Which anomaly detection algorithm is included within ITSI?
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.
Which ITSI components are required before a module can be created?
Before a module can be created in Splunk IT Service Intelligence (ITSI), it is essential to have one or more datamodels established. Datamodels in Splunk provide a structured format for organizing and interpreting data, which is crucial for modules within ITSI. Modules often rely on datamodels to extract, transform, and present data in a meaningful way, especially when dealing with complex datasets across various sources. Datamodels serve as the foundation for the module's ability to categorize and analyze data efficiently, enabling the creation of KPIs, services, and visualizations that are aligned with the specific needs of the module. Having these datamodels in place ensures that the module can function correctly and provide valuable insights into the monitored IT environments.
Which is the least permissive role required to modify default deep dives?
To modify default deep dives in Splunk IT Service Intelligence (ITSI), the least permissive role typically required is the itoa_admin role. This role is specifically designed within ITSI to provide administrative capabilities, including the ability to configure and customize various aspects of ITSI, such as services, KPIs, and deep dives. The itoa_admin role has the necessary permissions to edit and manage default deep dives, enabling users with this role to tailor the deep dives to meet specific operational requirements and preferences. Other roles like itoa_analyst, admin, or power might not have sufficient privileges to modify default deep dives, as these roles are generally more restricted in terms of their ability to make broad changes within ITSI.
How can Service Now incidents be created automatically when a Multi-KPI alert triggers? (select all that apply)
To automatically create ServiceNow incidents when a Multi-KPI alert triggers in Splunk IT Service Intelligence (ITSI), the following approaches can be used:
C) By creating a notable event aggregation policy with a ServiceNow (SNOW) incident action: ITSI allows the creation of notable event aggregation policies that can specify actions to be taken when certain conditions are met. One of these actions can be the creation of an incident in ServiceNow, directly linking the alerting mechanism in ITSI with incident management in ServiceNow.
D) By editing the associated correlation search and specifying an alert action: Correlation searches in ITSI are used to identify patterns or conditions that signify notable events. These searches can be configured to include alert actions, such as creating a ServiceNow incident, whenever the search conditions are met. This direct integration ensures that incidents are automatically generated in ServiceNow, based on the specific criteria defined in the correlation search.
Options A and B are not standard practices for integrating ITSI with ServiceNow for automatic incident creation. The configuration typically involves setting up actionable alert mechanisms within ITSI that are specifically designed to integrate with external systems like ServiceNow.
Which of the following is a good use case for creating a custom module?
Creating a custom module in Splunk IT Service Intelligence (ITSI) is particularly beneficial for the purpose of migrating KPI base searches and related visualizations to other ITSI installations. Custom modules can encapsulate a set of configurations, searches, and visualizations that are tailored to specific monitoring needs or environments. By packaging these elements into a module, it becomes easier to transfer, deploy, and maintain consistency across different ITSI instances. This modularity supports the reuse of developed components, simplifying the process of scaling and replicating monitoring setups in diverse operational contexts. The ability to migrate these components seamlessly enhances operational efficiency and ensures that best practices and custom configurations can be shared across an organization's ITSI deployments.
