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The Splunk SPLK-3002 exam consists of 60 multiple-choice and multiple-answer questions to be completed within 90 minutes. The questions are designed to assess the candidate's ability to configure and use ITSI to monitor, analyze, and troubleshoot IT infrastructure. SPLK-3002 exam also tests the candidate's knowledge of ITSI data models, service-oriented monitoring, advanced analytics, and machine learning. SPLK-3002 exam is administered online and can be taken from anywhere in the world.
Splunk SPLK-3002 exam is designed to test an individual's knowledge and skills in managing and administering Splunk IT Service Intelligence (ITSI). Splunk IT Service Intelligence Certified Admin certification exam is intended for IT professionals who are responsible for managing and maintaining ITSI deployments and utilizing the platform to monitor and analyze IT services. SPLK-3002 exam is highly regarded in the industry and passing it demonstrates a strong understanding of ITSI as well as a commitment to ongoing professional development.
NEW QUESTION # 32
Which of the following describes default deep dives?
- A. Include all KPIs of all services.
- B. Are manually generated and can be accessed via the Service Analyzer.
- C. Include health scores of all services.
- D. Are auto-generated and can be accessed via the Service Analyzer.
Answer: D
Explanation:
In Splunk IT Service Intelligence (ITSI), default deep dives are auto-generated and can be accessed via the Service Analyzer. Deep dives are an essential feature of ITSI that provide an in-depth, granular view into the health and performance of services and their associated KPIs. These default deep dives are automatically created for each service, allowing users to quickly drill down into the detailed operational metrics and performance data of their services. By accessing these deep dives through the Service Analyzer, ITSI users can efficiently investigate issues, understand service dependencies, and make informed decisions to maintain optimal service health. The auto-generated nature of these default deep dives simplifies the monitoring and analysis process, providing immediate insights into service performance without the need for manual setup or configuration.
NEW QUESTION # 33
Anomaly detection can be enabled on which one of the following?
- A. Entity
- B. Service
- C. Multi-KPI alert
- D. KPI
Answer: D
Explanation:
A is the correct answer because anomaly detection can be enabled on a KPI level in ITSI. Anomaly detection allows you to identify trends and outliers in KPI search results that might indicate an issue with your system. You can enable anomaly detection for a KPI by selecting one of the two anomaly detection algorithms in the KPI configuration panel. Reference: Apply anomaly detection to a KPI in ITSI
NEW QUESTION # 34
In maintenance mode, which features of KPIs still function?
- A. KPI searches still run during maintenance mode, but results go to itsi_maintenance_summary index.
- B. New KPIs can be created, but existing KPIs are locked.
- C. KPI searches will execute but will be buffered until the maintenance window is over.
- D. KPI calculations and threshold settings can be modified.
Answer: C
Explanation:
Explanation
It's a best practice to schedule maintenance windows with a 15- to 30-minute time buffer before and after you start and stop your maintenance work. This gives the system an opportunity to catch up with the maintenance state and reduces the chances of ITSI generating false positives during maintenance operations.
NEW QUESTION # 35
Which scenario would benefit most by implementing ITSI?
- A. Monitoring of system hardware.
- B. Monitoring of system process statuses
- C. Monitoring of business services functionality.
- D. Monitoring of retail sales metrics.
Answer: C
Explanation:
Reference:
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?
NEW QUESTION # 36
What effects does the KPI importance weight of 11 have on the overall health score of a service?
- A. At least 10% of the KPIs will go critical.
- B. It is a minimum health indicator KPI.
- C. Importance weight is unused for health scoring.
- D. The service will go critical.
Answer: B
NEW QUESTION # 37
What are valid ITSI Glass Table editor capabilities? (Choose all that apply.)
- A. Correlation search creation.
- B. Adding KPI metric lanes to glass tables.
- C. Creating glass tables.
- D. Service swapping configuration.
Answer: B,C,D
Explanation:
Create a glass table to visualize and monitor the interrelationships and dependencies across your IT and business services.
The service swapping settings are saved and apply the next time you open the glass table.
You can add metrics like KPIs, ad hoc searches, and service health scores that update in real time against a background that you design. Glass tables show real-time data generated by KPIs and services.
Reference:
The glass table editor is a tool that allows you to create and edit glass tables in ITSI. Some of the capabilities of the glass table editor are:
Creating glass tables from scratch or from existing templates.
Configuring service swapping on widgets to toggle displaying metrics from different services.
Adding KPI metric lanes to glass tables to show historical trends of KPI values.
The glass table editor does not support correlation search creation, which is a separate feature in ITSI that allows you to create searches that look for relationships between data points and generate notable events. Reference: Overview of the glass table editor in ITSI, [Configure service swapping on glass tables], [Add KPI metric lanes to glass tables], [Overview of correlation searches in ITSI]
NEW QUESTION # 38
What is the main purpose of the service analyzer?
- A. Display a list of All Services and Entities.
- B. Monitor overall Service and KPI status.
- C. Trigger external alerts based on threshold violations.
- D. Allow Analysts to add comments to Alerts.
Answer: B
Explanation:
Reference:
The service analyzer is a dashboard that allows you to monitor the overall service and KPI status in ITSI. The service analyzer displays a list of all services and their health scores, which indicate how well each service is performing based on its KPIs. You can also view the status and values of each KPI within a service, as well as drill down into deep dives or glass tables for further analysis. The service analyzer helps you identify issues affecting your services and prioritize them based on their impact and urgency. The main purpose of the service analyzer is:
D) Monitor overall service and KPI status. This is true because the service analyzer provides a comprehensive view of the health and performance of your services and KPIs in real time.
The other options are not the main purpose of the service analyzer because:
A) Display a list of all services and entities. This is not true because the service analyzer does not display entities, which are IT components that require management to deliver an IT service. Entities are displayed in other dashboards, such as entity management or entity health overview.
B) Trigger external alerts based on threshold violations. This is not true because the service analyzer does not trigger alerts, which are notifications sent to external systems or users when certain conditions are met. Alerts are triggered by correlation searches or alert actions configured in ITSI.
C) Allow analysts to add comments to alerts. This is not true because the service analyzer does not allow analysts to add comments to alerts, which are notifications sent to external systems or users
NEW QUESTION # 39
There are two Smart Mode configuration settings that control how fields affect grouping. Which of these is correct?
- A. Text deviation and category deviation.
- B. Text similarity and category similarity.
- C. Text deviation and category similarity.
- D. Text similarity and category deviation.
Answer: B
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.
NEW QUESTION # 40
What are valid considerations when designing an ITSI Service? (Choose all that apply.)
- A. Services, entities, and saved searches are stored in the ITSI app, while events created by KPI execution are stored in the itsi_summary index.
- B. Backfill of a KPI should always be selected so historical data points can be used immediately and alerts based on that data can occur.
- C. Entities, entity meta-data, and entity rules should be planned carefully to support the service design and configuration.
- D. Service access control requirements for ITSI Team Access should be considered, and appropriate teams provisioned prior to creating the ITSI Service.
Answer: A,D
NEW QUESTION # 41
How do you automatically restrict a KPI to only the entities in its service, and generate KPI values for each entity?
- A. Select "Yes" for "Split by Entity" and "No" for "Filter to Entities in Service".
- B. Select "No" for "Split by Entity" and "Yes" for "Filter to Entities in Service".
- C. Select "No" for both "Split by Entity" and "Filter to Entities in Service".
- D. Select "Yes" for both "Split by Entity" and "Filter to Entities in Service".
Answer: D
NEW QUESTION # 42
Anomaly detection can be enabled on which one of the following?
- A. Entity
- B. Service
- C. Multi-KPI alert
- D. KPI
Answer: D
Explanation:
Explanation
Enable anomaly detection to identify trends and outliers in KPI search results that might indicate an issue with your system.
NEW QUESTION # 43
What is the default importance value for dependent services' health scores?
- A. 0
- B. Unassigned
- C. 1
- D. 2
Answer: D
Explanation:
Explanation
By default, impacting service health scores have an importance value of 11.
NEW QUESTION # 44
When troubleshooting KPI search performance, which search names in job activity identify base searches?
- A. Indicator - Shared - xxxx - ITSI Search
- B. Indicator - XXXX - Base Search
- C. Indicator - Base - XXXX - Shared Search
- D. Indicator - Base - xxxx - ITSI Search
Answer: A
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.
NEW QUESTION # 45
In maintenance mode, which features of KPIs still function?
- A. KPI searches still run during maintenance mode, but results go to itsi_maintenance_summary index.
- B. New KPIs can be created, but existing KPIs are locked.
- C. KPI searches will execute but will be buffered until the maintenance window is over.
- D. KPI calculations and threshold settings can be modified.
Answer: C
Explanation:
It's a best practice to schedule maintenance windows with a 15- to 30-minute time buffer before and after you start and stop your maintenance work. This gives the system an opportunity to catch up with the maintenance state and reduces the chances of ITSI generating false positives during maintenance operations.
Reference:
A is the correct answer because KPI searches still run during maintenance mode, but the results are buffered until the maintenance window is over. This means that no alerts are triggered during maintenance mode, but once it ends, the buffered results are processed and alerts are generated if necessary. You cannot create new KPIs or modify existing KPIs during maintenance mode. Reference: [Overview of maintenance windows in ITSI]
NEW QUESTION # 46
When creating a custom deep dive, what color are services/KPIs in maintenance mode within the topology view?
- A. Gear Icon
- B. Blue
- C. Purple
- D. Gray
Answer: D
Explanation:
When creating a custom deep dive, services or KPIs that are in maintenance mode are shown in gray color in the topology view. This indicates that they are not actively monitored and do not generate alerts or notable events. Reference: Deep Dives
NEW QUESTION # 47
After a notable event has been closed, how long will the meta data for that event remain in the KV Store by default?
- A. 3 months.
- B. 6 months.
- C. 9 months.
- D. 1 year.
Answer: B
Explanation:
Explanation
By default, notable event metadata is archived after six months to keep the KV store from growing too large.
NEW QUESTION # 48
When deploying ITSI on a distributed Splunk installation, which component must be installed on the search head(s)?
- A. ITSI app
- B. SA-ITSI-Licensechecker
- C. SA-ITOA
- D. All ITSI components
Answer: B
Explanation:
Explanation
Install SA-ITSI-Licensechecker and SA-UserAccess on any license master in a distributed or search head cluster environment. If a search head in your environment is also a license master, the license master components are installed when you install ITSI on the search heads.
NEW QUESTION # 49
Which of the following is part of setting up a new aggregation policy?
- A. Policy version
- B. Filtering criteria
- C. Module rules
- D. Review order
Answer: B
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.
NEW QUESTION # 50
Which of the following is a best practice when configuring maintenance windows?
- A. Disable any glass tables that reference a KPI that is part of an open maintenance window.
- B. Give the maintenance window a buffer, for example, 15 minutes before and after actual maintenance work.
- C. Change the color of services and entities that are part of an open maintenance window in the service analyzer.
- D. Develop a strategy for configuring a service's notable event generation when the service's maintenance window is open.
Answer: B
Explanation:
It's a best practice to schedule maintenance windows with a 15- to 30-minute time buffer before and after you start and stop your maintenance work.
Reference:
A maintenance window is a period of time when a service or entity is undergoing maintenance operations or does not require active monitoring. It is a best practice to schedule maintenance windows with a 15- to 30-minute time buffer before and after you start and stop your maintenance work. This gives the system an opportunity to catch up with the maintenance state and reduces the chances of ITSI generating false positives during maintenance operations. For example, if a server will be shut down for maintenance at 1:00PM and restarted at 5:00PM, the ideal maintenance window is 12:30PM to 5:30PM. The 15- to 30-minute time buffer is a rough estimate based on 15 minutes being the time period over which most KPIs are configured to search data and identify alert triggers. Reference: Overview of maintenance windows in ITSI
NEW QUESTION # 51
Which of the following is a best practice when configuring maintenance windows?
- A. Disable any glass tables that reference a KPI that is part of an open maintenance window.
- B. Give the maintenance window a buffer, for example, 15 minutes before and after actual maintenance work.
- C. Change the color of services and entities that are part of an open maintenance window in the service analyzer.
- D. Develop a strategy for configuring a service's notable event generation when the service's maintenance window is open.
Answer: B
Explanation:
Explanation
It's a best practice to schedule maintenance windows with a 15- to 30-minute time buffer before and after you start and stop your maintenance work.
NEW QUESTION # 52
Which anomaly detection algorithm is included within ITSI?
- A. Linear regression
- B. Entity cohesion
- C. Standard deviation
- D. Infantile regression
Answer: B
Explanation:
Among the anomaly detection algorithms included within Splunk IT Service Intelligence (ITSI), "Entity Cohesion" is a notable option. The Entity Cohesion algorithm is designed to detect anomalies by comparing the behavior of one entity against the collective behavior of a group of similar entities. This approach is particularly useful in scenarios where entities are expected to exhibit similar patterns of behavior under normal conditions. Anomalies are identified when an entity's metrics deviate significantly from the group norm, suggesting a potential issue with that specific entity. This method leverages the concept of cohesion among similar entities to enhance the accuracy and relevance of anomaly detection within ITSI environments.
NEW QUESTION # 53
ITSI Saved Search Scheduling is configured to use realtime_schedule = 0. Which statement is accurate about this configuration?
- A. 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.
- B. If this value is set to 0, the scheduler bases its determination of the next scheduled search on the last search execution time.
- C. If this value is set to 0, the scheduler may skip scheduled execution periods.
- D. If this value is set to 0, the scheduler bases its determination of the next scheduled search execution time on the current time.
Answer: B
Explanation:
Explanation
If set to 0, the scheduler determines the next scheduled search run time based on the last run time for the search. This is called continuous scheduling.
NEW QUESTION # 54
Which of the following items apply to anomaly detection? (Choose all that apply.)
- A. Anomaly detection automatically generates notable events when KPI data diverges from the pattern.
- B. There are 3 types of anomaly detection supported in ITSI: adhoc, trending, and cohesive.
- C. Use AD on KPIs that have an unestablished baseline of data points. This allows the ML pattern to perform it's magic.
- D. A minimum of 24 hours of data is needed for anomaly detection, and a minimum of 4 entities for cohesive analysis.
Answer: A,D
Explanation:
Reference:
Anomaly detection is a feature of ITSI that uses machine learning to detect when KPI data deviates from a normal pattern. The following items apply to anomaly detection:
B) A minimum of 24 hours of data is needed for anomaly detection, and a minimum of 4 entities for cohesive analysis. This ensures that there is enough data to establish a baseline pattern and compare different entities within a service.
C) Anomaly detection automatically generates notable events when KPI data diverges from the pattern. You can configure the sensitivity and severity of the anomaly detection alerts and assign them to episodes or teams. Reference: [Anomaly Detection]
NEW QUESTION # 55
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