Splunk Enterprise
Google Maps for Splunk adds a geo-visualization module based on the Google Maps API and allows you to quickly plot geographical information on a map. Furthermore maps can be embedded in advanced dashboards.