Questions for the SPLK-3002 were updated on : Dec 01 ,2025
Which of the following is a good use case for creating a custom module?
C
Explanation:
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.
How can Service Now incidents be created automatically when a Multi-KPI alert triggers? (select all
that apply)
CD
Explanation:
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 is the least permissive role required to modify default deep dives?
D
Explanation:
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.
Which ITSI components are required before a module can be created?
C
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.
Which anomaly detection algorithm is included within ITSI?
A
Explanation:
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.
When working with a notable event group in the Notable Events Review dashboard, which of the
following can be set at the individual or group level?
B
Explanation:
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.
Which of the following services often has KPIs but no entities?
C
Explanation:
In the context of Splunk IT Service Intelligence (ITSI), a Business Service often has Key Performance
Indicators (KPIs) but might not have directly associated entities. Business Services represent high-
level aggregations of organizational functions or processes and are typically measured by KPIs that
reflect the performance of underlying technical services or components rather than direct
infrastructure entities. For example, a Business Service might monitor overall transaction completion
times or customer satisfaction scores, which are abstracted from the specific technical entities that
underlie these metrics. This abstraction allows Business Services to provide a business-centric view
of IT health and performance, focusing on outcomes rather than specific technical components.
Which of the following is a characteristic of notable event groups?
A
Explanation:
In Splunk IT Service Intelligence (ITSI), notable event groups are used to logically group related
notable events, which enhances the manageability and analysis of events:
A) Notable event groups combine independent notable events: This characteristic allows for the
aggregation of related events into a single group, making it easier for users to manage and
investigate related issues. By grouping events, users can focus on the broader context of an issue
rather than getting lost in the details of individual events.
While notable event groups play a critical role in organizing and managing events in ITSI, they do not
inherently allow users to adjust threshold settings, which is typically handled at the KPI or service
level. Additionally, while notable event groups are utilized within the ITSI framework, the statement
that they are created in the 'itsi_tracked_alerts' index might not fully capture the complexity of how
event groups are managed and stored within the ITSI architecture.
What can a KPI widget on a glass table drill down into?
D
Explanation:
In Splunk IT Service Intelligence (ITSI), a KPI widget on a glass table can be configured to drill down
into a variety of destinations based on the needs of the user and the design of the glass table. This
flexibility allows users to dive deeper into the data or analysis represented by the KPI widget,
providing context and additional insights. The destinations for drill-downs from a KPI widget can
include:
A) Another glass table, offering a different perspective or more detailed view related to the KPI. B. A
Splunk dashboard that provides broader analysis or incorporates data from multiple sources. C. A
custom deep dive for in-depth, time-series analysis of the KPI and related metrics.
This versatility makes KPI widgets powerful tools for navigating through the wealth of operational
data and insights available in ITSI, facilitating effective monitoring and decision-making.
Which of the following are characteristics of service templates? (select all that apply)
BC
Explanation:
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.
Which of the following items describe ITSI teams? (select all that apply)
BCD
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.
When troubleshooting KPI search performance, which search names in job activity identify base
searches?
B
Explanation:
In the context of troubleshooting KPI search performance in Splunk IT Service Intelligence (ITSI), the
search names in the job activity that identify base searches typically follow the pattern "Indicator -
Shared - xxxx - ITSI Search." These base searches are fundamental components of the KPI calculation
process, aggregating and preparing data for further analysis by KPIs. Identifying these base searches
in the job activity is crucial for diagnosing performance issues, as these searches can be resource-
intensive and impact overall system performance. Understanding the naming convention helps
administrators and analysts quickly pinpoint the base searches related to specific KPIs, facilitating
more effective troubleshooting and optimization of search performance within the ITSI environment.
Which of the following is a characteristic of custom deep dives?
C
Explanation:
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.
How can admins manually control groupings of notable events?
D
Explanation:
In Splunk IT Service Intelligence (ITSI), administrators can manually control the grouping of notable
events using aggregation policies. Aggregation policies allow for the definition of criteria based on
which notable events are grouped together. This includes configuring rules based on event fields,
severity, source, or other event attributes. Through these policies, administrators can tailor the event
grouping logic to meet the specific needs of their environment, ensuring that related events are
grouped in a manner that facilitates efficient analysis and response. This feature is crucial for
managing the volume of events and focusing on the most critical issues by effectively organizing
related events into manageable groups.
There are two Smart Mode configuration settings that control how fields affect grouping. Which of
these is correct?
C
Explanation:
In the context of Smart Mode configuration within Splunk IT Service Intelligence (ITSI), the two
settings that control how fields affect grouping are "Text similarity" and "Category similarity." Smart
Mode is a feature used in event grouping that leverages machine learning to automatically group
related events. "Text similarity" refers to how closely the textual content of event fields must match
for those events to be grouped together, taking into account commonalities in strings or narratives
within the event data. "Category similarity," on the other hand, relates to the similarity in the
categorical attributes of events, such as event types or source types, which helps in clustering events
that are similar in nature or origin. Both of these settings are crucial in determining how events are
grouped in ITSI, influencing the granularity and relevance of the event groupings based on textual
and categorical similarities.