Splunk SPLK-3002 Splunk IT Service Intelligence Certified Admin Exam Practice Test

Answer : C

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.

Answer : A

An ITSI Glass Table provides a customizable, high-level view that can display a system's topology overlaid with real-time Key Performance Indicator (KPI) metrics and service health scores. This visualization tool allows users to create a visual representation of their IT infrastructure, applications, and services, integrating live data to monitor the health and performance of each component in context. The ability to overlay KPI metrics on the system topology enables IT and business stakeholders to quickly understand the operational status and health of various elements within their environment, facilitating more informed decision-making and rapid response to issues.

Answer : C

To install Splunk IT Service Intelligence (ITSI) on a single Search Head, one of the straightforward methods is to use the Splunk Web interface, specifically the 'Manage Apps' dashboard, to download and install ITSI. This method is user-friendly and does not require manual file handling or command-line operations. By navigating to 'Manage Apps' in the Splunk Web interface, users can find ITSI in the app repository or upload the ITSI installation package if it has been downloaded previously. From there, the installation process is initiated through the Splunk Web interface, simplifying the setup process. This approach ensures that the installation follows Splunk's standard app installation procedures, helping to avoid common installation errors and ensuring that ITSI is correctly integrated into the Splunk environment.

Answer : B

When onboarding data into a Splunk index, assuming that ITSI will need to use this data, you should consider the following:

B) Check if the data could leverage pre-built KPIs from modules, then use the correct TA to onboard the data. This is true because modules are pre-packaged sets of services, KPIs, and dashboards that are designed for specific types of data sources, such as operating systems, databases, web servers, and so on. Modules help you quickly set up and monitor your IT services using best practices and industry standards. To use modules, you need to install and configure the correct technical add-ons (TAs) that extract and normalize the data fields required by the modules.

The other options are not things you should consider because:

A) Use | stats functions in custom fields to prepare the data for KPI calculations. This is not true because using | stats functions in custom fields can cause performance issues and inaccurate results when calculating KPIs. You should use | stats functions only in base searches or ad hoc searches, not in custom fields.

C) Make sure that all fields conform to CIM, then use the corresponding module to import related services. This is not true because not all modules require CIM-compliant data sources. Some modules have their own data models and field extractions that are specific to their data sources. You should check the documentation of each module to see what data requirements and dependencies they have.

D) Plan to build as many data models as possible for ITSI to leverage. This is not true because building too many data models can cause performance issues and resource consumption in your Splunk environment. You should only build data models that are necessary and relevant for your ITSI use cases.

Answer : A

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.

Answer : B

In Splunk IT Service Intelligence (ITSI), when a Key Performance Indicator (KPI) aggregate value is calculated, the tstats function is often called. The tstats function in Splunk is used for rapid statistical queries over large volumes of data, which is particularly useful in ITSI for efficiently calculating aggregate values of KPIs across potentially vast datasets. This function allows for quick aggregation and summarization of indexed data, which is essential for monitoring and analyzing the performance metrics that KPIs represent in ITSI. Unlike the stats command, which operates on already retrieved events, tstats works directly on indexed data, providing faster performance especially when dealing with high volumes of data typical in an IT environment. The tstats command is therefore fundamental in the backend processing of ITSI for calculating aggregate values of KPIs, enabling real-time and historical analysis of service health and performance.

Answer : A

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. Reference:What is Splunk IT Service Intelligence?