SPLK-1005 Questions and Answers

The correct attribute/value pair to successfully extract the timestamp from the provided events is TIME_FORMAT = %b %d %H:%M:%S. This format corresponds to the structure of the timestamps in the provided data:

%b represents the abbreviated month name (e.g., Sep).

%d represents the day of the month.

%H:%M:%S represents the time in hours, minutes, and seconds.

This format will correctly extract timestamps like "Sep 12 06:11:58".

Splunk Documentation Reference: Configure Timestamp Recognition

The correct SEDCMD setting to mask the credit card numbers, ensuring that the masked version replaces each digit with an "x" character, is Option A.

The SEDCMD syntax works as follows:

s/ starts the substitute command.

(?cc_num=\d{7})\d{9}/ matches the specific pattern of the credit card number in the logs.

\1xxxxxxxxx replaces the matched portion with the first captured group (the first 7 digits of the cc_num), followed by 9 "x" characters to mask the remaining digits.

/g ensures that the substitution is applied globally, throughout the string.

Thus, Option A correctly implements this requirement.

Splunk Documentation Reference: SEDCMD for Masking Data

The recommended approach for setting the host values based on their origin when files from multiple systems are stored on a centralized log server is to use the host_segment setting. This setting allows you to dynamically set the host value based on a specific segment of the file path, which can be particularly useful when organizing logs from different servers into directories.

Splunk Documentation Reference: Inputs.conf - host_segment

Splunk executes scripts from specific directories that are structured within its installation paths. These directories typically include:

SPLUNK_HOME/etc/system/bin: This directory is used to store scripts that are part of the core Splunk system configuration.

SPLUNK_HOME/etc/apps/<app name>/bin: Each Splunk app can have its own bin directory where scripts specific to that app are stored.

SPLUNK_HOME/bin/scripts: This is a standard directory for storing scripts that may be globally accessible within Splunk's environment.

However, C. SPLUNKHOMS/ctc/scripts/local is not a recognized or standard path used by Splunk for executing scripts. This path does not adhere to the typical directory structure within the SPLUNK_HOME environment, making it the correct answer as it does not correspond to a valid script execution path in Splunk.

Splunk Documentation References:

Using Custom Scripts in Splunk

Directory Structure of SPLUNK_HOME

For input apps that are not permitted on Splunk Cloud, the recommended place to deploy them is on a Universal Forwarder or Heavy Forwarder. These forwarders handle data collection and preprocessing before sending the data to Splunk Cloud. This setup allows organizations to leverage apps and configurations that are not supported directly in the cloud environment.

Splunk Documentation Reference: Forwarding Data to Splunk Cloud

Explanation: When events lack a timestamp, Splunk defaults to using the file modification time, which is accessible metadata for parsing time information if no timestamp is present in the log entry. [Reference: Splunk Docs on timestamp recognition]

In a managed Splunk Cloud environment, HTTP Event Collector (HEC) tokens are configured by an administrator through the Splunk Web interface. When setting up a new HEC input, a unique token is automatically generated. This token is then provided to application developers, who will use it to authenticate and send data to Splunk via the HEC endpoint.

This token ensures that the data is correctly ingested and associated with the appropriate inputs and indexes. Unlike the other options, which either involve external tokens or support cases, option B reflects the standard procedure for configuring HEC tokens in Splunk Cloud, where control over tokens remains within the Splunk environment itself.

Splunk Cloud Reference: Splunk's documentation on HEC inputs provides detailed steps on creating and managing tokens within Splunk Cloud. This includes the process of generating tokens, configuring data inputs, and distributing these tokens to application developers.

Source:

Splunk Docs: HTTP Event Collector in Splunk Cloud Platform

Splunk Docs: Create and manage HEC tokens

Explanation: props.conf and transforms.conf define data parsing, transformations, and routing rules, making them essential for data transformations. [Reference: Splunk Docs on props.conf and transforms.conf]

When creating a deployment app in Splunk, certain files and folders are considered essential to ensure proper configuration and operation:

app.conf (in default or local): This is required as it defines the app's metadata and behaviors.

local.meta: This file is important for defining access permissions for the app and is often included.

metadata folder: The metadata folder contains files like local.meta and default.meta and is typically required for defining permissions and other metadata-related settings.

props.conf: While props.conf is essential for many Splunk apps, it is not mandatory unless you need to define specific data parsing or transformation rules.

D. props.conf is the correct answer because, although it is commonly used, it is not a mandatory part of every deployment app. An app may not need data parsing configurations, and thus, props.conf might not be present in some apps.

Splunk Documentation References:

Building Splunk Apps

Deployment Apps

This confirms that props.conf is not a required part of a deployment app, making it the correct answer.

In Splunk, when configuring file and directory monitor inputs, several settings are available that control how data is indexed and processed. These settings are defined in the inputs.conf file. Among the given options:

host: Specifies the hostname associated with the data. It can be set to a static value, or dynamically assigned using settings like host_regex or host_segment.

index: Specifies the index where the data will be stored.

sourcetype: Defines the data type, which helps Splunk to correctly parse and process the data.

TCP_Routing: Used to route data to specific indexers in a distributed environment based on TCP routing rules.

host_regex: Allows you to extract the host from the path or filename using a regular expression.

host_segment: Identifies the segment of the directory structure (path) to use as the host.

Given the options:

Option B is correct because it includes host, index, sourcetype, TCP_Routing, host_regex, and host_segment. These are all valid settings for file and directory monitor inputs in Splunk.

Splunk Documentation References:

Monitor Inputs (inputs.conf)

Host Setting in Inputs

TCP Routing in Inputs

By referring to the Splunk documentation on configuring inputs, it's clear that Option B aligns with the valid settings used for file and directory monitoring, making it the correct choice.

The recommended approach to collect data from network devices is to use a Syslog server with a Universal Forwarder (UF) installed. The network devices send data to the Syslog server, which then forwards the data to Splunk Cloud using the Universal Forwarder. This method ensures reliable data ingestion and processing while maintaining flexibility in handling different types of network device data.

Splunk Documentation Reference: Best practices for getting data in

SEDCMD is a directive used within the props.conf file in Splunk to perform inline data transformations. Specifically, it uses sed-like syntax to modify data as it is being processed.

A. Can only be used to mask or truncate raw data: This is the correct answer because SEDCMD is typically used to mask sensitive data, such as obscuring personally identifiable information (PII) or truncating parts of data to ensure privacy and compliance with security policies. It is not used for more complex transformations such as changing the sourcetype per event.

B. Configured in props.conf and transform.conf: Incorrect, SEDCMD is only configured in props.conf.

C. Can be used to manipulate the sourcetype per event: Incorrect, SEDCMD does not manipulate the sourcetype.

D. Operates on a REGEX pattern match of the source, sourcetype, or host of an event: Incorrect, while SEDCMD uses regex for matching patterns in the data, it does not operate on the source, sourcetype, or host specifically.

Splunk Documentation References:

SEDCMD Usage

Mask Data with SEDCMD

By default, the sc_admin role in Splunk Cloud is granted several important capabilities, including:

indexes_edit: The ability to create, edit, and manage indexes.

fsh_manage: Manage full-stack monitoring integrations.

admin_all_objects: Full administrative control over all objects in Splunk.

can_delete: The ability to delete events using the delete command.

Option C correctly lists these default capabilities for the sc_admin role.

Splunk Documentation Reference: User roles and capabilities

The correct monitor statement to retrieve only files that start with "access" in the directory /opt/log/www2/ is [monitor:///opt/log/www2/access*]. This configuration specifically targets files that begin with the name "access" and will match any such files within that directory, such as "access.log".

Splunk Documentation Reference: Monitor files and directories

In a Splunk Cloud environment, the Data Preview feature is used to create and test new sourcetypes. This feature allows you to upload sample data, configure parsing settings, and define sourcetypes interactively without directly editing configuration files like props.conf or using the CLI.

Splunk Documentation Reference: Data Preview

Explanation: A heavy forwarder is appropriate in this scenario because it can perform additional data parsing, filtering, and routing before forwarding data to Splunk Cloud. This is particularly useful for data that requires preprocessing or cannot be sent directly due to security policies. [Reference: Splunk Docs on forwarder types and capabilities]

In Splunk Cloud, when there is a need for a change request that might involve modifying settings, upgrading, or other actions requiring Splunk Support, the process typically requires submitting a support case.

D. Any person with the appropriate entitlement: This is the correct answer. Any individual who has the necessary permissions or entitlements within the Splunk environment can submit a support case. This includes administrators or users who have been granted the ability to engage with Splunk Support. The request does not necessarily have to come from a Certified Splunk Cloud Administrator or the infrastructure owner; rather, it can be submitted by anyone with the correct level of access.

Splunk Documentation References:

Submitting a Splunk Support Case

Managing User Roles and Entitlements

In Splunk, SEDCMD (Stream Editing Commands) is applied during the Typing Pipeline of the data indexing process. The Typing Pipeline is responsible for various tasks, such as applying regular expressions for field extractions, replacements, and data transformation operations that occur after the initial parsing and aggregation steps.

Here’s how the indexing process works in more detail:

Parsing Pipeline: In this stage, Splunk breaks incoming data into events, identifies timestamps, and assigns metadata.

Merging Pipeline: This stage is responsible for merging events and handling time-based operations.

Typing Pipeline: The Typing Pipeline is where SEDCMD operations occur. It applies regular expressions and replacements, which is essential for modifying raw data before indexing. This pipeline is also responsible for field extraction and other similar operations.

Index Pipeline: Finally, the processed data is indexed and stored, where it becomes available for searching.

Splunk Cloud Reference: To verify this information, you can refer to the official Splunk documentation on the data pipeline and indexing process, specifically focusing on the stages of the indexing pipeline and the roles they play. Splunk Docs often discuss the exact sequence of operations within the pipeline, highlighting when and where commands like SEDCMD are applied during data processing.

Source:

Splunk Docs: Managing Indexers and Clusters of Indexers

Splunk Answers: Community discussions and expert responses frequently clarify where specific operations occur within the pipeline.

The valid method for creating index-time field extractions is to create a configuration app that includes the necessary props.conf and/or transforms.conf configurations. This app can then be uploaded via the UI. Index-time field extractions must be defined in these configuration files to ensure that fields are extracted correctly during indexing.

Splunk Documentation Reference: Index-time field extractions