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SPLK-1001 Splunk Practice Test Questions and Exam Dumps

Question No 1:

In Splunk, you want to search for events specifically from the host named WWW3. Which search string will accurately return only the events from this particular host?

A. host=*
B. host=WWW3
C. host=WWW*
D. Host=WWW3

Answer:

B. host=WWW3

Explanation:

In Splunk, searches are performed based on specific fields and values, and one of the most common fields to filter by is the host. The host field typically represents the name of the machine or system from which the data was collected. To retrieve events from a specific host, you need to accurately specify the host’s name in your search query.

Let’s examine each search string and explain why only one correctly filters events from host=WWW3:

A. host=*:

This search string will return all events from all hosts because the * is a wildcard that matches any value. It does not filter by any specific host, so this query will return results from all hosts, not just from WWW3.

Why Incorrect:
This is not the correct choice because it doesn't filter for the WWW3 host; it returns all data across all hosts in the index.

B. host=WWW3:

This search string accurately filters events from the host WWW3. The host=WWW3 query looks for events where the host field exactly matches WWW3.

Why Correct:
This is the correct choice because it directly specifies that you want to retrieve events only from the host named WWW3. It is case-sensitive, so it will match exactly WWW3 and not other variations.

C. host=WWW:*

The search string host=WWW* uses a wildcard (*) at the end of WWW. This will match any host name that begins with WWW, so it could return events from hosts like WWW1, WWW2, WWW3, and any other host whose name starts with WWW.

Why Incorrect:
While this query will include events from WWW3, it will also include events from other hosts whose names start with WWW, such as WWW1 or WWW2. This is too broad if you only want events from WWW3.

D. Host=WWW3:

This search string is incorrect because Splunk field names are case-sensitive. The correct field name is host, not Host (with a capital "H"). Using Host=WWW3 would return no results because Splunk would not recognize Host as a valid field.

Why Incorrect:
The case sensitivity of Splunk’s search syntax means that Host=WWW3 is not recognized as the correct search term, and as a result, no events would be returned.

The correct search string to return events only from hostWWW3 is B. host=WWW3. This query filters for events where the host field matches exactly WWW3. Understanding the exact case sensitivity and how to use wildcards in Splunk searches is essential for accurate event retrieval.

Therefore, the correct answer is B. host=WWW3.

Question No 2:

You are using Splunk and have run a search. By default, how long does Splunk retain the search job before it is automatically deleted?

A. 10 Minutes
B. 15 Minutes
C. 1 Day
D. 7 Days

Answer:

B. 15 Minutes

Explanation:

In Splunk, when you run a search, the search job is created, and Splunk performs the search and stores the results temporarily. The search job includes both the search query itself and the results produced by the query. After the search has been completed, the search job will persist for a certain amount of time, and then it will be deleted automatically if it is not explicitly saved.

The retention time for a search job by default is 15 minutes. This means that unless the search job is saved (for example, as a report or by exporting the results), it will be automatically deleted 15 minutes after the search completes. The search job is automatically cleaned up by Splunk to manage system resources effectively and prevent the accumulation of unnecessary data.

Let’s review the other options:

A. 10 Minutes:

Explanation:
This is not the default retention time for search jobs in Splunk. The default is 15 minutes, not 10 minutes.

Why Incorrect:
This option underestimates the default retention period for search jobs in Splunk.

B. 15 Minutes:

Explanation:
This is the correct answer. By default, Splunk retains search jobs for 15 minutes after the job is completed. If no further actions (such as saving or exporting) are taken, the job will be deleted after this period.

Why Correct:
This is the default retention period for search jobs in Splunk. It is set to balance between resource usage and the need to access search results within a reasonable time frame.

C. 1 Day:

This is not the default retention period for search jobs. While search jobs could potentially be saved for 1 day (or longer) if explicitly configured to do so, the default retention time is much shorter (15 minutes).

Why Incorrect:
This is not the default behavior in Splunk. It might be useful for reports or saved searches, but not for general search jobs.

D. 7 Days:

This retention period is too long for default search jobs. In Splunk, search jobs are not typically retained for 7 days unless they are saved as reports or dashboards.

Why Incorrect:
This retention period does not apply to regular search jobs in Splunk.

Additional Information:

The retention time for search jobs can be configured in Splunk’s settings if needed. For example, administrators can configure the maximum retention time for search jobs through the web.conf file. However, the default behavior is a 15-minute retention window.

You can adjust the retention time by modifying settings in Splunk’s configuration files or by saving the search jobs if they are required to be accessible for longer periods.

The default retention period for search jobs in Splunk is 15 minutes. After this time, the search job will be automatically deleted unless it is saved or exported. This behavior helps manage system resources and ensures that search job data does not accumulate unnecessarily.

Thus, the correct answer is B. 15 Minutes.

Question No 3:

You are configuring an automatic lookup in Splunk. Before you can create an automatic lookup, which of the following steps must be performed? (Choose all that apply.)

A. The lookup command must be used.
B. The lookup definition must be created.
C. The lookup file must be uploaded to Splunk.
D. The lookup file must be verified using the inputlookup command.

Answer:

B. The lookup definition must be created.
C. The lookup file must be uploaded to Splunk.

Explanation:

In Splunk, automatic lookups are used to enrich event data with additional information by referencing a lookup table. However, before you can configure and use an automatic lookup, certain prerequisites must be completed. Let's break down each of the steps involved in setting up an automatic lookup:

A. The lookup command must be used.

Explanation:
This option is incorrect. While the lookup command is used to apply lookups manually within Splunk searches, it is not a prerequisite for setting up automatic lookups. The automatic lookup feature relies on predefined configurations, not a manual command.

Why Incorrect:
The lookup command is used in searches but is not directly related to setting up automatic lookups.

B. The lookup definition must be created.

Explanation:
This is correct. Before setting up an automatic lookup, you must create a lookup definition. A lookup definition specifies how the lookup file is used, such as what fields are being matched, what the result fields are, and which field from the event data corresponds to the lookup file.

Why Correct:
The lookup definition is essential to establish the relationship between your event data and the lookup table. It defines how data in your lookup file is used to enrich your search results.

C. The lookup file must be uploaded to Splunk.

Explanation:
This is correct. Before you can use a lookup in an automatic lookup configuration, the actual lookup file must be uploaded to Splunk. The file typically contains key-value pairs (or tabular data) that will be referenced in your searches.

Why Correct:
The lookup file contains the data that will be matched with your event data during searches. Without uploading the lookup file to Splunk, the automatic lookup cannot function properly.

D. The lookup file must be verified using the inputlookup command.

Explanation:
This option is incorrect. The inputlookup command is used to retrieve and inspect the contents of a lookup table within a search. While it is useful for testing and inspecting the lookup file, it is not required to verify the lookup file before setting up an automatic lookup.

Why Incorrect:
While inputlookup can help you verify the contents of your lookup file during the configuration process, it is not a prerequisite for setting up the automatic lookup.

Additional Information:

• Automatic Lookup Setup: Once the lookup file is uploaded and the lookup definition is created, you can then configure the automatic lookup itself by specifying the conditions under which the lookup is applied (e.g., matching fields in event data with the lookup file).

• Use Cases for Automatic Lookups: Automatic lookups are often used to enrich logs with additional contextual data, such as adding geolocation information from an IP address, user information from a username, or any other field you want to correlate with event data automatically.

• Configuration Files: The configuration for lookups is typically stored in the props.conf (for field extraction and lookups) and transforms.conf (for defining the lookup file and its operations) files in Splunk.

Before you can configure an automatic lookup in Splunk, you must upload the lookup file to Splunk and create a lookup definition to specify how the lookup should operate. The other options, like using the lookup command or verifying the file with inputlookup, are not essential steps in the creation process.

Thus, the correct answer is B. The lookup definition must be created and C. The lookup file must be uploaded to Splunk.

Question No 4:

In a Splunk deployment, which of the following components typically resides on the machines where data originates, collecting and forwarding log or event data to a central Splunk instance?

A. Indexer
B. Forwarder
C. Search head
D. Deployment server

Answer:

B. Forwarder

Explanation:

In a Splunk environment, data originates from various machines or devices, and the role of forwarding that data to a central Splunk instance is handled by a specific component. To understand this better, let’s break down the roles of each of the Splunk components mentioned in the question:

A. Indexer

Explanation:
An Indexer is responsible for indexing and storing the data that is sent to Splunk. It processes incoming data by parsing, indexing it, and storing it in the Splunk database. While the indexer is a critical component for data storage and searching, it does not typically reside on the source machines where the data originates.

Why Incorrect:
The indexer processes data once it arrives at the central Splunk system, not at the originating source machine. Therefore, it is not the correct answer in this context.

B. Forwarder

Explanation:
A Forwarder is the correct answer. It is a lightweight Splunk component that resides on the machines where the data originates. The forwarder collects logs or event data from local files or system logs and then forwards this data to a central Splunk indexer or a group of indexers for storage and indexing. There are two types of forwarders: the Universal Forwarder (which is a lightweight agent) and the Heavy Forwarder (which performs additional parsing and indexing before forwarding).

Why Correct:
The forwarder is specifically designed to reside on the source machines (like servers or endpoints), collect the data, and send it to the central Splunk infrastructure for further processing and analysis. This is the key component for data collection in a distributed Splunk environment.

C. Search Head

Explanation:
A Search Head is used to search and analyze indexed data in Splunk. It provides the user interface for querying, reporting, and visualizing the data. The search head is typically not involved in data collection or forwarding, and it does not reside on the machines where data originates.

Why Incorrect:
The search head is used for querying and analyzing the data once it has been indexed and stored. It does not perform data collection from source machines, making it an incorrect option in this case.

D. Deployment Server

Explanation:
The Deployment Server is a component used for managing and distributing configurations, apps, and updates to other Splunk instances (such as forwarders and search heads). It is used to maintain consistent configurations across the Splunk deployment but is not typically responsible for collecting or forwarding data.

Why Incorrect:
The deployment server helps with managing configurations but does not directly interact with the data collection or forwarding process, making it unsuitable for this scenario.

Additional Information:

• Forwarders are essential in Splunk's distributed architecture because they minimize the processing load on the source machine and ensure that only relevant data is forwarded to the central indexer. This architecture helps Splunk scale efficiently as it can collect data from a wide range of sources without overwhelming the central system.

• Types of Forwarders:

• Universal Forwarder (UF): A lightweight agent that forwards raw event data from the source machine to the Splunk indexer. It does not perform any parsing or indexing.

• Heavy Forwarder (HF): A more robust forwarder that can parse and index data before sending it to the indexer. It’s typically used when additional processing is needed at the source before sending data to the central indexer.

The correct answer is B. Forwarder, as it is the Splunk component that resides on the machines where the data originates, collecting and forwarding logs or event data to a central Splunk system.

Question No 5:

In a Splunk environment, when scheduling a report, what determines the scope of data that will be included in the report at the time of execution?

A. All data accessible to the User role will appear in the report.
B. All data accessible to the owner of the report will appear in the report.
C. All data accessible to all users will appear in the report until the next time the report is run.
D. The owner of the report can configure permissions so that the report uses either the User role or the owner’s profile at run time.

Answer:

B. All data accessible to the owner of the report will appear in the report.

Explanation:

In Splunk, scheduled reports are often used to automate the process of generating and distributing data-based insights to users. The scope of data that appears in the report at the time of execution is influenced by the permissions and access associated with the user or role that owns the report. Let's break down the options and their relevance:

A. All data accessible to the User role will appear in the report.

Explanation:
This option suggests that data access is determined by the permissions granted to the "User" role, not the owner of the report. However, in Splunk, the data that appears in a scheduled report is determined by the permissions of the owner of the report, not the general user role. Each user may have different data access based on their role, but the scheduled report will use the owner's permissions.

Why Incorrect:
The scope of data appearing in a scheduled report depends on the owner's data access, not the access level of the user role. Therefore, this statement is not accurate.

B. All data accessible to the owner of the report will appear in the report.

Explanation:
The data that appears in a scheduled report is determined by the access permissions of the owner of the report at the time the report is run. The owner’s permissions define what data they can see, and consequently, the scheduled report will only return the data the owner can access when it is executed. The scheduled report runs using the owner's profile, so if they have access to specific datasets, those datasets will appear in the report.

Why Correct:
The correct answer is that the data included in a scheduled report depends on the owner's access permissions, ensuring that the report is consistent with the owner's access rights.

C. All data accessible to all users will appear in the report until the next time the report is run.

Explanation:
This option suggests that the data visible to all users will be included in the report, but it is not accurate. In Splunk, the data scope in a scheduled report is limited to the owner’s permissions at the time of execution, not the permissions of all users. Therefore, this statement misrepresents how data visibility works in scheduled reports.

Why Incorrect:
This is incorrect because the report is not run based on "all users'" permissions; it is based on the owner's permissions. Each user may have access to different data, but the scheduled report only includes the data accessible to the owner.

D. The owner of the report can configure permissions so that the report uses either the User role or the owner’s profile at run time.

Explanation:
While Splunk does allow for some configurability in terms of report permissions, the scope of data in a scheduled report is always based on the permissions of the report owner. The ability to configure the scope based on roles at runtime is not a feature provided in Splunk.

Why Incorrect:
This option is not correct because the report will always use the owner's profile and access permissions, and there's no built-in functionality to dynamically switch between roles (such as the "User" role and the owner's profile) for determining the data scope at runtime.

Additional Information:

In Splunk, the owner of a report plays a crucial role in determining what data the report will access and display when executed. While the owner has full control over the report’s settings, they also have control over which users or roles can access the report itself. For example, even if a user does not have access to certain data, they may still be able to view the report if the permissions are properly configured.

However, the content of the report at runtime is always governed by the access permissions of the owner. Therefore, the data displayed is a result of the owner’s role and access rights at the time the report runs.

The correct answer is B. All data accessible to the owner of the report will appear in the report. Scheduled reports in Splunk are executed based on the permissions granted to the owner, and the data scope reflects the owner’s access rights.

Question No 6:

When writing searches in Splunk, how should Boolean operators (AND, OR, NOT) be formatted?

A. They must be lowercase.
B. They must be uppercase.
C. They must be in quotations.
D. They must be in parentheses.

Answer:

B. They must be uppercase.

Explanation:

In Splunk, Boolean operators play a crucial role in refining search queries and controlling how data is filtered. Understanding how to properly use these operators ensures more accurate and efficient searches, especially when dealing with large datasets. Let's break down each option:

A. They must be lowercase.

Explanation:
In Splunk, Boolean operators (such as AND, OR, and NOT) are not case-sensitive, but they are conventionally written in uppercase. Writing them in lowercase is not incorrect, but it is against the best practice and may lead to confusion, as uppercase is the standard format.

Why Incorrect:
While lowercase operators will work in some cases, the recommended practice is to use uppercase for Boolean operators to maintain clarity and consistency in search queries.

B. They must be uppercase.

Explanation:
In Splunk, Boolean operators like AND, OR, and NOT are typically written in uppercase. This is not just a formatting choice, but a convention followed for clarity and readability in Splunk search queries. This ensures that the operators stand out clearly in the search string, making the query easier to understand and troubleshoot.

For example:

• index=web AND status=200

• source="logs.csv" OR source="events.csv"

Why Correct:
The correct practice in Splunk search syntax is to use uppercase for Boolean operators to enhance clarity and readability. Uppercase makes the operators visually distinct, which helps when analyzing and modifying complex queries.

C. They must be in quotations.

Explanation:
Quotations are used in Splunk to define string literals or search terms, especially for fields containing spaces or special characters. For example:

• index="web" OR source="events.csv"

Why Incorrect:
However, Boolean operators themselves should not be enclosed in quotations. Instead, they must appear as standalone uppercase keywords (AND, OR, NOT) in a search.

D. They must be in parentheses.

Explanation:
Parentheses in Splunk are used to group search conditions and to control the order of operations within complex queries. For instance, you can combine Boolean operators with parentheses for structured queries like this:

• index=web AND (status=200 OR status=404)

Why Incorrect:
While parentheses are important for grouping terms and conditions, Boolean operators themselves do not need to be in parentheses. The parentheses are used to control how the search conditions are evaluated, not to modify the operators themselves.

In Splunk search queries, Boolean operators (AND, OR, NOT) must be written in uppercase. This format follows Splunk's standard syntax for search queries and helps improve the readability of complex searches, ensuring that operators are easily distinguishable from other terms in the query. Therefore, the correct answer is B. They must be uppercase.

Question No 7:

You want to retrieve events in Splunk from two indexes: netfw and netops. Specifically, you want to return events from index=netfw where the event contains the word "failure", and from index=netops where the event contains the words "warn" or "critical". Which search would return the correct results?

A. (index=netfw failure) AND index=netops warn OR critical
B. (index=netfw failure) OR (index=netops (warn OR critical))
C. (index=netfw failure) AND (index=netops (warn OR critical))
D. (index=netfw failure) OR index=netops OR (warn OR critical)

Answer:

B. (index=netfw failure) OR (index=netops (warn OR critical))

Explanation:

To properly form a search that retrieves specific events from different indexes, we must ensure that the search query is logically constructed to target the correct index and terms. Let's break down each option:

A. (index=netfw failure) AND index=netops warn OR critical

Explanation:
In this query, the search is looking for events in both index=netfw where the term "failure" is present AND in index=netops where either "warn" or "critical" is present. However, the query contains a logical error due to missing parentheses around the "warn OR critical" part, which causes the query to be interpreted incorrectly. The operator AND here means both conditions must be true, but due to incorrect grouping, this query will likely return incomplete results.

Why Incorrect:
This search logic is flawed because the AND operator will cause incorrect evaluation of conditions, and the lack of parentheses around the "warn OR critical" condition will lead to unintended behavior.

B. (index=netfw failure) OR (index=netops (warn OR critical))

Explanation:
This search is correctly structured:

• (index=netfw failure) will search for events in index=netfw where the word "failure" appears.

• (index=netops (warn OR critical)) will search for events in index=netops where either "warn" or "critical" appears.

The use of OR ensures that the search will return events from either of these conditions, fulfilling the requirement of retrieving events from both index=netfw with "failure" and index=netops with "warn" or "critical".

Why Correct:
This query correctly returns the results where:

• The event contains the word "failure" in index=netfw.

• The event contains either "warn" or "critical" in index=netops.

C. (index=netfw failure) AND (index=netops (warn OR critical))

Explanation:
This search would attempt to retrieve events where both conditions must be true simultaneously:

• "failure" in index=netfw.

• "warn" or "critical" in index=netops.

However, since an event cannot simultaneously exist in both indexes, this query is logically incorrect because it's asking for events that meet both conditions across different indexes in a way that is not possible.

Why Incorrect:
This query would fail to return results because an event cannot be in both netfw and netops at the same time, and the AND operator is incorrectly used here.

D. (index=netfw failure) OR index=netops OR (warn OR critical)

Explanation:
This search is also incorrectly structured. It uses OR between three separate conditions:

• (index=netfw failure) — correctly looking for "failure" in netfw.

• index=netops — searches for all events in netops (which isn't what is required).

• (warn OR critical) — this part alone will search for events that contain "warn" or "critical", but it doesn't specify index=netops for these terms.

Why Incorrect:
This search is too broad because it doesn't properly group the conditions related to index=netops and doesn't limit the terms "warn" and "critical" to the correct index. As a result, it will return irrelevant data from index=netops and any events containing "warn" or "critical".

The correct search that will return the desired results is B. (index=netfw failure) OR (index=netops (warn OR critical)). This search correctly targets the events from both index=netfw and index=netops with the appropriate terms and uses logical grouping to ensure accurate results.

Question No 8:

You are constructing a Splunk search query to retrieve data from the security index with the access_* sourcetype. You want to filter the results by the status code 200 and then calculate the count of events, grouped by the price field. What is the correct placement of the pipe (|) in the search query?

A. index=security sourcetype=access_* status=200 stats | count by price
B. index=security sourcetype=access_* status=200 | stats count by price
C. index=security sourcetype=access_* status=200 | stats count | by price
D. index=security sourcetype=access_* | status=200 | stats count by price

Answer:

B. index=security sourcetype=access_ status=200 | stats count by price*

Explanation:

In Splunk, the pipe (|) is used to separate different stages in the search process, with each stage representing a transformation of the data. Understanding the correct placement of the pipe is essential for building effective search queries.

Let’s break down the components of the query and the logic behind the pipe placement:

Correct Query:

B. index=security sourcetype=access_ status=200 | stats count by price*

Explanation:

• index=security sourcetype=access_ status=200*: This part of the query filters the data to include only events from the security index with a sourcetype that starts with access_ and where the status field is 200. This is the initial filtering step.

• |: The pipe separates the initial filtering from the next step, which involves applying a statistical function to the filtered data.

• stats count by price: This is the next stage, where the stats command is used to count the number of events, grouped by the price field. The stats command operates on the results of the preceding filter.

This sequence ensures that only events with status=200 are passed to the stats function, and the count of those events is calculated per unique price value.

Other Options:

A. index=security sourcetype=access_ status=200 stats | count by price*

Explanation: This query is incorrect because stats is placed before the pipe. The stats command needs to come after the filter (status=200), not before. This would result in an error, as the stats command needs to operate on the data retrieved after filtering.

C. index=security sourcetype=access_ status=200 | stats count | by price*

Explanation: This query is also incorrect because of the extra pipe (|) before the by price part. The correct syntax is stats count by price without an extra pipe between count and by price.

D. index=security sourcetype=access_ | status=200 | stats count by price*

Explanation: In this query, the status=200 condition is incorrectly placed after the first pipe. The status=200 condition should be part of the initial filter before the pipe, not after it. The | should come only after the filtering conditions are applied.

The correct answer is B because it correctly applies the filtering condition status=200 before using the pipe to pass the filtered data to the stats command, which counts the number of events by the price field. This is the proper structure for a Splunk query that performs data filtering and aggregation in sequence.

Question No 9:

You are using the top command in Splunk to identify the most frequent values of a field. The top command has several options that allow for further customization of the results. Which of the following constraints can be used with the top command to modify the output?

A. limit
B. useperc
C. addtotals
D. fieldcount

Answer:

A. limit

Explanation:

The top command in Splunk is used to display the most common values of a specified field and their associated frequency. It is a very useful command for summarizing and identifying patterns in your data. The top command also has a set of optional constraints that can be applied to adjust the output based on specific requirements.

Explanation of Constraints:

A. limit
The limit option is used to specify the maximum number of results (or rows) to display. By default, the top command will display the top 10 most frequent values. You can use the limit constraint to increase or decrease this number according to your needs. For example, if you want to see the top 20 values instead of just the default top 10, you can add limit=20.

Example:
| top fieldname limit=20

1.  This will return the top 20 values for the specified fieldname.

2. B. useperc
   The useperc constraint is not a valid option for the top command. This option does not exist in Splunk's documentation for the top command.

3. C. addtotals
   The addtotals option is used to add a row that shows the total count of all the values in the field. This can be useful to see the aggregate count of all the events that fall under the specified field. While this option is valid in some other commands, it is not typically used directly with the top command.

4. D. fieldcount
   The fieldcount option is also not a valid constraint for the top command. While this might sound like a useful option, it does not apply in the context of Splunk's top command.

The correct answer is A. limit because it is the only valid constraint in the list that can be used with the top command to modify the number of results returned. The limit option is commonly used when you need more than the default 10 results or when you want to limit the results to a smaller set. Other options like useperc, addtotals, and fieldcount are not valid constraints for the top command.

By using the limit option, you can effectively control the number of top values that are displayed in your Splunk search results, making it a flexible and powerful tool for data analysis.

Question No 10:

You are editing a dashboard in Splunk, and you need to make changes to its panels and layout. There are several options available to modify how the dashboard is displayed and the data it shows. Which of the following actions can you take when editing a dashboard in Splunk? (Choose all that apply.)

A. Add an output.
B. Export a dashboard panel.
C. Modify the chart type displayed in a dashboard panel.
D. Drag a dashboard panel to a different location on the dashboard.

Answer:

B. Export a dashboard panel.
C. Modify the chart type displayed in a dashboard panel.
D. Drag a dashboard panel to a different location on the dashboard.

Explanation:

When working with Splunk dashboards, there are several customizable options that allow users to modify and optimize how data is displayed. These options are crucial for creating interactive and user-friendly dashboards, especially when multiple users need to access and analyze data.

Let's break down each of the options listed:

A. Add an output

This option is not typically available when editing a dashboard. In Splunk dashboards, outputs are generally not added directly. Instead, users often create visualizations or panels that display the results of search queries, but outputs like dropdowns or input fields for user interaction are handled by specific input elements or configuration settings. Thus, this option is not a valid action when editing a dashboard.

B. Export a dashboard panel

This is a valid option. You can export a dashboard panel (or the entire dashboard) in Splunk for sharing or further use. Exporting a panel usually involves exporting the data or the visual representation of that panel, which can be saved in formats like CSV or PNG, depending on the type of panel. This option allows users to share their insights or reuse them in other contexts.

Example of exporting a panel:
When you click on the panel options, you can export the results to a file format, such as CSV, if the panel displays tabular data, or export a PNG file for images or charts.

C. Modify the chart type displayed in a dashboard panel

This is a valid option. You can modify the chart type in a dashboard panel to change how the data is visualized. Splunk provides various chart types, such as bar charts, pie charts, line graphs, and tables, to help present data in the most effective way. You can adjust the visualization to best suit the nature of your data or the insights you want to convey.

Example of modifying chart types:
If a panel is currently displaying a line chart, you can switch it to a bar chart or a pie chart for better visualization, depending on the data's structure.

D. Drag a dashboard panel to a different location on the dashboard

This is also a valid option. You can rearrange dashboard panels by dragging them to different locations on the dashboard. This allows for easy customization of the layout, making the dashboard more user-friendly and aligned with how users want to view the information. It helps in optimizing the space and grouping related panels together.

Example of rearranging panels:
In edit mode, you can drag and drop panels into different positions, making the dashboard more intuitive and easier to navigate for the end user.

When editing a dashboard in Splunk, you have the flexibility to modify the chart type, rearrange dashboard panels, and export a panel for sharing or further analysis. These options enhance user experience and allow for efficient data visualization and management. However, adding an output is not a standard action when editing a dashboard, which makes A. Add an output the incorrect choice.