Notable events in Splunk IT Service Intelligence (ITSI) are primarily generated through scheduled correlation searches. These searches are designed to monitor data for specific conditions or patterns defined by the ITSI administrator, and when these conditions are met, a notable event is created. These correlation searches are often linked to specific services or groups of services, allowing for targeted monitoring and alerting based on the operational needs of those services. This mechanism enables ITSI to provide timely and relevant alerts that can be further investigated and managed through the Episode Review dashboard, facilitating efficient incident response and management within the IT environment.

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A multi-KPI alert is a type of correlation search that is based on defined trigger conditions for two or more KPIs. When trigger conditions occur simultaneously for each KPI, the search generates a notable event. For example, you might create a multi-KPI alert based on two common KPIs: CPU load percent and web requests. A sudden simultaneous spike in both CPU load percent and web request KPIs might indicate a DDOS (Distributed Denial of Service) attack. Multi-KPI alerts can bring such trending behaviors to your attention early, so that you can take action to minimize any impact on performance. Multi-KPI alerts are useful for correlating the status of multiple KPIs across multiple services. They help you identify causal relationships, investigate root cause, and provide insights into behaviors across your infrastructure. The best use case for configuring a multi-KPI alert is to raise an alert when one or more KPIs indicate an outage is occurring, such as when the service health score drops below a certain threshold or when multiple KPIs have critical severity levels. Reference: Create multi-KPI alerts in ITSI

A KPI lane is a type of deep dive swim lane that does not require writing SPL. You can simply select a service and a KPI from a drop-down list and ITSI will automatically populate the lane with the corresponding data. You can also adjust the threshold settings and time range for the KPI lane. Reference: [KPI Lanes]

Among the anomaly detection algorithms included within Splunk IT Service Intelligence (ITSI), "Entity Cohesion" is a notable option. The Entity Cohesion algorithm is designed to detect anomalies by comparing the behavior of one entity against the collective behavior of a group of similar entities. This approach is particularly useful in scenarios where entities are expected to exhibit similar patterns of behavior under normal conditions. Anomalies are identified when an entity's metrics deviate significantly from the group norm, suggesting a potential issue with that specific entity. This method leverages the concept of cohesion among similar entities to enhance the accuracy and relevance of anomaly detection within ITSI environments.