Pass the Splunk IT Service Intelligence Certified Admin SPLK-3002 Questions and answers with Dumpstech

One of the recommended best practices for Splunk IT Service Intelligence (ITSI) installation is to avoid installing ITSI on search heads that already have Splunk Enterprise Security (ES) installed. This recommendation stems from potential resource conflicts and performance issues that can arise when both resource-intensive applications are deployed on the same instance. Both ITSI and ES are complex applications that require significant system resources to function effectively, and running them concurrently on the same search head can lead to degraded performance, conflicts in resource allocation, and potential stability issues. It's generally advised to segregate these applications onto separate Splunk instances to ensure optimal performance and stability for both platforms.

When an episode warrants investigation, the analyst acknowledges the episode, which moves the status from New to In Progress.

It's a best practice to schedule maintenance windows with a 15- to 30-minute time buffer before and after you start and stop your maintenance work. 

Service templates in Splunk IT Service Intelligence (ITSI) are designed to streamline the creation of services by providing pre-defined configurations:

B.Service templates contain KPIs and KPI thresholds:This allows for the standardized deployment of services with predefined performance indicators and their associated thresholds, ensuring consistency across similar services.

C.Service templates can contain specific or generic entity rules:These rules define how entities are associated with services created from the template, allowing for both broad and targeted applicability.

While service templates contain configurations for KPIs, thresholds, and entity rules, the ability to modify templates after services have been instantiated from them is limited. Changes to a template do not retroactively affect services already created from that template. Moreover, service templates do not inherently contain domain-specific dashboards or deep dives; these are created separately within ITSI.

Provide a value to filter the service to a specific set of entities. These entity rule values are meant to be custom for each service.

Splunk IT Service Intelligence (ITSI) is designed to align IT monitoring with the business outcomes that matter to stakeholders — especially executives who are focused on service performance and its impact on revenue, customer experience, and operational goals. In ITSI,entitiesrepresent the individual components that make up services and contribute to Key Performance Indicators (KPIs). Selecting the right entities for service modeling is critical: technical entities (like hosts or network interfaces) are useful for IT operations troubleshooting, but they don’t inherently represent business outcomes. Executive leadership cares about how incidents affect business capabilities and outcomes — such as sales performance, customer transactions, and channel health. Therefore, entities that reflectbusiness context(for example, store locations, product categories, or payment types) map IT issues directly to business performance indicators. When executives can see service health and incidents broken down by these business‑centric entities, they gainimpactful visibilityinto how issues affect revenue, customer interactions, and overall business operations. In contrast, purely technical entities such as hosts or network interfaces do not provide that business impact perspective, and demographic slices like season or customer age — while potentially valuable for marketing — don’t directly connect IT service health to business service performance in ITSI modeling.

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.

Time policies are user-defined threshold values to be used at different times of the day or week to account for changing KPI workloads. Time policies accommodate normal variations in usage across your services and improve the accuracy of KPI and service health scores. For example, if your organization’s peak activity is during the standard work week, you might create a KPI threshold time policy that accounts for higher levels of usage during work hours, and lower levels of usage during off-hours and weekends. The statement that applies when configuring time policies for KPI thresholds is:

B. They are great if you expect normal behavior at 1:00 to be different than normal behavior at 5:00. This is true because time policies allow you to define different threshold values for different time blocks, such as AM/PM, work hours/off hours, weekdays/weekends, and so on. This way, you can account for the expected variations in your KPI data based on the time of day or week.

The other statements do not apply because:

A. A person can only configure 24 policies, one for each hour of the day. This is not true because you can configure more than 24 policies using different time block combinations, such as 3 hour block, 2 hour block, 1 hour block, and so on.

C. If a person expects a KPI to change significantly through a cycle on a daily basis, don’t use it. This is not true because time policies are designed to handle KPIs that change significantly through a cycle on a daily basis, such as web traffic volume or CPU load percent.

D. It is possible for multiple time policies to overlap. This is not true because you can only have one active time policy at any given time. When you create a new time policy, the previous time policy is overwritten and cannot be recovered.