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Event noise reduction indicator for prioritized triage and remediation

Event noise is the term used to describe the hundreds of hourly and daily notifications and alarms (eg: CPU utilization, memory utilization, end user response time) delivered by monitoring systems to IT operations teams to show the health and performance of infrastructure and applications across their IT environment. Event noise reduction involves reducing the event storm by combining multiple matching events into a single aggregated event. Event noise reduction enables you to perform prioritized triage and remediation.

Related topics

Monitoring-key-performance-indicators-and-entities

Data-providers-for-services-and-situations

Noise reduction in BMC Helix AIOps console uses an ML-based event correlation algorithm and no-code functionality to deduplicate, reconcile, and group all the events coming from both BMC and third-party tools to create Situations. Creating Situations is achieved in near real-time using event timestamps, message text, and topology. 

Enable AIOps Situations

For the noise reduction to work, you need ML-situations and must enable the AIOps Situations feature. For more information, see Enabling the AIOps features.

You can view the event noise reduction value in percentage.

What is the source of events considered for event noise reduction?

To compute the event noise reduction value, BMC Helix AIOps console considers ML-based aggregated events, which are derived by using AI/ML algorithms. For more information, see Configuring ML-based situations.

The noise reduction widget shows the percentage of the all events correlated into Situations. You can view the noise reduction value in percentage and its trend on the Overview page as shown in the following example:

noise_reduction.png

Event noise reduction computation

The following computation is used to derive the noise reduction value in percentage.

Noise reduction computation

noiseReduction(%) = ((secondaryEvents-primaryEvents)/totalEventsAssociatedwithServiceswithID)*100)

Example

Consider the following example to understand how the noise reduction value is computed:

Total number of service associated events in the system (totalEventsAssociatedwithServices) = 50

Total number of ML-based situations in the system (primaryEvents) = 10

Total number of events associated with the ML-based situations in the system (secondaryEvents) = 20

noiseReduction(%) = ((secondaryEvents-primaryEvents)/totalEvents)*100) = ((20-10)/50)*100 = 20%


What are total events?

Total events are the events that are associated with a service and contain a Service ID. 


What are primary events?

A primary event is an aggregated event derived from several matching events. For example, you can derive a single event from the secondary events listed in the following example: The host1.bmc.com host is shutting down. The primary event should match the following conditions: 

  • Class = Situation 
  • Algorithm Name = ML
  • Relationships = evcount must be greater than 0 and the rstat value must be primary.

PrimaryEvent.png

What are secondary events?

Secondary events are a set of matching events that can be combined to create a single aggregated event. For example, if the host1.bmc.com host is shut down, you may receive several events originating from that host as shown in the following example:

Secondary events

Primary event

application1 is shutting down

The host1.bmc.com host is shutting down

stopped application2

Unable to authenticate application3

Unable to open application5

The secondary event should match the following conditions: 

Relationships = Must contain mlsituation and the relationships.rstat value must be secondary.

Secondary events.png

 

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