Splunk SPLK-2002 Practice Test - Questions Answers, Page 9

A Technical Add-On (TA) is a Splunk app that contains configurations for data collection, parsing, and enrichment. It can also enable event data for a data model, which is useful for creating dashboards and reports. Therefore, before installing a TA, it is important to identify the number of scheduled or real-time searches that will use the data model, and to validate if the TA enables event data for a data model. The number of forwarders that the TA can support is not relevant, as the TA is installed on the indexer or search head, not on the forwarder.The installation location of the TA depends on the type of data and the use case, so it is not a fixed requirement

The replication factor and the search factor are two important settings for a Splunk indexer cluster. The replication factor determines how many copies of each bucket are maintained across the set of peer nodes. The search factor determines how many searchable copies of each bucket are maintained.The default values for both settings are 3, which means that each bucket has three copies, and at least one of them is searchable

The following may explain the problem of why a colleague cannot see the src_ip field in their search results: The field was extracted as a private knowledge object, and the colleague did not explicitly use the field in the search and the search was set to Fast Mode. A knowledge object is a Splunk entity that applies some knowledge or intelligence to the data, such as a field extraction, a lookup, or a macro. A knowledge object can have different permissions, such as private, app, or global. A private knowledge object is only visible to the user who created it, and it cannot be shared with other users. A field extraction is a type of knowledge object that extracts fields from the raw data at index time or search time. If a field extraction is created as a private knowledge object, then only the user who created it can see the extracted field in their search results. A search mode is a setting that determines how Splunk processes and displays the search results, such as Fast, Smart, or Verbose. Fast mode is the fastest and most efficient search mode, but it also limits the number of fields and events that are displayed. Fast mode only shows the default fields, such as _time, host, source, sourcetype, and _raw, and any fields that are explicitly used in the search. If a field is not used in the search and it is not a default field, then it will not be shown in Fast mode. The events are tagged as communicate, but are missing the network tag, and the Typing Queue, which does regular expression replacements, is blocked, are not valid explanations for the problem. Tags are labels that can be applied to fields or field values to make them easier to search. Tags do not affect the visibility of fields, unless they are used as filters in the search. The Typing Queue is a component of the Splunk data pipeline that performs regular expression replacements on the data, such as replacing IP addresses with host names.The Typing Queue does not affect the field extraction process, unless it is configured to do so

The Search Job Inspector can be used to expand the following sections: Search job properties and Optimization suggestions. The Search Job Inspector is a tool that provides detailed information about a search job, such as the search parameters, the search statistics, the search timeline, and the search log. The Search Job Inspector can be accessed by clicking the Job menu in the Search bar and selecting Inspect Job. The Search Job Inspector has several sections that can be expanded or collapsed by clicking the arrow icon next to the section name. The Search job properties section shows the basic information about the search job, such as the SID, the status, the duration, the disk usage, and the scan count. The Optimization suggestions section shows the suggestions for improving the search performance, such as using transforming commands, filtering events, or reducing fields. The Execution costs and Saved search history sections are not part of the Search Job Inspector, and they cannot be expanded. The Execution costs section is part of the Search Dashboard, which shows the relative costs of each search component, such as commands, lookups, or subsearches.The Saved search history section is part of the Saved Searches page, which shows the history of the saved searches that have been run by the user or by a schedule

Splunk internal logs are stored in the SPLUNK_HOME/var/log/splunk directory by default. The default log size for Splunk internal logs is 25 MB, which means that when a log file reaches 25 MB, Splunk rolls it to a backup file and creates a new log file.The default number of backup files is 5, which means that Splunk keeps up to 5 backup files for each log file

A Splunk job is a search process that is kicked off via a report, an alert, or a user action. A Splunk job is a child OS process manifested from the splunkd process, which is the main Splunk daemon. A Splunk job is subjected to some usage quota, such as memory, CPU, and disk space, which can be configured in the limits.conf file. A Splunk job is not a user-defined Splunk capability, as it is a core feature of the Splunk platform.

Splunk internal indexes are the indexes that store Splunk's own data, such as internal logs, metrics, audit events, and configuration snapshots. By default, Splunk internal indexes are stored in the SPLUNK_HOME/var/lib/splunk directory, along with other user-defined indexes. The SPLUNK_HOME/bin directory contains the Splunk executable files and scripts. The SPLUNK_HOME/var/run directory contains the Splunk process ID files and lock files. The SPLUNK_HOME/etc/system/default directory contains the default Splunk configuration files.

Syslog is a standard protocol for sending log messages from various devices and applications to a central server. Syslog can use either UDP or TCP as the transport layer protocol. UDP is faster but less reliable, as it does not guarantee delivery or order of the messages. TCP is slower but more reliable, as it ensures delivery and order of the messages. Therefore, to improve the reliability of syslog delivery to Splunk, it is recommended to use TCP syslog.

Another option to improve the reliability of syslog delivery to Splunk is to use one or more syslog servers to persist data with a Universal Forwarder to send the data to Splunk indexers. This way, the syslog servers can act as a buffer and store the data in case of network or Splunk outages. The Universal Forwarder can then forward the data to Splunk indexers when they are available.

Using a network load balancer to direct syslog traffic to active backend syslog listeners is not a reliable option, as it does not address the possibility of data loss or duplication due to network failures or Splunk outages. Configuring UDP inputs on each Splunk indexer to receive data directly is also not a reliable option, as it exposes the indexers to the network and increases the risk of data loss or duplication due to UDP limitations.

The logical first step when starting a deployment plan is to collect the initial requirements for the deployment from all stakeholders. This includes identifying the business objectives, the data sources, the use cases, the security and compliance needs, the scalability and availability expectations, and the budget and timeline constraints. Collecting the initial requirements helps to define the scope and the goals of the deployment, and to align the expectations of all the parties involved.

Inventorying the currently deployed logging infrastructure, determining what apps and use cases will be implemented, and gathering statistics on the expected adoption of Splunk for sizing are all important steps in the deployment planning process, but they are not the logical first step. These steps can be done after collecting the initial requirements, as they depend on the information gathered from the stakeholders.