Splunk® IT Service Intelligence

Service Insights Manual

Overview of Predictive Analytics in ITSI

Predictive Analytics uses machine learning algorithms to predict the health score value of a selected service in IT Service Intelligence (ITSI). The models use historical service health score and KPI data to approximate what a service's health might look like in 30 minutes.

ITSI provides visualization tools that guide you through the process of creating machine learning models without having to learn complex machine learning algorithms and technology.

Implement Predictive Analytics to identify and fix service outages before they happen. By receiving a warning that your service is likely to degrade in the next 30 minutes, you can take steps to resolve the problem before it affects other areas of your environment.

Use Predictive Analytics if:

  • You've had unplanned outages in the past.
  • You want to prevent future outages.
  • You want to understand and identify patterns in your service.
  • You want to understand how future outages can impact your business.


See also

Last modified on 28 April, 2023
Update a service template in ITSI   Set up Predictive Analytics in ITSI

This documentation applies to the following versions of Splunk® IT Service Intelligence: 4.11.0, 4.11.1, 4.11.2, 4.11.3, 4.11.4, 4.11.5, 4.11.6, 4.12.0 Cloud only, 4.12.1 Cloud only, 4.12.2 Cloud only, 4.13.0, 4.13.1, 4.13.2, 4.13.3, 4.14.0 Cloud only, 4.14.1 Cloud only, 4.14.2 Cloud only, 4.15.0, 4.15.1, 4.15.2, 4.15.3, 4.16.0 Cloud only, 4.17.0, 4.17.1, 4.18.0, 4.18.1, 4.19.0

Was this topic useful?

You must be logged into splunk.com in order to post comments. Log in now.

Please try to keep this discussion focused on the content covered in this documentation topic. If you have a more general question about Splunk functionality or are experiencing a difficulty with Splunk, consider posting a question to Splunkbase Answers.

0 out of 1000 Characters