Free SPLK-3002 Practice Test Questions 2026

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.

Explanation: A Multi-KPI alert in Splunk IT Service Intelligence (ITSI) is designed to trigger based on the conditions of multiple Key Performance Indicators (KPIs). This type of alert is particularly useful when a single KPI's state is not sufficient to indicate an issue, but the correlation between multiple KPIs can provide a clearer picture of an emerging problem. The best use case for a Multi-KPI alert is therefore when comparing the values of two or more KPIs indicates an unusual condition is occurring. This allows for more nuanced and context-rich alerting mechanisms that can identify complex issues not detectable by monitoring individual KPIs. This approach is beneficial in complex environments where the interplay between different performance metrics needs to be considered to accurately detect and diagnose issues.

Explanation: For Entity Cohesion anomaly detection in Splunk IT Service Intelligence (ITSI), the minimum number of entities a KPI must be split by is 2. Entity Cohesion as a method of anomaly detection focuses on identifying anomalies based on the deviation of an entity's behavior in comparison to other entities within the same group or cohort. By requiring a minimum of only two entities, ITSI allows for the comparison of entities to detect significant deviations in one entity's performance or behavior, which could indicate potential issues. This method leverages the idea that entities performing similar functions or within the same service should exhibit similar patterns of behavior, and significant deviations could be indicative of anomalies. The low minimum requirement of two entities ensures that this powerful anomaly detection feature can be utilized even in smaller environments.

Explanation: A KPI lane is a type of deep dive swim lane that does not require writing SPL. You can simply select a service and a KPI from a drop-down list and ITSI will automatically populate the lane with the corresponding data. You can also adjust the threshold settings and time range for the KPI lane.

Explanation: B is the correct answer because adaptive thresholding is a feature of ITSI that allows you to dynamically adjust KPI thresholds based on historical patterns and trends. Adaptive thresholding requires a time buffer of at least 15 minutes to calculate the thresholds based on the previous data points. The time buffer ensures that there is enough data to perform the calculations and avoid false positives or negatives.

Reference: The KPI importance weight is a value that indicates how much a KPI contributes to the overall health score of a service. The importance weight can range from 1 (lowest) to 10 (highest). The statement that applies when configuring a KPI importance weight of 11 is:, B. Importance weight is unused for health scoring. This is true because an importance weight of 11 is invalid and cannot be used for health scoring. The maximum value for importance weight is 10., The other statements do not apply because:, A. At least 10% of the KPIs will go critical. This is not true because an importance weight of 11 does not affect the severity level of any KPIs., C. The service will go critical. This is not true because an importance weight of 11 does not affect the health score or status of any service., D. It is a minimum health indicator KPI. This is not true because an importance weight of 11 does not indicate anything about the minimum health level of a KPI.

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.

Explanation: During the data audit phase of requirements gathering for Splunk IT Service Intelligence (ITSI), it's crucial to identify and record the meta-data for entities, focusing on information (info) and aliases. This step involves understanding and documenting the key attributes and identifiers that describe each entity, such as host names, IP addresses, device types, or other relevant characteristics. These attributes are used to categorize and uniquely identify entities within ITSI, enabling more effective mapping of data to services and KPIs. By meticulously recording this meta-data, organizations ensure that their ITSI implementation is aligned with their specific monitoring needs and infrastructure, facilitating accurate service modeling and event management. This practice is foundational for setting up ITSI to reflect the actual IT environment, enhancing the relevance and effectiveness of the monitoring and analysis capabilities.

Explanation:
By default, impacting service health scores have an importance value of 11.
Reference: https://docs.splunk.com/Documentation/ITSI/4.10.2/SI/Dependencies A service template is a predefined set of KPIs and entity rules that you can apply to a service or a group of services. A service template helps you standardize the configuration and monitoring of similar services across your IT environment. A service template can also include dependent services, which are services that are required for another service to function properly. For example, a web server service might depend on a database service and a network service. The default importance value for dependent services’ health scores is:
D. 10. This is true because the importance value indicates how much a dependent service contributes to the health score of the parent service. The default value is 10, which means that the dependent service has the highest impact on the parent service’s healthscore. You can change the importance value of a dependent service in the service template settings.
The other options are not correct because:
A. 11. This is not true because 11 is an invalid value for importance. The valid range is from 1 (lowest) to 10 (highest).
B. 1. This is not true because 1 is the lowest value for importance, not the default value. A value of 1 means that the dependent service has the lowest impact on the parent service’s health score.
C. Unassigned. This is not true because every dependent service has an assigned importance value, which defaults to 10.
References: Create and manage service templates in ITSI, Set KPI importance values in ITSI

Explanation: In Splunk IT Service Intelligence (ITSI), default deep dives are autogenerated and can be accessed via the Service Analyzer. Deep dives are an essential feature of ITSI that provide an in-depth, granular view into the health and performance of services and their associated KPIs. These default deep dives are automatically created for each service, allowing users to quickly drill down into the detailed operational metrics and performance data of their services. By accessing these deep dives through the Service Analyzer, ITSI users can efficiently investigate issues, understand service dependencies, and make informed decisions to maintain optimal service health. The auto-generated nature of these default deep dives simplifies the monitoring and analysis process, providing immediate insights into service performance without the need for manual setup or configuration.

Explanation: An ITSI Glass Table provides a customizable, high-level view that can display a system's topology overlaid with real-time Key Performance Indicator (KPI) metrics and service health scores. This visualization tool allows users to create a visual representation of their IT infrastructure, applications, and services, integrating live data to monitor the health and performance of each component in context. The ability to overlay KPI metrics on the system topology enables IT and business stakeholders to quickly understand the operational status and health of various elements within their environment, facilitating more informed decision-making and rapid response to issues.

Explanation:
After you configure KPI thresholds, you can set up alerts to notify you when aggregate KPI severities change. ITSI generates notable events in Episode Review based on the alerting rules you configure.
Anomaly detection generates notable events when a KPI IT Service Intelligence (ITSI) deviates from an expected pattern.
Notable events are typically generated by a correlation search.
Reference: https://docs.splunk.com/Documentation/ITSI/4.10.2/SI/KPIthresholds
https://docs.splunk.com/Documentation/ITSI/4.10.1/SI/AboutSI
A, B, and D are correct answers because ITSI can generate notable events when a KPI breaches a threshold, when a KPI detects an anomaly, or when a correlation search matches a defined pattern. These are the main ways that ITSI can alert you to potential issues or incidents in your IT environment. References: Configure KPI thresholds in ITSI, Apply anomaly detection to a KPI in ITSI, Generate events with correlation searches in ITSI