Overview

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IBM Z® OMEGAMON® AI Insights is designed to detect and visualize performance anomalies within z/OS components and applications. It leverages advanced machine learning algorithms embedded in its code to analyze data.

OMEGAMON AI Insights can analyze data that is collected from any of the following OMEGAMON monitoring agents:

  • IBM Z OMEGAMON AI for CICS 6.1
  • IBM Z OMEGAMON AI for JVM 6.1
  • IBM Z OMEGAMON AI for Networks 6.1
  • IBM Z OMEGAMON AI for z/OS 6.1

These agents monitor the behavior of applications and components by tracking various performance metrics, referred to as attributes. In the process, they collect data that are passed on to OMEGAMON AI Insights. With this data, OMEGAMON AI Insights can arrive at models that predict the seasonality of various key performance indicators across diverse types of workloads.

The generated models start providing predictions as soon as they are installed, however they mature over time through a process that uses historical data and consists of two steps:
  1. Train: Historical data is used to build or update forecast models. This step does not occur in real-time but should be done regularly for getting seasonality trends. The Training process needs some data over a reasonable period to be able to build a forecast model. The standard minimum period of training is fourteen days. OMEGAMON AI Insights models are generated immediately after the minimum requirements are met and forecast can be visualized.
  2. Predict: In this step, the models determine if the current metric is beyond the forecast. It creates an anomaly and calculates the severity level. This step is generally scheduled for every hour but can be scheduled for other frequencies.

Once a model has matured, you can begin comparing the forecasts it generates with live key performance indicators. For instance, you would know if the CPU utilization measured on a given day is abnormal if it exceeds the value predicted for that day by the model.

The live data, along with the predicted seasonality patterns output by a model, are presented through visually appealing dashboards on Elastic Kibana. Through these dashboards, you can easily detect abnormal behavior, and promptly troubleshoot by drilling down into specifics.

In addition to providing visual warnings, OMEGAMON AI Insights can also email alerts to stakeholders based on the severity of an anomaly.

OMEGAMON AI Insights is an application that can be hosted directly on a Docker container on Linux for Z. Containerization simplifies the installation process and enhances the product's scalability to match varying workloads. It also provides the flexibility to seamlessly transition between on-premises and cloud environments with minimal disruption.

All data required for analysis is collected by OMEGAMON AI Insights from Elasticsearch, which in turn receives it from OMEGAMON Data Provider.