Splunk SPLK-1002 Splunk Core Certified Power User Exam Exam Practice Test

When using the Field Extractor (FX) in Splunk to perform field extraction, any consistent character can be used as a delimiter. The Field Extractor allows users to define how fields are separated in the raw event data, and as long as the delimiter is consistent, the FX tool can parse and extract the fields correctly.

The correct answer is D. field2 values are replaced with the value of the field1.

A field alias is a way to associate an additional (new) name with an existing field name. A field alias can be used to normalize fields from different sources that have different names but represent the same data. Field aliases can also be used to rename fields for clarity or convenience1.

When you create a field alias in Splunk Web, you can select the Overwrite Field Values option to change the behavior of the field alias. This option affects how the Splunk software handles situations where the original field has no value or does not exist, as well as situations where the alias field already exists as a field in your events, alongside the original field2.

If you select the Overwrite Field Values option, the following rules apply:

If the original field does not exist or has no value in an event, the alias field is removed from that event.

If the original field and the alias field both exist in an event, the value of the alias field is replaced with the value of the original field.

If you do not select the Overwrite Field Values option, the following rules apply:

If the original field does not exist or has no value in an event, the alias field is unchanged in that event.

If the original field and the alias field both exist in an event, both fields are retained with their respective values.

Therefore, if you create a field alias where field1—field2 and select the Overwrite Field Values option, and an event only contains values for field1, then the value of field2 will be replaced with the value of field1.

https://docs.splunk.com/Documentation/Splunk/8.1.1/SearchReference/ConditionalFunctions

A POST workflow action in Splunk is designed to send data to an external web service by using HTTP POST requests. This type of workflow action can pass a combination of clear text strings and variables derived from the search results or event data. The clear text strings might include static text or predefined values, while the variables are dynamic elements that represent specific fields or values extracted from the Splunk events. This flexibility allows for constructing detailed and context-specific requests to external systems, enabling various integration and automation scenarios. The POST request can include both types of data, making it versatile for different use cases.

 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 delimiter method in the Field Extractor should be used when fields in events are separated consistently by a specific character (such as a comma, tab, or pipe). This method simplifies extraction without requiring complex regular expressions.

The correct answer is D. An argument can be passed to the inner macro by nesting parentheses.

A search macro is a way to reuse a piece of SPL code in different searches. A search macro can take arguments, which are variables that can be replaced by different values when the macro is called. A search macro can also contain another search macro within it, which is called a nested macro. A nested macro can also take arguments, which can be passed from the outer macro or directly from the search string.

To pass an argument to the inner macro, you need to use parentheses to enclose the argument value and separate it from the outer macro argument. For example, if you have a search macro named outer_macro (1) that contains another search macro named inner_macro (2), and both macros take one argument each, you can pass an argument to the inner macro by using the following syntax:

outer_macro (argument1, inner_macro (argument2))

This will replace the argument1 and argument2 with the values you provide in the search string. For example, if you want to pass “foo” as the argument1 and “bar” as the argument2, you can write:

outer_macro ("foo", inner_macro ("bar"))

This will expand the macros with the corresponding arguments and run the SPL code contained in them.

In Splunk, data sets used in the Pivot tool are derived from data models. The Pivot tool allows users to create reports and visualizations based on the structured information available in data models.

POST workflow actions allow parameters to contain both fixed values and values substituted from event fields.

Extract: “POST arguments can include static text, field value substitutions, or a combination of both.”

The chart command with sum(price) by product, region will return a table where the total revenue (price) is aggregated (sum) for each product and sales region. This is the correct way to aggregate data in Splunk.

The maxspan option in the transaction command limits the maximum time span of the transaction to the specified duration, in this case, 5 minutes. This ensures that only events within that time window are grouped into one transaction.

Normalize your data for each of these fields using a combination of field aliases, field extractions, and lookups.

https://docs.splunk.com/Documentation/CIM/4.15.0/User/UsetheCIMtonormalizedataatsearchtime

This search will run the third_party_outages macro and pass the arguments EMEA and -24h to the macro definition. A search macro is a reusable chunk of SPL that can be inserted into other searches. A search macro can take arguments that are used to resolve the search string at execution time. The syntax for using a search macro is macro_name (argument1, argument2, ...).ReferencesSee Use search macros in searches and Search macro examples in the Splunk Documentation.

To search for a tag on a specific field, Splunk requires the syntax tag:: < field > = < tagname > .

Extract: “To search for a tag associated with a field, use tag:: < field > = < tagname > .”

Thus, tag::host=prod is correct.

The fillnull command can be used to replace null values in specific fields. The correct equivalent expression for the given eval statement would involve using fillnull twice, once for field1 to replace null values with 0, and once for field2 to replace null values with "NO-VALUE".

The Splunk Common Information Model (CIM) add-on helps you normalize your data from different sources and make it easier to analyze and report on it3. One of the functionalities that the CIM add-on relies on to normalize fields with different names is field aliases3. Field aliases allow you to assign an alternative name to an existing field without changing the original field name or value2. By using field aliases, you can map different field names from different sources or sourcetypes to a common field name that conforms to the CIM standard3. Therefore, option B is correct, while options A, C and D are incorrect.

The transaction command groups related events based on shared field values. The maxspan argument specifies the maximum time span allowed between the earliest and latest events in a transaction.

Extract: “Use the maxspan argument to specify the maximum duration of a transaction. Events that exceed this time span are not grouped into the same transaction.”

Therefore, transaction user host maxspan=15s groups events by user and host only when they occur within 15 seconds of each other.

The Common Information Model (CIM) add-on in Splunk applies preconfigured data models to data at search time. This means that when a search is executed, the CIM add-on uses its predefined data models to normalize and map the relevant data to a common format. This approach ensures that data is interpreted and analyzed consistently across various datasets without modifying the data at index time.

The fillnull command replaces null values in fields with a specified replacement value.

Extract: “Use fillnull to replace null field values with a string or numeric value that you specify.”

Thus, in this case, all null field values are replaced with “Unknown.”

When you mouse over and click to add a search term from the Fields sidebar or from an event in your search results, Splunk automatically adds the term to your search string with an implied AND operator2. However, this does not apply to some Boolean operators such as OR, NOT and parentheses (). These operators are not implied when you add a search term and you have to type them manually if you want to use them in your search string2. Therefore, options A, B and D are correct, while option C is incorrect because AND is implied when you add a search term.

If a search returns statistics, it can be viewed as a chart2. Statistics are tabular data that show the relationship between two or more fields2. You can create statistics by using commands such as stats, chart or timechart2. You can view statistics as a chart by selecting the Visualization tab in the Search app and choosing a chart type such as column, line or pie2. Therefore, option B is correct, while options A, C and D are incorrect because they are not types of data that can be viewed as a chart.

The timechart command buckets data in time intervals depending on the selected time range2. The timechart command is similar to the chart command but it automatically groups events into time buckets based on the _time field2. The size of the time buckets depends on the time range that you select for your search. For example, if you select Last 24 hours as your time range, Splunk will use 30-minute buckets for your timechart. If you select Last 7 days as your time range, Splunk will use 4-hour buckets for your timechart2. Therefore, option B is correct, while options A and C are incorrect because they are not factors that affect the size of the time buckets.

An event type in Splunk is defined by a search string that returns a specific set of events. The search string index=games sourcetype=score player=* score > 9999 is valid because it filters events based on specific criteria directly within the main search command. This search will find all events in the games index with a sourcetype of score, where the player field exists, and the score is greater than 9999. This specificity and direct filtering make it suitable for defining an event type.

The transaction command allows you to correlate events across multiple sources. The transaction command is a search command that allows you to group events into transactions based on some common characteristics, such as fields, time, or both. A transaction is a group of events that share one or more fields that relate them to each other. A transaction can span across multiple sources or sourcetypes that have different formats or structures of data. The transaction command can help you correlate events across multiple sources by using the common fields as the basis for grouping. The transaction command can also create some additional fields for each transaction, such as duration, eventcount, startime, etc.

Field aliases can only be applied after fields have been extracted .

Extract: “Field extraction occurs before field aliasing in the search-time data processing order. Field aliases depend on extracted field names to function.”

Thus, fields must first be extracted before any alias can be assigned.

The timechart command is used to create a time-series chart of statistical values based on your search results2. You can use the timechart command with a by clause to split the results by one or more fields and create multiple series in the chart2. However, you can only list one field after the by clause when using the timechart command because _time is already implied as the x-axis of the chart2. Therefore, option B is correct, while options A, C and D are incorrect.

The tag=Priv* search will return events containing a tag named Privileged, as well as any other tag that starts with Priv. The asterisk (*) is a wildcard character that matches zero or more characters. The other searches will not match the exact tag name.

The type of workflow action that sends field values to an external resource (e.g. a ticketing system) is POST. A POST workflow action allows you to send a POST request to a URI location with field values or static values as arguments. For example, you can use a POST workflow action to create a ticket in an external system with information from an event.

The appendcols command in Splunk is used to connect an additional table of data directly to the right side of the existing table. It appends the results of a subsearch as new fields to the current results, effectively adding columns to the existing table.

The correct answer is D. eval.

A calculated field is a field that is added to events at search time by using an eval expression. A calculated field can use the values of two or more fields that are already present in the events to perform calculations. A calculated field can be defined with Splunk Web or in the props.conf file. They can be used in searches, reports, dashboards, and data models like any other extracted field1.

A calculated field is a shortcut for performing repetitive, long, or complex transformations using the eval command. The eval command is used to create or modify fields by using expressions. The eval command can perform mathematical, string, date and time, comparison, logical, and other operations on fields or values2.

For example, if you want to create a new field named total that is the sum of two fields named price and tax, you can use the eval command as follows:

| eval total=price+tax

However, if you want to use this new field in multiple searches, reports, or dashboards, you can create a calculated field instead of writing the eval command every time. To create a calculated field with Splunk Web, you need to go to Settings > Fields > Calculated Fields and enter the name of the new field (total), the name of the sourcetype (sales), and the eval expression (price+tax). This will create a calculated field named total that will be added to all events with the sourcetype sales at search time. You can then use the total field like any other extracted field without writing the eval expression1.

The other options are not correct because they are not related to calculated fields. These options are:

A. transaction: This command is used to group events that share some common values into a single record, called a transaction. A transaction can span multiple events and multiple sources, and can be useful for correlating events that are related but not contiguous3.

B. lookup: This command is used to enrich events with additional fields from an external source, such as a CSV file or a database. A lookup can add fields to events based on the values of existing fields, such as host, source, sourcetype, or any other extracted field.

C. stats: This command is used to calculate summary statistics on the fields in the search results, such as count, sum, average, etc. It can be used to group and aggregate data by one or more fields.

In Splunk, a field alias is used to create an alternative name for an existing field, making it easier to refer to data in a consistent manner across different searches and reports. Field aliases can be applied to both calculated fields and extracted fields. Calculated fields are those that are created using eval expressions, while extracted fields are typically those parsed from the raw data at index time or search time. This flexibility allows users to streamline their searches by using more intuitive field names without altering the underlying data. Field aliases cannot be applied to data in a lookup table, specific individual fields within a dataset, or directly to a host, source, or sourcetype.

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The correct answers are B. duration and D. transaction id.

The explanation is as follows:

The transaction command is a Splunk command that finds transactions based on events that meet various constraints12.

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 member12.

The transaction command adds some fields to the raw events that are part of the transaction123. These fields are:

duration: The difference, in seconds, between the timestamps for the first and last events in the transaction123.

eventcount: The number of events in the transaction123.

transaction_id: A unique identifier for each transaction3. This field is useful for filtering or joining transactions3.

Therefore, the fields that the transaction command adds to the raw events are duration and transaction_id, which are options B and D in your question.

Highlighted search terms indicate matching search results in Splunk, which means that they show which parts of your events match your search string2. For example, if you search for error OR fail, Splunk will highlight error or fail in your events to show which events match your search string2. Therefore, option D is correct, while options A, B and C are incorrect because they are not indicated by highlighted search terms.

The correct answer is C. Events where values of field A are equal to values of field B.

The where command is used to filter the search results based on an expression that evaluates to true or false. The where command can compare two fields, two values, or a field and a value. The where command can also use functions, operators, and wildcards to create complex expressions1.

The syntax for the where command is:

| where < expression >

The expression can be a comparison, a calculation, a logical operation, or a combination of these. The expression must evaluate to true or false for each event.

To compare two fields with the where command, you need to use the field names without any quotation marks. For example, if you want to find events where the values for the field A match the values for the field B, you can use the following syntax:

| where A=B

This will return only the events where the two fields have the same value.

The other options are not correct because they use different syntax or fields that are not related to the where command. These options are:

A. Events that contain the string value where A=B: This option uses the string value where A=B as a search term, which is not valid syntax for the where command. This option will return events that have the literal text “where A=B” in them.

B. Events that contain the string value A=B: This option uses the string value A=B as a search term, which is not valid syntax for the where command. This option will return events that have the literal text “A=B” in them.

D. Events where field A contains the string value B: This option uses quotation marks around the value B, which is not valid syntax for comparing fields with the where command. Quotation marks are used to enclose phrases or exact matches in a search2. This option will return events where the field A contains the string value “B”.

The transaction command is used to group events that are related by some common fields or conditions, such as start/end values, time span, or pauses. The stats command is used to calculate statistics on a group of events by a common field value.

References

Splunk Community

Splunk Transaction - Exact Details You Need

The Splunk Common Information Model (CIM) Add-on includes a variety of data models designed to normalize data from different sources to allow for cross-source reporting and analysis. Among the data models included, Alerts (Option B) and Email (Option D) are part of the CIM. The Alerts data model is used for data related to alerts and incidents, while the Email data model is used for data pertaining to email messages and transactions. User permissions (Option A) and Databases (Option C) are not data models included in the CIM; rather, they pertain to aspects of data access control and specific types of data sources, respectively, which are outside the scope of the CIM's predefined data models.

This is because an event type is a knowledge object that assigns a user-defined name to a set of events that match a specific search criteria. For example, you can create an event type named successful_purchase for events that have sourcetype=access_combined, status=200, and action=purchase. Then, you can use eventtype=successful_purchase as a search term to find those events. You can also use event types to create alerts, reports, and dashboards. You can learn more about event types from the Splunk documentation1. The other options are incorrect because they do not describe what an event type is. A log level measurement is a field that indicates the severity of an event, such as info, warn, or error. A knowledge object that is applied before fields are extracted is a source type, which identifies the format and structure of the data. Either a log, a metric, or a trace is a type of data that Splunk can ingest and analyze, but not an event type.

The maxspan function of the transaction command allows you to set the maximum total time between the earliest and latest events returned. The maxspan function is an argument that can be used with the transaction command to specify the start and end constraints for the transactions. The maxspan function takes a time modifier as its value, such as 30s, 5m, 1h, etc. The maxspan function sets the maximum time span between the first and last events in a transaction. If the time span between the first and last events exceeds the maxspan value, the transaction will be split into multiple transactions.

When using the Field Extractor (FX) in Splunk for regex field extraction, it's important to select the context in which you want to perform the extraction. The context is essentially the subset of data you're focusing on for your field extraction task.

D. Sourcetype or source: This is the correct option. In the initial steps of using the Field Extractor tool, you're prompted to choose a data type for your field extraction. The options available are typically based on the nature of your data and how it's organized in Splunk. "Sourcetype" refers to the kind of data you're dealing with, a categorization that helps Splunk apply specific processing rules. "Source" refers to the origin of the data, like a specific log file or data input. By selecting either a sourcetype or source, you're narrowing down the dataset on which you'll perform the regex extraction, making it more manageable and relevant.

The fillnull command replaces null values in one or more fields with a specified value. The values option allows you to specify a comma-separated list of values to fill the null values in the corresponding fields. The fields option allows you to specify a comma-separated list of fields to apply the fillnull command to. The eval statement in the question uses the if and isnull functions to check if field1 and field2 have null values and replace them with 0 and “NO-VALUE” respectively. The equivalent expression using fillnull is to use the values option to specify 0 and “NO-VALUE” and the fields option to specify field1 and field22

1: Splunk Core Certified Power User Track, page 9. 2: Splunk Documentation, fillnull command.

The descriptions of the data models that come with the Splunk Common Information Model (CIM) Add-on are documented in the CIM Add-on manual (Option B). This manual provides detailed information about the data models, including their structure, the types of data they are designed to normalize, and how they can be used to facilitate cross-sourcing reporting and analysis.

The eval command supports a number of functions that you can use in your expressions to perform calculations, conversions, string manipulations and more2. One of the eval command functions is tostring(), which converts a numeric value to a string value2. Therefore, option D is correct, while options A, B and C are incorrect because they are not valid eval command functions.

In Splunk data models, child datasets inherit constraints and fields from parent datasets , not the other way around.

Extract: “Child datasets inherit field and constraint definitions from their parent datasets. Changes to child datasets do not affect their parent datasets.”

Therefore, the All Customer Interactions dataset (the parent) remains unaffected by changes to the Category Products child dataset.

The maxpause option of the transaction command in Splunk is used to specify the maximum time allowed between events in a transaction. If the time between events exceeds the maxpause value, those events are not considered part of the same transaction.

It provides users with a standardized set of field names and tags to normalize data.The Splunk CIM add-on provides a standardized set of field names and data models, which allows users to normalize and categorize data from various sources into a common format. This helps with data interoperability and enables faster, more consistent reporting and searching across different data sources.References:Splunk Documentation - Common Information Model (CIM)

https://docs.splunk.com/Documentation/Splunk/8.0.2/SearchReference/Eval

The eval command calculates an expression and puts the resulting value into a search results field.

If the field name that you specify does not match a field in the output, a new field is added to the search results.

If the field name that you specify matches a field name that already exists in the search results, the results of the eval expression overwrite the values in that field.

Splunk event types are based on search strings that cannot contain pipes or subsearches.

Extract: “Event type search strings must not contain a pipe (|) and cannot include transforming or filtering commands.”

Thus, only option B is a valid event type definition because it is a simple base search without pipelines or subsearches.

The datamodel command is a generating command that searches a data model.

Extract: “The datamodel command lets you search data model datasets. It returns events from the data model when used with the search keyword.”

Thus, the search returns events from the data model Application_State.

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 correct answer is C. Distributable streaming. This is because the eval command is a type of command that can run on the indexers before the results are sent to the search head. This reduces the amount of data that needs to be transferred and improves the search performance. Distributable streaming commands can operate on each event or result individually, without depending on other events or results. You can learn more about the types of commands and how they affect search performance from the Splunk documentation1.

The correct answer is B. Pivot1.

In Splunk, Pivot is a tool that uses data models to generate reports and dashboard panels without the need for users to write or understand Splunk’s Search Processing Language (SPL)1. Data models enable users of Pivot to create compelling reports and dashboards1. When a Pivot user designs a pivot report, they select the data model that represents the category of event data that they want to work with1. Then they select a dataset within that data model that represents the specific dataset on which they want to report1. This makes Pivot a powerful tool for users who need to create visualizations but do not have a deep understanding of SPL1.

Creating a field alias in Splunk does not modify or remove the original field. Instead, the alias allows the same data to be accessed using a different field name without affecting the original field.

In this case, the outer join is applied, which means that all rows from the outer (left) table will be included, even if there are no matching rows in the inner (right) table. The result will include all five rows from the outer table, with the matched data from the inner table where employeeNumber matches. Rows without matching employeeNumber values will have null values for the fields from the inner table.

The correct answer is C. ‘weekly_sales (3.99, 10)’. This is because search macros accept arguments without quotation marks or dollar signs, and the number of arguments must match the number of parameters defined in the macro. The other options are incorrect because they either use quotation marks or dollar signs around the arguments, or they provide a different number of arguments than the macro expects. You can learn more about how to use search macros in searches from the Splunk documentation1.

The following statements about tags are true: tags are based on field/value pairs and tags categorize events based on a search. Tags are custom labels that can be applied to fields or field values to provide additional context or meaning for your data. Tags can be used to filter or analyze your data based on common concepts or themes. Tags can be created by using various methods, such as search commands, configuration files, user interfaces, etc. Some of the characteristics of tags are:

Tags are based on field/value pairs: This means that tags are associated with a specific field name and a specific field value. For example, you can create a tag called “alert” for the field name “status” and the field value “critical”. This means that only events that have status=critical will have the “alert” tag applied to them.

Tags categorize events based on a search: This means that tags are defined by a search string that matches the events that you want to tag. For example, you can create a tag called “web” for the search string sourcetype=access_combined. This means that only events that match the search string sourcetype=access_combined will have the “web” tag applied to them.

The following statements about tags are false: tags are case-insensitive and tags are designed to make data more understandable. Tags are case-sensitive and tags are designed to make data more searchable. Tags are case-sensitive: This means that tags must match the exact case of the field name and field value that they are associated with. For example, if you create a tag called “alert” for the field name “status” and the field value “critical”, it will not apply to events that have status=CRITICAL or Status=critical. Tags are designed to make data more searchable: This means that tags can help you find relevant events or patterns in your data by using common concepts or themes. For example, if you create a tag called “web” for the search string sourcetype=access_combined, you can use tag=web to find all events related to web activity.

https://docs.splunk.com/Documentation/Splunk/8.0.2/Knowledge/SetupaGETworkflowaction

Define a GET workflow action

Steps

Navigate to Settings > Fields > Workflow Actions.

Click New to open up a new workflow action form.

Define a Label for the action.

The Label field enables you to define the text that is displayed in either the field or event workflow menu. Labels can be static or include the value of relevant fields.

Determine whether the workflow action applies to specific fields or event types in your data.

Use Apply only to the following fields to identify one or more fields. When you identify fields, the workflow action only appears for events that have those fields, either in their event menu or field menus. If you leave it blank or enter an asterisk the action appears in menus for all fields.

Use Apply only to the following event types to identify one or more event types. If you identify an event type, the workflow action only appears in the event menus for events that belong to the event type.

For Show action in determine whether you want the action to appear in the Event menu, the Fields menus, or Both.

Set Action type to link.

In URI provide a URI for the location of the external resource that you want to send your field values to.

Similar to the Label setting, when you declare the value of a field, you use the name of the field enclosed by dollar signs.

Variables passed in GET actions via URIs are automatically URL encoded during transmission. This means you can include values that have spaces between words or punctuation characters.

Under Open link in, determine whether the workflow action displays in the current window or if it opens the link in a new window.

Set the Link method to get.

Click Save to save your workflow action definition.

In workflow action definitions, field tokens are enclosed with dollar signs to represent field values dynamically.

Extract: “In workflow actions, enclose field names with dollar signs ($fieldname$) to insert their values dynamically into URLs or searches.”

Event types are custom categories of events that are based on search criteria. Event types can be used to label events with meaningful names, such as error, success, login, logout, etc. Event types can also be used to create transactions, alerts, reports, dashboards, etc. Event types can be created in two ways:

By going to the Settings menu and clicking Event Types > New. This will open a form where you can enter the name, description, search string, app context, and tags for the event type.

By selecting an event in search results and clicking Event Actions > Build Event Type. This will open a dialog box where you can enter the name and description for the event type. The search string will be automatically populated based on the selected event.

Event types cannot be created by using the searchtypes command in the search bar, as this command does not exist in Splunk. Event types can also be created by editing the event_type stanza in the transforms.conf file, not the props.conf file.

The timeline is a graphical representation of your search results that shows the distribution of events over time2. You can use the timeline to zoom in or out of a specific time range or to select one or more bars on the timeline to filter your results by that time range2. However, these actions will not re-run the search, but rather refine the existing results based on the selected time range2. Therefore, options B, C and D are correct, while option A is incorrect because zooming out will re-run the search with a broader time range.

The Field Extractor (FX) allows you to use regular expressions (regex) to extract fields from your events using a graphical interface or by manually editing the regex2. When you use the FX to perform a regex field extraction, you can use the require option to specify a string that must be present in an event for it to be included in the extraction2. This way, you can filter out events that do not contain the required string and focus on the events that are relevant for your extraction2. Therefore, option D is correct, while options A, B and C are incorrect.

In Splunk, a variable for a macro is defined by placing the variable name inside dollar signs, like this: $variable name$. This syntax allows the macro to dynamically replace the variable with the appropriate value when the macro is invoked within a search. Using this method ensures that the search strings can be dynamically adjusted based on the variable's value at runtime.

The span option is used to specify the time span for the timechart command. The span value can be a number followed by a time unit, such as h for hour, d for day, w for week, etc. The span value determines how the data is grouped into time buckets. For example, span=12h means that the data is grouped into 12-hour intervals. The timespan option is not a valid option for the timechart command2

1: Splunk Core Certified Power User Track, page 9. 2: Splunk Documentation, timechart command.

In Splunk, the NOT operator is used to exclude events from your search results. The search index=network NOT StatusCode=200 will return all events in the ‘network’ index where the StatusCode is not 200. This includes events where the StatusCode field is present and has a value other than 200, as well as events where the StatusCode field is not present at all.

The Splunk Common Information Model (CIM) Add-on is a foundational component for many Splunk apps, providing a common framework for data normalization and field extraction. This add-on includes a set of pre-configured data models that are essential for consistent reporting, searching, and correlation across various types of data. These data models help standardize field names and event structures, ensuring that data from disparate sources can be queried in a uniform way. While the CIM Add-on facilitates the use of standardized sourcetypes and supports data validation, the primary feature it offers is the set of pre-configured data models which are crucial for maintaining consistency across different datasets.

The correct answer is C. _time.

The timechart command creates a time series chart with corresponding table of statistics, with time used as the X-axis1. You can specify a split-by field, where each distinct value of the split-by field becomes a series in the chart1. In this case, the split-by field is action, which means that the chart will have different lines for different actions, such as accept, reject, or fail2. The count function will calculate the number of events for each action in each time bin1.

For example, the following image shows a timechart of the count by action for a similar search3:

As you can see, the x-axis is populated by the _time field, which represents the time range of the search. The y-axis is populated by the count function, which represents the number of events for each action. The legend shows the different values of the action field, which are used to split the chart into different series.

To create a tag, the user must have the tag capability associated with their user role. The tag capability allows the user to create, edit, and delete tags. The user does not need to identify a field:value pair, have the Power role, or be able to edit the sourcetype the tag applies to.ReferencesSee Define and manage tags in Settings and [About capabilities] in the Splunk Documentation.

Tags are aliases or alternative names for field values in Splunk. They can make your data more understandable by using common or descriptive terms instead of cryptic or technical terms. For example, you can tag a field value such as “200” with “OK” or “success” to indicate that it is a HTTP status code for a successful request. Tags are case sensitive, meaning that “OK” and “ok” are different tags. Tags are created at search time, meaning that they are applied when you run a search on your data. Tags are searched by using the syntax tag:: < tagname > , where  < tagname >  is the name of the tag you want to search for.