Splunk updates a bevy of its suites with machine learning advances

Splunk's algorithms are focused on investigations for security incidents, alerting, predictive tools for operations and maintenance and business optimization for demand, inventory and analysis of historical data.

Splunk on Tuesday outlined new versions of its flagship suites with an emphasis on machine learning advances.

The company updated Splunk® Enterprise, Splunk IT Service Intelligence (ITSI), Splunk Enterprise Security (ES) and Splunk User Behavior Analytics (UBA) for both cloud and on-premises deployments.

Splunk's algorithms are focused on investigations for security incidents, alerting, predictive tools for operations and maintenance and business optimization for demand, inventory and analysis of historical data.

Among the key updates:

  • Splunk Cloud and Splunk Enterprise 6.5 will offer custom machine learning tools and a new user interface for analysis. The updates include a guided workbench to create machine learning models for IT, security and business processes. Data prep tools are designed to reach more users.
  • Splunk ITSI 2.4 will include tools to simplify security investigations as well as workflows. Pre-built tools will baseline normal operational patterns and create alerts for anomalies. The interface has also been overhauled to provide a single view of an enterprise.
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  • Splunk ES 4.5 and UBA 3.0 has new models, content updates and new data sources. Security metrics have been added along with threat detection tools.
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