2026 Latest SPLK-1002 dumps – Instant Download PDF [Q37-Q53]

The following search would create a graph similar to the one below:
index_internal sourcetype=Savesplunker | fields sourcetype, status | transaction status maxspan=1d | timechart
count by status
The search does the following:
It uses index_internal to specify the internal index that contains Splunk logs and metrics.
It uses sourcetype=Savesplunker to filter events by the sourcetype that indicates the Splunk Enterprise
Security app.
It uses fields sourcetype, status to keep only the sourcetype and status fields in the events.
It uses transaction status maxspan=1d to group events into transactions based on the status field with a
maximum time span of one day between the first and last events in a transaction.
It uses timechart count by status to create a time-based chart that shows the count of transactions for
each status value over time.
The graph shows the following:
It is a line graph with two lines, one yellow and one blue.
The x-axis is labeled with dates from Wed, Apr 4, 2018 to Tue, Apr 10, 2018.
The y-axis is labeled with numbers from 0 to 15.
The yellow line represents “shipped” and the blue line represents “success”.
The yellow line has a steady increase from 0 to 15, while the blue line has a sharp increase from 0 to 5,
then a decrease to 0, and then a sharp increase to 10.
The graph is titled “Type”.
Therefore, option C is the correct answer.

The correct syntax to find events associated with a tag in Splunk is tag= < value > 1. So, the correct answer is D). tag= < value > . This syntax allows you to annotate specified fields in your search results with tags1.
In Splunk, tags are a type of knowledge object that you can use to add meaningful aliases to field values in your data1. For example, if you have a field called status_code in your data, you might have different status codes like 200, 404, 500, etc. You can create tags for these status codes like success for 200, not_found for
404, and server_error for 500. Then, you can use the tag command in your searches to find events associated with these tags1.
Here is an example of how you can use the tag command in a search:
index=main sourcetype=access_combined | tag status_code
In this search, the tag command annotates the status_code field in the search results with the corresponding tags. If you have tagged the status code 200 with success, the status code 404 with not_found, and the status code 500 with server_error, the search results will include these tags1.
You can also use the tag command with a specific tag value to find events associated with that tag. For example, the following search finds all events where the status code is tagged with success:
index=main sourcetype=access_combined | tag status_code | search tag::status_code=success In this search, the tag command annotates the status_code field with the corresponding tags, and the search command filters the results to include only events where the status_code field is tagged with success1.

Reference:
The Splunk Common Information Model (CIM) add-on is a collection of pre-built data models and knowledge objects that help you normalize your data from different sources and make it easier to analyze and report on it3. The CIM add-on includes several data models that cover various domains such as Alerts, Email, Database, Network Traffic, Web and more3. Therefore, options A, B and C are correct because they are names of some of the data models included in the CIM add-on. Option D is incorrect because User permissions is not a name of a data model in the CIM add-on.

Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/Definesearchmacros The macro definition below shows a macro that tracks user sessions based on two arguments: action and JSESSIONID.
sessiontracker(2)
The macro definition does the following:
It specifies the name of the macro as sessiontracker. This is the name that will be used to execute the macro in a search string.
It specifies the number of arguments for the macro as 2. This indicates that the macro takes two arguments when it is executed.
It specifies the code for the macro as index=main sourcetype=access_combined_wcookie action=$action$ JSESSIONID=$JSESSIONID$ | stats count by JSESSIONID. This is the search string that will be run when the macro is executed. The search string can contain any part of a search, such as search terms, commands, arguments, etc. The search string can also include variables for the arguments using dollar signs around them.
In this case, action and JSESSIONID are variables for the arguments that will be replaced by their values when the macro is executed.
Therefore, to correctly configure the macro, you should enter sessiontracker as the name and action, JSESSIONID as the arguments. Alternatively, you can use sessiontracker(2) as the name and leave the arguments blank.

The fields sidebar is a panel that shows the fields that are present in your search results2. The fields sidebar
does not show all extracted fields, which are fields that are extracted from your raw data using various
methods such as regular expressions, delimiters or key-value pairs2. The fields sidebar only shows selected
fields and interesting fields2. Selected fields are fields that you choose to display in your search results by
clicking on them in the fields sidebar or by using the fields command2. Interesting fields are fields that appear
in at least 20 percent of events or have high variability among values2. Therefore, option C is correct, while
options A and B are incorrect because they are types of fields that the fields sidebar does show.

In Splunk, Pivot is a tool that allows you to report on a specific data set without using the Splunk Search Processing Language (SPL)1. You can use a drag-and-drop interface to design and generate pivots that present different aspects of your data in the form of tables, charts, and other visualizations12.
One of the features of Pivot is that it allows you to save your reports1. This can be useful when you want to reuse a report or share it with others1. Therefore, it’s not true that users cannot share visualizations created with Pivot or that they must use SPL to find events in a Pivot12. It’s also not true that users cannot create visualizations with Pivot, as creating visualizations is one of the main functions of Pivot12.

The transaction command is a Splunk command that finds transactions based on events that meet
various constraints1.
Transactions are made up of the raw text (the _raw field) of each member, the time and date fields of the
earliest member, as well as the union of all other fields of each member1.
The transaction command adds some fields to the raw events that are part of the transaction12. These
fields are:
duration: The difference, in seconds, between the timestamps for the first and last events in the
transaction12.
eventcount: The number of events in the transaction12.
closed_txn: A Boolean field that indicates whether the transaction is closed or evicted2. A
transaction is closed if it meets one of the following conditions: maxevents, maxpause, maxspan,
or startswith2. A transaction is evicted if it does not meet any of these conditions and exceeds the
memory limit specified by maxopentxn or maxopenevents23.
Therefore, evicted transactions can be distinguished from non-evicted transactions by checking the value
of the closed_txn field. The closed_txn field is set to 0, or false, for evicted transactions and 1, or true
for non-evicted, or closed, transactions23.

POST workflow actions are custom actions that send a POST request to a web server when you click on a field value in your search results. POST workflow actions can be configured with various options, such as label name, base URL, URI parameters, post arguments, app context, etc. One of the options that are required to create a POST workflow action is post arguments. Post arguments are key-value pairs that are sent in the body of the POST request to provide additional information to the web server. Post arguments can include field values from your data by using dollar signs around the field names.

The correct answer is D. limit=0. This is because the limit argument specifies the maximum number of series
to display in the chart. If you set limit=0, no series filtering occurs and all values are returned.You can learn
more about the limit argument and how it works with the agg argument from the Splunk documentation1. The
other options are incorrect because they are not valid values for the limit argument. The limit argument
expects an integer value, not a string or a wildcard.You can learn more about the syntax and usage of the
timechart command from the Splunk documentation23.

When using a field value variable with a Workflow Action, the exclamation mark (!) will escape the data. A
Workflow Action is a custom action that performs a task when you click on a field value in your search
results. A Workflow Action can be configured with various options, such as label name, base URL, URI
parameters, post arguments, app context, etc. A field value variable is a placeholder for the field value that will
be used to replace the variable in the URL or post argument of the Workflow Action. A field value variable is
written as fieldname, where field_name is the name of the field whose value will be used. However, if the field
value contains special characters that need to be escaped, such as spaces, commas, etc., you can use the
exclamation mark (!) before and after the field value variable to escape the data. For example, if you have a
field value variable host, you can write it as !$host! to escape any special characters in the host field value.
Therefore, option B is the correct answer.

The relationship between data models and pivots is that data models provide the datasets for pivots. Data
models are collections of datasets that represent your data in a structured and hierarchical way. Data models
define how your data is organized into objects and fields. Pivots are user interfaces that allow you to create
data visualizations that present different aspects of a data model. Pivots let you select options from menus and
forms to create charts, tables, maps, etc., without writing any SPL code. Pivots use datasets from data models
as their source of data. Pivots and data models are not the same thing, as pivots are tools for visualizing data
models. Pivots do not provide datasets for data models, but rather use them as inputs.
Therefore, only statement A is true about the relationship between data models and pivots.

The transaction and stats commands are two ways to group events from one or more data sources based on common fields or time ranges. The transaction command creates a single event out of a group of related events, while the stats command calculates summary statistics over a group of events. The eval and coalesce commands are used to create or combine fields, not to group events. The format command is used to format the results of a subsearch, not to group events. The top and rare commands are used to rank the most or least common values of a field, not to group events23
1: Splunk Core Certified Power User Track, page 9. 2: Splunk Documentation, transaction command. 3: Splunk Documentation, stats command.

Reference:https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/SetupaGETworkflowaction

The correct answer is B. Use the field values in an HTTP error event to create a new ticket in an external system.
A workflow action is a knowledge object that enables a variety of interactions between fields in events and other web resources. Workflow actions can create HTML links, generate HTTP POST requests, or launch secondary searches based on field values1.
There are three types of workflow actions that can be set up using Splunk Web: GET, POST, and Search2.
GET workflow actions create typical HTML links to do things like perform Google searches on specific values or run domain name queries against external WHOIS databases2.
POST workflow actions generate an HTTP POST request to a specified URI. This action type enables you to do things like creating entries in external issue management systems using a set of relevant field values2.
Search workflow actions launch secondary searches that use specific field values from an event, such as a search that looks for the occurrence of specific combinations of ipaddress and http_status field values in your index over a specific time range2.
Therefore, the example that would use a POST workflow action is B. Use the field values in an HTTP error event to create a new ticket in an external system. This example requires sending an HTTP POST request to the URI of the external system with the field values from the event as arguments.
The other examples would use different types of workflow actions. These examples are:
A) Perform an external IP lookup based on a domain value found in events: This example would use a GET workflow action to create a link to an external IP lookup service with the domain value as a parameter.
C) Launch secondary Splunk searches that use one or more field values from selected events: This example would use a Search workflow action to run another Splunk search with the field values from the event as search terms.
D) Open a web browser to look up an HTTP status code: This example would also use a GET workflow action to create a link to a web page that explains the meaning of the HTTP status code.
Reference:
Splexicon:Workflowaction
About workflow actions in Splunk Web