It's a deduplicated group of notable events occurring as part of a larger sequence, or an incident or period considered in isolation. Reference: An episode is a deduplicated group of notable events occurring as part of a larger sequence, or an incident or period considered in isolation. An episode helps you reduce alert noise and focus on the most important issues affecting your IT services. An episode is created by an aggregation policy, which is a set of rules that determines how to group notable events based on certain criteria, such as severity, source, title, and so on. You can use episode review to view, manage, and resolve episodes in ITSI. The statement that defines an episode is: C) A notable event group. This is true because an episode is composed of one or more notable events that are related by some common factor. The other options are not definitions of an episode because: A) A workflow task. This is not true because a workflow task is an action that you can perform on an episode, such as assigning an owner, changing the status, adding comments, and so on. B) A deep dive. This is not true because a deep dive is a dashboard that allows you to analyze the historical trends and anomalies of your KPIs and metrics in ITSI. D) A notable event. This is not true because a notable event is an alert generated by ITSI based on certain conditions or correlations, not a group of alerts.
Question 12
Which of the following is a characteristic of base searches?
Correct Answer: C
Question 13
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 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.
Question 14
Anomaly detection can be enabled on which one of the following?
Correct Answer: A
Explanation Enable anomaly detection to identify trends and outliers in KPI search results that might indicate an issue with your system.
Question 15
Which of the following is a characteristic of notable event groups?
Correct Answer: A
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.
