Question 1

What are valid considerations when designing an ITSI Service? (Choose all that apply.)

Accepted Answer

A, B, C

Explanation: Reference: https://docs.splunk.com/Documentation/ITSI/4.10.2/Configure/ImplementPerms A, B, and C are correct answers because service access control requirements for ITSI Team Access should be considered before creating the ITSI Service, as different teams may have different permissions and views of the service data. Entities, entity meta-data, and entity rules should also be planned carefully to support the service design and configuration, as they determine how ITSI maps data sources to services and KPIs. Services, entities, and saved searches are stored in the ITSI app, while events created by KPI execution are stored in the itsi_summary index for faster retrieval and analysis. Reference: ITSI service design best practices, Overview of ITSI indexes

Question 2

There are two Smart Mode configuration settings that control how fields affect grouping. Which of these is correct?

Accepted Answer

C

Explanation: In the context of Smart Mode configuration within Splunk IT Service Intelligence (ITSI), the two settings that control how fields affect grouping are "Text similarity" and "Category similarity." Smart Mode is a feature used in event grouping that leverages machine learning to automatically group related events. "Text similarity" refers to how closely the textual content of event fields must match for those events to be grouped together, taking into account commonalities in strings or narratives within the event data. "Category similarity," on the other hand, relates to the similarity in the categorical attributes of events, such as event types or source types, which helps in clustering events that are similar in nature or origin. Both of these settings are crucial in determining how events are grouped in ITSI, influencing the granularity and relevance of the event groupings based on textual and categorical similarities.

Question 3

Which of the following actions can be performed with a deep dive?

Accepted Answer

A

Explanation: Deep dives in Splunk IT Service Intelligence (ITSI) allow for an in-depth analysis of services and their KPIs over time, providing a detailed view of the operational health and performance trends. One of the powerful actions that can be performed with a deep dive is the creation of a Multi-KPI alert from the deep dive's current state. This functionality enables users to define alerts based on the complex conditions observed during the deep dive analysis, allowing for the early detection of similar situations in the future. By configuring a Multi-KPI alert directly from a deep dive, ITSI users can leverage their insights and observations to proactively monitor for patterns or conditions that may indicate potential service degradation or failure, enhancing the overall responsiveness and effectiveness of the IT monitoring strategy.

Question 4

Which deep dive swim lane type does not require writing SPL?

Accepted Answer

D

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. Reference: [KPI Lanes]

Question 5

Which of the following is a good use case for creating a custom module?

Accepted Answer

C

Explanation: Creating a custom module in Splunk IT Service Intelligence (ITSI) is particularly beneficial for the purpose of migrating KPI base searches and related visualizations to other ITSI installations. Custom modules can encapsulate a set of configurations, searches, and visualizations that are tailored to specific monitoring needs or environments. By packaging these elements into a module, it becomes easier to transfer, deploy, and maintain consistency across different ITSI instances. This modularity supports the reuse of developed components, simplifying the process of scaling and replicating monitoring setups in diverse operational contexts. The ability to migrate these components seamlessly enhances operational efficiency and ensures that best practices and custom configurations can be shared across an organization's ITSI deployments. Thank you for your visit.

Question 6

Which of the following is a characteristic of notable event groups?

Accepted Answer

A

Explanation: 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.

Question 7

For which ITSI function is it a best practice to use a 15-30 minute time buffer?

Accepted Answer

B

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: Configure adaptive thresholding for a KPI in ITSI

Question 8

Which glass table feature can be used to toggle displaying KPI values from more than one service on a single widget?

Accepted Answer

D

Explanation: Reference: https://docs.splunk.com/Documentation/ITSI/4.10.2/SI/Visualizations#collapseDesktop8 A glass table is a visualization tool that allows you to monitor the interrelationships and dependencies across your IT and business services. You can add metrics like KPIs, ad hoc searches, and service health scores that update in real time against a background that you design. One of the features of glass tables is service swapping, which enables you to toggle displaying KPI values from more than one service on a single widget. You can use service swapping to compare metrics across different services without creating multiple glass tables or widgets. Reference: Overview of the glass table editor in ITSI, [Configure service swapping on glass tables]

Question 9

There are two departments using ITSI. Finance and Sales. Analysts in each department should not be
allowed to see each other’s services. What are the role configuration steps required to accomplish
this?

Accepted Answer

C

Explanation: C is the correct answer because teams are a feature of ITSI that allow you to restrict access to service content in UI views based on user roles. To create separate teams for finance and sales analysts, you need to create custom roles that inherit from the itoa_analyst role, which has read-only access to ITSI content. For example, you can create itoa_finance_analyst and itoa_sales_analyst roles that inherit from itoa_analyst. Then, you need to create custom teams that include these roles and assign them to the relevant services. For example, you can create a finance team that includes the itoa_finance_analyst role and assign it to the finance services. Similarly, you can create a sales team that includes the itoa_sales_analyst role and assign it to the sales services. This way, analysts in each department can only see their own services and not each other’s. Reference: Create teams in ITSI, Assign teams to services in ITSI

Question 10

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

Accepted Answer

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

Question 11

Which of the following is part of setting up a new aggregation policy?

Accepted Answer

A

Explanation: When setting up a new aggregation policy in Splunk IT Service Intelligence (ITSI), one of the crucial components is defining the filtering criteria. This aspect of the aggregation policy determines which events should be included in the aggregation based on specific conditions or attributes. The filtering criteria can be based on various event fields such as severity, source, event type, and other custom fields relevant to the organization's monitoring strategy. By specifying the filtering criteria, ITSI administrators can ensure that the aggregation policy is applied only to the pertinent events, thus facilitating more targeted and effective event management and reducing noise in the operational environment. This helps in organizing and prioritizing events more efficiently, enhancing the overall incident management process within ITSI.

Question 12

In which index are active notable events stored?

Accepted Answer

C

Explanation: In Splunk IT Service Intelligence (ITSI), notable events are created and managed within the context of its Event Analytics framework. These notable events are stored in the itsi_tracked_alerts index. This index is specifically designed to hold the active notable events that are generated by ITSI's correlation searches, which are based on the conditions defined for various services and their KPIs. Notable events are essentially alerts or issues that need to be investigated and resolved. The itsi_tracked_alerts index enables efficient storage, querying, and management of these events, facilitating the ITSI's event management and review process. The other options, such as itsi_notable_archive and itsi_notable_audit, serve different purposes, such as archiving resolved notable events and auditing changes to notable event configurations, respectively. Therefore, the correct answer for where active notable events are stored is the itsi_tracked_alerts index.

Question 13

In distributed search, which components need to be installed on instances other than the search head?

Accepted Answer

A

Explanation: SA-IndexCreation is required on all indexers. For non-clustered, distributed environments, copy SA- IndexCreation to $SPLUNK_HOME/etc/apps/ on individual indexers. Reference: https://docs.splunk.com/Documentation/ITSI/4.10.2/Install/InstallDD In distributed search, the components that need to be installed on instances other than the search head are SA-IndexCreation and SA-ITSI-Licensechecker on indexers. SA-IndexCreation is an add-on that creates the indexes required by ITSI, such as itsi_summary and itsi_tracked_alerts. SA-ITSI- Licensechecker is an add-on that monitors the license usage of ITSI and generates alerts when the license limit is exceeded or about to expire. These components need to be installed on indexers because they handle the data ingestion and storage functions for ITSI. The other components, such as ITSI app and SA-ITOA, need to be installed on the search head(s) because they handle the search management and presentation functions for ITSI. Reference: Install IT Service Intelligence in a distributed environment

Question 14

What is the minimum number of entities a KPI must be split by in order to use Entity Cohesion anomaly detection?

Accepted Answer

D

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.

Question 15

When troubleshooting KPI search performance, which search names in job activity identify base searches?

Accepted Answer

B

Explanation: In the context of troubleshooting KPI search performance in Splunk IT Service Intelligence (ITSI), the search names in the job activity that identify base searches typically follow the pattern "Indicator - Shared - xxxx - ITSI Search." These base searches are fundamental components of the KPI calculation process, aggregating and preparing data for further analysis by KPIs. Identifying these base searches in the job activity is crucial for diagnosing performance issues, as these searches can be resource- intensive and impact overall system performance. Understanding the naming convention helps administrators and analysts quickly pinpoint the base searches related to specific KPIs, facilitating more effective troubleshooting and optimization of search performance within the ITSI environment.

Free Splunk SPLK-3002 Actual Exam Questions