Splunk SPLK-3002 Exam

In the Notable Events Review dashboard within Splunk IT Service Intelligence (ITSI), when working with a notable event group, users can set or adjust certain attributes at the individual event level or at the group level. These attributes include:

Severity: The importance or impact level of the notable event or group, which can be adjusted to reflect the current assessment of the situation.

Status: The current state of the notable event or group, such as 'New,' 'In Progress,' or 'Resolved,' indicating the progress in addressing the event or group.

Owner: The user or team responsible for managing and resolving the notable event or group.

These settings allow for effective management and tracking of notable events, ensuring that they are appropriately prioritized, acted upon, and resolved by the responsible parties.

Custom deep dives in Splunk IT Service Intelligence (ITSI) are versatile and highly customizable dashboards that allow users to analyze various types of data in a unified view. One of the key characteristics of custom deep dives is their ability to combine lanes of different data types, such as metrics, events, Key Performance Indicators (KPIs), and service health scores. This multifaceted approach provides a comprehensive and layered view of the IT environment, enabling analysts and operators to correlate different data types and gain deeper insights into the health and performance of services. By incorporating these diverse data lanes, custom deep dives facilitate a more holistic understanding of the operational landscape, aiding in more effective troubleshooting and decision-making.

In Splunk IT Service Intelligence (ITSI), the Service Health Score is a metric that provides a quantifiable measure of the overall health and performance of a service. The score ranges from 0 to 100, with higher scores indicating better health. The range for a normal Service Health score category is typically from 80 to 100. Scores within this range suggest that the service is performing well, with no significant issues affecting its health. This categorization helps IT and business stakeholders quickly assess the operational status of their services, enabling them to focus on services that may require attention or intervention due to lower health scores.

In the context of Splunk IT Service Intelligence (ITSI), service dependencies allow for the modeling of relationships between services, where the health of one service (dependent) can affect the health of another (primary).

B) It is best practice to use the dependent service's built-in 'ServiceHealthScore' KPI to reflect impact to the primary service: Utilizing the 'ServiceHealthScore' KPI of a dependent service as part of the primary service's health calculation is a recommended practice. This approach ensures that changes in the health of the dependent service directly influence the primary service's overall health score, providing a more holistic view of service health within the IT environment.

C) Setting the dependent service KPI importance level will be treated as any other KPI in the primary service's health score: When a dependent service's KPI is incorporated into a primary service, the importance level assigned to this KPI is factored into the primary service's overall health score calculation just like any other KPI. This means that the impact of the dependent service on the primary service can be weighted according to the business significance of the relationship between the services.

The other options are not accurate representations of ITSI service dependencies. Changes in KPI importance levels do not break dependencies, and there is no restriction on configuring impactful dependent services to only one primary service, as dependencies can be complex and multi-layered across various services.

B is the correct answer because value over time is a valid type of Multi-KPI Alert in ITSI. A Multi-KPI Alert is a type of alert that triggers when multiple KPIs from one or more services meet certain conditions within a specified time range. Value over time is a condition that compares the current value of a KPI to its previous values over a specified time range. For example, you can create a Multi-KPI Alert that triggers when the CPU usage and memory usage of a service are both higher than their average values in the last 24 hours. Reference: [Create Multi-KPI alerts in ITSI], [Multi-KPI alert conditions in ITSI]