Splunk IT Service Intelligence Certified Admin Exam - SPLK-3002 Exam Dumps

Explanation: 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.

C is the correct answer because a default deep dive initially shows all of the KPIs for a selected service. You can create a default deep dive by drilling down from another dashboard or by selecting a service from the deep dive lister page. A default deep dive does not show health scores, importance scores, or entity swim lanes by default.

An episode represents a disruption of service operation causing impact to business operations. It is a deduplicated group of notable events occurring as part of a larger sequence, or an incident or period considered in isolation. In Episode Review, you can manage the episodes and their statuses using various actions. One of the actions is Acknowledge, which changes the status of an episode from New to Acknowledged and assigns the current user as the owner. This action indicates that someone is working on resolving the episode and prevents duplicate efforts from other users.

Explanation:
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.
A maintenance window is a period of time when a service or entity is undergoing maintenance operations or does not require active monitoring. It is 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. This gives the system an opportunity to catch up with the maintenance state and reduces the chances of ITSI generating false positives during maintenance operations. For example, if a server will be shut down for maintenance at 1:00PM and restarted at 5:00PM, the ideal maintenance window is 12:30PM to 5:30PM. The 15- to 30-minute time buffer is a rough estimate based on 15 minutes being the time period over which most KPIs are configured to search data and identify alert triggers.

Explanation: In Splunk IT Service Intelligence (ITSI), teams are used to organize services, KPIs, and other objects within ITSI to facilitate access control and management:
B.Services should be assigned to the 'global' team if all users need access to it: The 'global' team in ITSI is a built-in concept that denotes universal accessibility. Assigning services to the 'global' team makes them accessible to all ITSI users, irrespective of their specific team memberships. This is useful for services that are relevant across the entire organization.
C. By default, all services are owned by the built-in 'global' team and administered by the 'itoa_admin' role:This default setting ensures that upon creation, services are accessible to administrators and can be further re-assigned or refined for access by specific teams as needed.
D. A new team admin role should be created for each team. The new role should inherit the 'itoa_team_admin' role:This best practice allows for granular access control and management within teams. Each team can have its own administrators with the appropriate level of access and permissions tailored to the needs of that team, derived from the capabilities of the 'itoa_team_admin' role.
The concept of adding 'itoa admin roles' with read-only permissions contradicts the typical use case for administrative roles, which usually require more than read-only access to manage services and entities effectively.

B is the correct answer because ITSI episodes are stored in the itsi_grouped_alerts index. This index contains notable events that have been grouped together based on predefined aggregation policies. Episodes help you reduce alert noise and focus on resolving incidents faster.

A is the correct answer because the itsi_summary_metrics index is used to store KPI values in ITSI. This index improves the performance of the searches dispatched by ITSI, particularly for very large environments. Every KPI is summarized in both the itsi_summary events index and the itsi_summary_metrics metrics index.

Explanation: An adaptive time threshold in the context of Splunk IT Service Intelligence (ITSI) refers to the capability of dynamically adjusting threshold values for Key Performance Indicators (KPIs) based on historical data trends and patterns. This feature allows thresholds to evolve as the 'normal' behavior of KPIs changes over time, ensuring that alerts remain relevant and reduce the likelihood of false positives or negatives. The advantage of this approach is that it accommodates for natural fluctuations in KPI values that may occur due to changes in business operations, seasonality, or other factors, without requiring manual threshold adjustments. This makes the monitoring system more resilient and responsive to actual conditions, improving the overall effectiveness of IT operations management.

D is the correct answer because ITSI provides multiple ways to delete multiple duplicate entities. You can use a CSV upload to overwrite existing entities with new or updated information, or delete them by setting the action field to delete. You can also use the entity lister page to select multiple entities and delete them in bulk. Alternatively, you can use a search command called | deleteentity to delete entities that match certain criteria.

When onboarding data into a Splunk index, assuming that ITSI will need to use this data, you should consider the following:
B. Check if the data could leverage pre-built KPIs from modules, then use the correct TA to onboard the data. This is true because modules are pre-packaged sets of services, KPIs, and dashboards that are designed for specific types of data sources, such as operating systems, databases, web servers, and so on. Modules help you quickly set up and monitor your IT services using best practices and industry standards. To use modules, you need to install and configure the correct technical add-ons (TAs) that extract and normalize the data fields required by the modules.
The other options are not things you should consider because:
A. Use | stats functions in custom fields to prepare the data for KPI calculations. This is not true because using | stats functions in custom fields can cause performance issues and inaccurate results when calculating KPIs. You should use | stats functions only in base searches or ad hoc searches, not in custom fields.
C. Make sure that all fields conform to CIM, then use the corresponding module to import related services. This is not true because not all modules require CIM-compliant data sources. Some modules have their own data models and field extractions that are specific to their data sources. You should check the documentation of each module to see what data requirements and dependencies they have.
D. Plan to build as many data models as possible for ITSI to leverage. This is not true because building too many data models can cause performance issues and resource consumption in your Splunk environment. You should only build data models that are necessary and relevant for your ITSI use cases.