ITSI Saved Search Scheduling is configured to use realtime_schedule = 0. Which statement is accurate about this configuration?
Correct Answer:B
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.
References: Create KPI base searches in ITSI, Rrealtime_schedule in SavedSearches.conf
Which ITSI functions generate notable events? (Choose all that apply.)
Correct Answer:ABD
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
When in maintenance mode, which of the following is accurate?
Correct Answer:A
Reference: https://docs.splunk.com/Documentation/ITSI/4.10.2/EA/REBestPractice
A is the correct answer because when in maintenance mode, KPIs and notable events will begin to be generated again once the window is over. Maintenance mode is a feature of ITSI that allows you to temporarily suspend alerts and health score calculations for a service or an entity during planned maintenance or downtime. During maintenance mode, KPI searches still run, but the results are buffered until the window is over. Once the window is over, the buffered results are processed and alerts and health scores are generated if necessary. References: [Overview of maintenance windows in ITSI]
Which of the following is a good use case for a Multi-KPI alert?
Correct Answer:D
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 isbeneficial in complex environments where the interplay between different performance metrics needs to be considered to accurately detect and diagnose issues.
Which of the following applies when configuring time policies for KPI thresholds?
Correct Answer:B
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 thresholdvalues 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.
References: Create time-based static KPI thresholds in ITSI
Which of the following is a good use case regarding defining entities for a service?
Correct Answer:A
Define entities before creating services. When you configure a service, you can specify entity matching rules based on entity aliases that automatically add the entities to your service.
Reference: https://docs.splunk.com/Documentation/ITSI/4.10.2/Entity/About
A is the correct answer because defining entities for a service allows you to automatically associate entities to services using multiple entity aliases. Entity aliases are alternative names or identifiers for an entity, such as host name, IP address, MAC address, or DNS name. ITSI matches entity aliases to fields in your data sources and assigns entities to services accordingly. This way, you can avoid manually adding entities to each service and ensure that your services reflect the latest changes in your environment.
References: Define entities for a service in ITSI