Monitoring and investigating situations
BMC Helix AIOps correlates events collected from multiple sources across infrastructure, applications, network resources, and monitoring solutions from different vendors into situations. The events from the same or different hosts are correlated based on their occurrence, message, signature, topology, or a combination of these factors into different situations. Situations created by using the AI/ML-based technique are known as ML-based situations in BMC Helix AIOps.
Situations are correlated by filtering raw events and other situations based on:
- Problem pattern and event signatures
- Analysis of the message content
- Sequence of the event from the same node or different nodes of a service hierarchy
- Time and day of occurrence, and so on
An event's signature is derived from the name of host from which the event originated and the event message. Based on the type of correlation, situations are categorized into independent, primary, or similar situations.
The following diagram shows how situations are created from raw events:
BMC Helix AIOps can analyze hundreds of thousands of raw events in near real time to create situations. Here are some of the major benefits of using ML-based situations in BMC Helix AIOps:
The following diagram shows high-level process for managing situations in BMC Helix AIOps: