2023 Current SPLK-3002 dumps Preparation through Our Practice Test
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The SPLK-3002 exam is a vendor-specific certification that is recognized globally as a valuable credential for IT professionals. It is designed for individuals who have already completed the Splunk Certified Power User certification and have experience working with Splunk IT Service Intelligence. Splunk IT Service Intelligence Certified Admin certification exam consists of 65 multiple-choice questions that must be completed within 90 minutes. Candidates must achieve a minimum score of 70% to pass the exam and earn the certification.
NEW QUESTION # 18
Within a correlation search, dynamic field values can be specified with what syntax?
- A. <fieldname /fieldname>
- B. %fieldname%
- C. fieldname
- D. eval(fieldname)
Answer: C
NEW QUESTION # 19
What is the default importance value for dependent services' health scores?
- A. 0
- B. Unassigned
- C. 1
- D. 2
Answer: C
Explanation:
Explanation
By default, impacting service health scores have an importance value of 11.
NEW QUESTION # 20
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 may skip scheduled execution periods.
- C. If this value is set to 0, the scheduler bases its determination of the next scheduled search on the last search execution time.
- 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: C
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 # 21
When changing a service template, which of the following will be added to linked services by default?
- A. Thresholds.
- B. Entity Rules.
- C. Health score.
- D. New KPIs.
Answer: D
Explanation:
C) New KPIs. This is true because when you add new KPIs to a service template, they will be automatically added to all the services that are linked to that template. This helps you keep your services consistent and up-to-date with the latest KPI definitions.
The other options will not be added to linked services by default because:
A) Thresholds. This is not true because when you change thresholds in a service template, they will not affect the existing thresholds in the linked services. You need to manually apply the threshold changes to each linked service if you want them to inherit the new thresholds from the template.
B) Entity rules. This is not true because when you change entity rules in a service template, they will not affect the existing entity rules in the linked services. You need to manually apply the entity rule changes to each linked service if you want them to inherit the new entity rules from the template.
D) Health score. This is not true because when you change health score settings in a service template, they will not affect the existing health score settings in the linked services. You need to manually apply the health score changes to each linked service if you want them to inherit the new health score settings from the template.
NEW QUESTION # 22
Which scenario would benefit most by implementing ITSI?
- A. Monitoring of business services functionality.
- B. Monitoring of system process statuses
- C. Monitoring of system hardware.
- D. Monitoring of retail sales metrics.
Answer: A
NEW QUESTION # 23
Which of the following describes enabling smart mode for an aggregation policy?
- A. Edit the notable event view, enable smart mode, select "fields", and click "Save"
- B. Edit the aggregation policy, enable smart mode, select fields to analyze, click "Save"
- C. Enable grouping in Notable Event Review, select "Smart Mode", select "fields", and click "Save"
- D. Configure -> Policies -> Smart Mode -> Enable, select "fields", click "Save"
Answer: D
Explanation:
Explanation
1. From the ITSI main menu, click Configuration > Notable Event Aggregation Policies.
2. Select a custom policy or the Default Policy.
3. Under Smart Mode grouping, enable Smart Mode.
4. Click Select fields. A dialog displays the fields found in your notable events from the last 24 hours.
NEW QUESTION # 24
Which of the following is a recommended best practice for service and glass table design?
- A. Always use the standard icons for glass table widgets to improve portability.
- B. Plan and implement services first, then build detailed glass tables.
- C. Design glass tables first to discover which KPIs are important.
- D. Start with base searches, then services, and then glass tables.
Answer: B
Explanation:
Reference:
A is the correct answer because it is recommended to plan and implement services first, then build detailed glass tables that reflect the service hierarchy and dependencies. This way, you can ensure that your glass tables provide accurate and meaningful service-level insights. Building glass tables first might lead to unnecessary or irrelevant KPIs that do not align with your service goals. Reference: Splunk IT Service Intelligence Service Design Best Practices
NEW QUESTION # 25
Which of the following is a valid type of Multi-KPI Alert?
- A. Score over composite.
- B. Status over time.
- C. Value over time.
- D. Rise over run.
Answer: C
Explanation:
Reference:
B is the correct answer because value over time is a valid type of Multi-KPI Alert in ITSI. A Multi-KPI Alert is a type of alert that triggers when multiple KPIs from one or more services meet certain conditions within a specified time range. Value over time is a condition that compares the current value of a KPI to its previous values over a specified time range. For example, you can create a Multi-KPI Alert that triggers when the CPU usage and memory usage of a service are both higher than their average values in the last 24 hours. Reference: [Create Multi-KPI alerts in ITSI], [Multi-KPI alert conditions in ITSI]
NEW QUESTION # 26
Which of the following is the best use case for configuring a Multi-KPI Alert?
- A. Comparing anomaly detection between two KPIs.
- B. Using machine learning to evaluate when data falls outside of an expected pattern.
- C. Raising an alert when one or more KPIs indicate an outage is occurring.
- D. Comparing content between two notable events.
Answer: C
Explanation:
Reference:
A multi-KPI alert is a type of correlation search that is based on defined trigger conditions for two or more KPIs. When trigger conditions occur simultaneously for each KPI, the search generates a notable event. For example, you might create a multi-KPI alert based on two common KPIs: CPU load percent and web requests. A sudden simultaneous spike in both CPU load percent and web request KPIs might indicate a DDOS (Distributed Denial of Service) attack. Multi-KPI alerts can bring such trending behaviors to your attention early, so that you can take action to minimize any impact on performance. Multi-KPI alerts are useful for correlating the status of multiple KPIs across multiple services. They help you identify causal relationships, investigate root cause, and provide insights into behaviors across your infrastructure. The best use case for configuring a multi-KPI alert is to raise an alert when one or more KPIs indicate an outage is occurring, such as when the service health score drops below a certain threshold or when multiple KPIs have critical severity levels. Reference: Create multi-KPI alerts in ITSI
NEW QUESTION # 27
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 may skip scheduled execution periods.
- C. If this value is set to 0, the scheduler bases its determination of the next scheduled search on the last search execution time.
- 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: C
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.
NEW QUESTION # 28
Which of the following applies when configuring time policies for KPI thresholds?
- A. A person can only configure 24 policies, one for each hour of the day.
- B. They are great if you expect normal behavior at 1:00 to be different than normal behavior at 5:00
- C. If a person expects a KPI to change significantly through a cycle on a daily basis, don't use it.
- D. It is possible for multiple time policies to overlap.
Answer: B
Explanation:
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.
NEW QUESTION # 29
Which of the following items describe ITSI Backup and Restore functionality? (Choose all that apply.)
- A. ITSI backup is inclusive of KV Store, ITSI Configurations, and index dependencies.
- B. ITSI backups are stored as a collection of JSON formatted files.
- C. A pre-configured default ITSI backup job is provided that can be modified, but not deleted.
- D. kvstore_to_json.py can be used in scripts or command line to backup ITSI for full or partial backups.
Answer: B,D
Explanation:
ITSI provides a kvstore_to_json.py script that lets you backup/restore ITSI configuration data, perform bulk service KPI operations, apply time zone offsets for ITSI objects, and regenerate KPI search schedules.
When you run a backup job, ITSI saves your data to a set of JSON files compressed into a single ZIP file.
Reference:
https://docs.splunk.com/Documentation/ITSI/4.10.2/Configure/kvstorejson
https://docs.splunk.com/Documentation/ITSI/4.10.2/Configure/BackupandRestoreITSIconfig C and D are correct answers because ITSI backup and restore functionality uses kvstore_to_json.py as a command line script or as part of custom scripts to backup ITSI data for full or partial backups. ITSI backups are also stored as a collection of JSON formatted files that contain KV store objects such as services, KPIs, glass tables, etc. A is not a correct answer because there is no pre-configured default ITSI backup job provided. You can create your own backup jobs or use the command line script or custom scripts to backup ITSI data. B is not a correct answer because ITSI backup is not inclusive of index dependencies. ITSI backup only includes KV store objects and optionally some .conf files. You need to use other methods to backup index data. Reference: [Overview of backing up and restoring ITSI KV store data], [Create a full backup of ITSI], [Create a partial backup of ITSI]
NEW QUESTION # 30
Which of the following describes a realistic troubleshooting workflow in ITSI?
- A. Correlation search -> KPI -> Aggregation Policy
- B. Correlation Search -> Deep Dive -> Notable Event
- C. Service Analyzer -> Aggregation Policy -> Deep Dive
- D. Service Analyzer -> Notable Event Review -> Deep Dive
Answer: D
Explanation:
A realistic troubleshooting workflow in ITSI is:
B) Service Analyzer -> Notable Event Review -> Deep Dive
This workflow involves using the Service Analyzer dashboard to monitor the health and performance of your services and KPIs, using the Notable Event Review dashboard to investigate and manage the notable events generated by ITSI, and using the Deep Dive dashboard to analyze the historical trends and anomalies of your KPIs and metrics.
The other workflows are not realistic because they involve components that are not part of the troubleshooting process, such as correlation search, aggregation policy, and KPI. These components are used to create and configure the alerts and episodes that ITSI generates, not to investigate and resolve them. Reference: [Service Analyzer dashboard in ITSI], Overview of Episode Review in ITSI, [Overview of deep dives in ITSI]
NEW QUESTION # 31
Within a correlation search, dynamic field values can be specified with what syntax?
- A. <fieldname /fieldname>
- B. fieldname
- C. %fieldname%
- D. eval(fieldname)
Answer: A
Explanation:
Reference:
B is the correct answer because dynamic field values can be specified with <fieldname /fieldname> syntax within a correlation search. This syntax allows you to insert values from fields returned by the correlation search into alert actions such as email subject or body. For example, <host /host> inserts the value of the host field into the email. Reference: [Use dynamic field values in correlation searches in ITSI]
NEW QUESTION # 32
Which of the following is a characteristic of base searches?
- A. The fewer KPIs that share a common base search, the more efficiency a base search provides, and anomaly detection is more efficient.
- B. The base search will execute whether or not a KPI needs it.
- C. Search expression, entity splitting rules, and thresholds are configured at the base search level.
- D. It is possible to filter to entities assigned to the service for calculating the metrics for the service's KPIs.
Answer: D
Explanation:
Reference:
A base search is a search definition that can be shared across multiple KPIs that use the same data source. Base searches can improve search performance and reduce search load by consolidating multiple similar KPIs. One of the characteristics of base searches is that it is possible to filter to entities assigned to the service for calculating the metrics for the service's KPIs. This means that you can use entity filtering rules to specify which entities are relevant for each KPI based on the base search results. Reference: Create KPI base searches in ITSI, [Filter entities for KPIs based on base searches]
NEW QUESTION # 33
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 both "Split by Entity" and "Filter to Entities in Service".
- C. Select "Yes" for both "Split by Entity" and "Filter to Entities in Service".
- D. Select "No" for "Split by Entity" and "Yes" for "Filter to Entities in Service".
Answer: C
Explanation:
Reference:
A is the correct answer because selecting "Yes" for both "Split by Entity" and "Filter to Entities in Service" allows you to automatically restrict a KPI to only the entities in its service and generate KPI values for each entity. Split by Entity splits the KPI search results by entity alias fields and calculates a separate KPI value for each entity. Filter to Entities in Service filters out any entities that are not part of the service from the KPI search results. This way, you can ensure that your KPI reflects only the relevant entities for your service and provides granular information for each entity. Reference: [Configure KPI settings in ITSI]
NEW QUESTION # 34
What is an episode?
- A. A workflow task.
- B. A notable event.
- C. A notable event group.
- D. A deep dive.
Answer: B
Explanation:
Explanation
It's a deduplicated group of notable events occurring as part of a larger sequence, or an incident or period considered in isolation.
NEW QUESTION # 35
After a notable event has been closed, how long will the meta data for that event remain in the KV Store by default?
- A. 1 year.
- B. 9 months.
- C. 3 months.
- D. 6 months.
Answer: D
Explanation:
By default, notable event metadata is archived after six months to keep the KV store from growing too large.
NEW QUESTION # 36
Which index will contain useful error messages when troubleshooting ITSI issues?
- A. itsi_summary
- B. _internal
- C. _introspection
- D. itsi_notable_audit
Answer: B
Explanation:
Reference:
The index that will contain useful error messages when troubleshooting ITSI issues is:
B) _internal. This is true because the _internal index contains logs and metrics generated by Splunk processes, such as splunkd and metrics.log. These logs can help you diagnose problems with your Splunk environment, including ITSI components and features.
The other indexes will not contain useful error messages because:
A) _introspection. This is not true because the _introspection index contains data about Splunk resource usage, such as CPU, memory, disk space, and so on. These data can help you monitor the performance and health of your Splunk environment, but not the error messages.
C) itsi_summary. This is not true because the itsi_summary index contains summarized data for your KPIs and services, such as health scores, severity levels, threshold values, and so on. These data can help you analyze the trends and anomalies of your IT services, but not the error messages.
D) itsi_notable_audit. This is not true because the itsi_notable_audit index contains audit data for your notable events and episodes, such as creation time, owner
NEW QUESTION # 37
Which of the following items apply to anomaly detection? (Choose all that apply.)
- A. There are 3 types of anomaly detection supported in ITSI: adhoc, trending, and cohesive.
- B. A minimum of 24 hours of data is needed for anomaly detection, and a minimum of 4 entities for cohesive analysis.
- C. Use AD on KPIs that have an unestablished baseline of data points. This allows the ML pattern to perform it's magic.
- D. Anomaly detection automatically generates notable events when KPI data diverges from the pattern.
Answer: B,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 # 38
When in maintenance mode, which of the following is accurate?
- A. Maintenance mode slots are scheduled on a per hour basis.
- B. Once the window is over, KPIs and notable events will begin to be generated again.
- C. Service health scores and KPI events are deleted until the window is over.
- D. KPIs are shown in blue while in maintenance mode.
Answer: B
NEW QUESTION # 39
When must a service define entity rules?
- A. To enable entity cohesion anomaly detection.
- B. If some or all of the KPIs in the service will be split by entity.
- C. If the intention is for the KPIs in the service to filter to only entities assigned to the service.
- D. If the intention is for the KPIs in the service to have different aggregate vs. entity KPI values.
Answer: C
Explanation:
Explanation
Provide a value to filter the service to a specific set of entities. These entity rule values are meant to be custom for each service.
NEW QUESTION # 40
Which of the following accurately describes base searches used for KPIs in a service?
- A. A base search can only be used by its service and all dependent services.
- B. All the KPIs in a service use the same base search.
- C. All the metrics in a base search are used by one service.
- D. Base searches can be used for multiple services.
Answer: D
Explanation:
Explanation
KPI base searches let you share a search definition across multiple KPIs in IT Service Intelligence (ITSI).
Create base searches to consolidate multiple similar KPIs, reduce search load, and improve search performance.
NEW QUESTION # 41
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