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Splunk IT Service Intelligence Certified Admin Questions 16–20 (page: 5)

Updated On: 10-Feb-2026

Which of the following accurately describes base searches used for KPIs in a service?

  1. Base searches can be used for multiple services.
  2. A base search can only be used by its service and all dependent services.
  3. All the metrics in a base search are used by one service.
  4. All the KPIs in a service use the same base search.

Answer(s): A

Explanation:

KPI base searches let you share a search definition across multiple KPIs in IT Service Intelligence (ITSI). Create base searches to consolidate multiple similar KPIs, reduce search load, and improve search performance.


Reference:

https://docs.splunk.com/Documentation/ITSI/4.10.2/SI/BaseSearch A base search is a search definition that can be shared across multiple KPIs that use the same data source. Base searches can improve search performance and reduce search load by consolidating multiple similar KPIs. The statement that accurately describes base searches used for KPIs in a service is:
A) Base searches can be used for multiple services. This means that you can create a base search for a service and use it for other services that have similar data sources and KPIs. For example, if you have multiple services that monitor web server performance, you can create a base search that queries the web server logs and use it for all the services that need to calculate KPIs based on those logs.



Which scenario would benefit most by implementing ITSI?

  1. Monitoring of business services functionality.
  2. Monitoring of system hardware.
  3. Monitoring of system process statuses
  4. Monitoring of retail sales metrics.

Answer(s): A


Reference:

https://docs.splunk.com/Documentation/ITSI/4.10.2/SI/AboutSI Splunk IT Service Intelligence (ITSI) is a monitoring and analytics solution that uses artificial intelligence and machine learning to provide insights into the health and performance of IT services.

ITSI lets you create services that represent the critical components of your IT infrastructure, such as applications, databases, servers, networks, and so on. You can then monitor the status and performance of these services using key performance indicators (KPIs), which are metrics that measure aspects of service health, such as availability, latency, error rate, and so on. ITSI also provides tools for visualizing, investigating, and alerting on service issues, such as service analyzers, glass tables, deep dives, episode review, and so on. The scenario that would benefit most by implementing ITSI is monitoring of business service functionality, because ITSI enables you to measure and improve the quality and reliability of your IT services and align them with your business objectives.

What is Splunk IT Service Intelligence?



ITSI Saved Search Scheduling is configured to use realtime_schedule = 0.
Which statement is accurate about this configuration?

  1. If this value is set to 0, the scheduler bases its determination of the next scheduled search execution time on the current time.
  2. If this value is set to 0, the scheduler bases its determination of the next scheduled search on the last search execution time.
  3. If this value is set to 0, the scheduler may skip scheduled execution periods.
  4. If this value is set to 0, the scheduler might skip some execution periods to make sure that the scheduler is executing the searches running over the most recent time range.

Answer(s): B

Explanation:

ITSI Saved Search Scheduling is a feature that allows you to schedule searches that run periodically to populate the data for your KPIs. You can configure various settings for your scheduled searches, such as the search frequency, the time range, the cron expression, and so on. One of the settings is realtime_schedule, which controls the way the scheduler computes the next execution time of a scheduled search. The statement that is accurate about this configuration is:
B) If this value is set to 0, the scheduler bases its determination of the next scheduled search on the last search execution time. This is called continuous scheduling. If set to 0, the scheduler never skips scheduled execution periods. However, the execution of the saved search might fall behind depending on the scheduler's load. Use continuous scheduling whenever you enable the summary index option.
The other statements are not accurate because:
A) If this value is set to 0, the scheduler bases its determination of the next scheduled search execution time on the current time. This is not true because this is what happens when the value is set to 1, not 0.
C) If this value is set to 0, the scheduler may skip scheduled execution periods. This is not true because this is what happens when the value is set to 1, not 0. D) If this value is set to 0, the scheduler might skip some execution periods to make sure that the scheduler is executing the searches running over the most recent time range. This is not true because this is what happens when the value is set to 1, not 0.


Reference:

Create KPI base searches in ITSI, Rrealtime_schedule in SavedSearches.conf



What effects does the KPI importance weight of 11 have on the overall health score of a service?

  1. At least 10% of the KPIs will go critical.
  2. Importance weight is unused for health scoring.
  3. The service will go critical.
  4. It is a minimum health indicator KPI.

Answer(s): B


Reference:

https://docs.splunk.com/Documentation/ITSI/4.10.2/SI/KPIImportance#:~:text=ITSI%20considers%2 0KPIs%20that%20have,other%20KPIs%20in%20the%20service
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.


Set KPI importance values in ITSI



Which of the following is an advantage of using adaptive time thresholds?

  1. Automatically update thresholds daily to manage dynamic changes to KPI values.
  2. Automatically adjust KPI calculation to manage dynamic event data.
  3. Automatically adjust aggregation policy grouping to manage escalating severity.
  4. Automatically adjust correlation search thresholds to adjust sensitivity over time.

Answer(s): A


Reference:

https://docs.splunk.com/Documentation/ITSI/4.10.2/SI/TimePolicies Adaptive thresholds are thresholds calculated by machine learning algorithms that dynamically adapt and change based on the KPI's observed behavior. Adaptive thresholds are useful for monitoring KPIs that have unpredictable or seasonal patterns that are difficult to capture with static thresholds. For example, you might use adaptive thresholds for a KPI that measures web traffic volume, which can vary depending on factors such as holidays, promotions, events, and so on. The advantage of using adaptive thresholds is:

A) Automatically update thresholds daily to manage dynamic changes to KPI values. This is true because adaptive thresholds use historical data from a training window to generate threshold values for each time block in a threshold template. Each night at midnight, ITSI recalculates adaptive threshold values for a KPI by organizing the data from the training window into distinct buckets and then analyzing each bucket separately. This way, the thresholds reflect the most recent changes in the KPI data and account for any anomalies or trends.
The other options are not advantages of using adaptive thresholds because:
B) Automatically adjust KPI calculation to manage dynamic event data. This is not true because adaptive thresholds do not affect the KPI calculation, which is based on the base search and the aggregation method. Adaptive thresholds only affect the threshold values that are used to determine the KPI severity level.
C) Automatically adjust aggregation policy grouping to manage escalating severity. This is not true because adaptive thresholds do not affect the aggregation policy, which is a set of rules that determines how to group notable events into episodes. Adaptive thresholds only affect the threshold values that are used to generate notable events based on KPI severity level. D) Automatically adjust correlation search thresholds to adjust sensitivity over time. This is not true because adaptive thresholds do not affect the correlation search, which is a search that looks for relationships between data points and generates notable events. Adaptive thresholds only affect the threshold values that are used by KPIs, which can be used as inputs for correlation searches.


Create adaptive KPI thresholds in ITSI



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