Monitoring and investigating situations

Situations in BMC Helix AIOps comprise event correlation and aggregation. Events collected from multiple sources across infrastructure, application, network resources, and even monitoring solutions from different vendors are correlated to create one or more Situations. These events associated with the same or different host are aggregated based on their occurrence, message, topology, or a combination of these factors. Situations created using the AI/ML-based technique are known as AIOps or ML-based Situations in BMC Helix AIOps. 

You can monitor and investigate the ML-based Situations.

AIOps or ML-based Situations and event signature

The ML-based Situation uses an AI/ML-based event processing technique to identify event patterns from hundreds of raw events, filter out impactful events, automatically aggregate those events into Situations, and add a unique signature to each event type. The AI/ML algorithm uses the event signature to build unique Situations from the aggregated events. 

Event signatures help identify the event pattern from an event sequence. However, while aggregating the events in to a Situation, the temporal relationship between the events is also considered. For example, consider an event sequence with CPU utilization events at 90%, 93%, and 97%. All events have the same pattern and signature. However, these are aggregated into the same Situation only if all these events fall within the same defined time window.

Review the following sections to learn how to monitor and investigate ML-based situations:

• ML-based situations
• Configuring ML-based situations
• Monitoring situations
• Investigating ML-based situations