AIOps on IBM Z - Group home

IBM Z Anomaly Analytics v5.1.2.14 provides KPI Context


Introducing KPI Context

One request we keep hearing from customers relates to how we can make the mainframe more productive for the next generation of IT Operation users. Integrating domain knowledge into solutions like IBM Z Anomaly Analytics is a pivotal strategy, empowering the next generation of users to harness AI insights and accelerate their productivity on platform, thereby diminishing the learning curve. Today we are proud to announce our newest capability in IBM Z Anomaly Analytics v5.1.2.14: Key Performance Indicator (KPI) Context. 

KPI Context now provides the end user with information they can use to better interpret and analyze anomalous activity. This new feature provides key information about every KPI that is supported by the product and includes:

  • KPI Summary: Explains what information this metric is representing in terms of resources in the underlying subsystem. Background information is provided to explain the function of the resource underlying each metric. 
  • Explanation of an anomaly in this KPI: Answers the question, "What does a change in this metric indicate about how this subsystem is operating?"
  • How the KPI is calculated: Details about how this metric was derived from the underlying SMF data. 

This was no small feat. There was significant collaboration across development teams including the subject matter experts from each z/OS and subsystem team as well as data science teams to embed their expertise into the solution. The ultimate goal is to provide transparency, trust and actionable insights so that our end users can be more confident and productive at their jobs. Check out the demo below to see how we are embedding domain knowledge into our solution.