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Working with machine learning in ITSI


The machine learning capabilities of Splunk ITSI can help your teams go from reactive to proactive by correlating the volume of alerts coming in at different times. When you look at key performance indicators (KPIs) like error count or memory utilization, you know that those are supposed to be in a certain threshold consistently.

But what about a business KPI like revenue that changes based on the time of the day or the day of the week? This is where Splunk ITSI adaptive thresholding comes in. Splunk ITSI can assess a revenue KPI and determine by one hour blocks, for example, what is normal and what is an acceptable standard deviation. You can then configure an adaptive threshold so you only receive alerts when the KPI reports values outside of the deviation, specific to the day and hour.

You can also apply predictive analytics to service health scores and set up alerts for when services with dependencies might cause a problem downstream. That way, your team can react before an error becomes a major problem.

To learn more about these machine learning capabilities in Splunk ITSI, watch the following demo.