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Where are KPI search results stored?
Search results are processed, created, and written to the itsi_summary index via an alert action.
D is the correct answer because KPI search results are stored in the itsi_summary index in ITSI. This index is an events index that stores the results of scheduled KPI searches. Summary indexing lets you run fast searches over large data sets by spreading out the cost of a computationally expensive report over time. Reference:Overview of ITSI indexes
Which of the following applies when configuring time policies for KPI thresholds?
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.
Which of the following is an advantage of using adaptive time thresholds?
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.
Which index is used to store KPI values?
The IT Service Intelligence (ITSI) metrics summary index,itsi_summary_metrics, is a metrics-based summary index that stores KPI data.
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. Reference:Overview of ITSI indexes
Which is the least permissive role required to modify default deep dives?
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.
