Free Practice Questions for Splunk SPLK-1003 Exam

The indexing pipeline and the parsing pipeline are the two pipelines that are responsible for transforming the raw data into events and preparing them for indexing. The indexing pipeline applies index-time settings, such as timestamp extraction, line breaking, host extraction, and source type recognition. The parsing pipeline applies parsing settings, such as field extraction, event segmentation, and event annotation.

The Splunk indexing process consists of three main phases: Input, Parsing, and Indexing. Understanding these phases is crucial for configuring data inputs and managing data flow within Splunk.

Input Phase: Splunk receives data from various sources, such as files, network ports, or scripted inputs.

Parsing Phase: Splunk breaks the data into individual events, applies transformations, and extracts timestamps.

Indexing Phase: Splunk writes the parsed events to disk and creates indexes for efficient searching.

From the official Splunk documentation:

"The data pipeline consists of three main phases: input, parsing, and indexing."

— How the Splunk platform indexes data - Splunk Documentation

Therefore, the correct order of the indexing process is: Input phase → Parsing phase → Indexing phase.

Splunk REST API is a valid method to create a Splunk user. The Splunk REST API allows administrators to create, edit, and delete users programmatically using HTTP requests. The other options are not valid methods to create a Splunk user. Creating a support ticket does not create a user, but requests assistance from Splunk support. Creating a user on the host operating system does not create a Splunk user, but a system user. Adding the username to users.conf does not create a user, but modifies the configuration file that stores user information. References = Configure users with the CLI, Configure users and roles

https://docs.splunk.com/Documentation/Splunk/8.1.1/Updating/Definedeploymentclasses#Ways_to_define_server_classes "When you use forwarder management to create a new server class, it saves the server class definition in a copy of serverclass.conf under $SPLUNK_HOME/etc/system/local. If, instead of using forwarder management, you decide to directly edit serverclass.conf, it is recommended that you create the serverclass.conf file in that same directory, $SPLUNK_HOME/etc/system/local."

Users log on to the search head and run reports: – The search head dispatches searches to the peers – Peers run searches in parallel and return their portion of results – The search head consolidates the individual results and prepares reports

https://docs.splunk.com/Documentation/Splunk/8.1.1/Data/Monitornetworkports

This is explained in the Splunk documentation1, which states:

If an indexer goes down during a search, the search head notifies you that the results might be incomplete. The search head does not attempt to re-run the search on another indexer.

Search-time field extractions are the process of extracting fields from events after they are indexed. Search-time field extractions are specified on the search head, which is the Splunk component that handles searching and reporting. Search-time field extractions are configured in props.conf and transforms.conf files, which are located in the etc/system/local directory on the search head. Therefore, option D is the correct answer. References: Splunk Enterprise Certified Admin | Splunk, [About fields - Splunk Documentation]

The correct answer is C. Distributed search is the feature that allows search heads in a company’s European offices to search data in their New York offices. Distributed search also enables restricting access to certain indexers by using the splunk_server field or the server.conf file1.

Distributed search is a way to scale your Splunk deployment by separating the search management and presentation layer from the indexing and search retrieval layer. With distributed search, a Splunk instance called a search head sends search requests to a group of indexers, or search peers, which perform the actual searches on their indexes. The search head then merges the results back to the user2.

Distributed search has several use cases, such as horizontal scaling, access control, and managing geo-dispersed data. For example, users in different offices can search data across the enterprise or only in their local area, depending on their needs and permissions2.

The other options are incorrect because:

A. Indexer clustering is a feature that replicates data across a group of indexers to ensure data availability and recovery. Indexer clustering does not directly affect distributed search, although search heads can be configured to search across an indexer cluster3.

B. LDAP control is a feature that allows Splunk to integrate with an external LDAP directory service for user authentication and role mapping. LDAP control does not affect distributed search, although it can be used to manage user access to data and searches.

D. Search head clustering is a feature that distributes the search workload across a group of search heads that share resources, configurations, and jobs. Search head clustering does not affect distributed search, although the search heads in a cluster can search across the same set of indexers.