This is the index that records changes to .conf files as of Splunk 9.0. According to the Splunk

documentation1, the _configtracker index tracks the changes made to the configuration files on the

Splunk platform, such as the files in the etc directory. The _configtracker index can help monitor and

troubleshoot the configuration changes, and identify the source and time of the changes1. The other

options are not indexes that record changes to .conf files. Option B, _introspection, is an index that

records the performance metrics of the Splunk platform, such as CPU, memory, disk, and network

usage2. Option C, _internal, is an index that records the internal logs and events of the Splunk

platform, such as splunkd, metrics, and audit logs3. Option D, _audit, is an index that records the

audit events of the Splunk platform, such as user authentication, authorization, and activity4.

Therefore, option A is the correct answer, and options B, C, and D are incorrect.

1: About the _configtracker index 2: About the _introspection index 3: About the _internal index 4:

About the _audit index

According to the Splunk documentation1, the Search Job Inspector is a tool that you can use to

troubleshoot search performance and understand the behavior of knowledge objects, such as event

types, tags, lookups, and so on, within the search. You can inspect search jobs that are currently

running or that have finished recently. The Search Job Inspector can help you investigate error

messages that appear underneath the search bar in Splunk Web, as it can show you the details of the

search job, such as the search string, the search mode, the search timeline, the search log, the search

profile, and the search properties. You can use this information to identify the cause of the error and

fix it2. The other options are false because:

Dashboard panels showing “Waiting for queued job to start” on page load is not a problem that can

be investigated using the Search Job Inspector, as it indicates that the search job has not started yet.

This could be due to the search scheduler being busy or the search priority being low. You can use the

Jobs page or the Monitoring Console to monitor the status of the search jobs and adjust the priority

or concurrency settings if needed3.

Different users seeing different extracted fields from the same search is not a problem that can be

investigated using the Search Job Inspector, as it is related to the user permissions and the

knowledge object sharing settings. You can use the Access Controls page or the Knowledge Manager

to manage the user roles and the knowledge object visibility4.

Events not being sorted in reverse chronological order is not a problem that can be investigated using

the Search Job Inspector, as it is related to the search syntax and the sort command. You can use the

Search Manual or the Search Reference to learn how to use the sort command and its options to sort

the events by any field or criteria.

Intermediate forwarders are forwarders that receive data from other forwarders and then send that

data to indexers. They can be useful in some scenarios, such as when network bandwidth or security

constraints prevent direct forwarding to indexers, or when data needs to be routed, cloned, or

modified in transit. However, intermediate forwarders also introduce additional complexity and

overhead to the data pipeline, which can affect the performance and reliability of data ingestion.

Therefore, intermediate forwarders should be avoided when possible, and used only when there is a

clear benefit or requirement for them. Some of the drawbacks of intermediate forwarders are:

They increase the number of hops and connections in the data flow, which can introduce latency and

increase the risk of data loss or corruption.

They consume more resources on the hosts where they run, such as CPU, memory, disk, and network

bandwidth, which can affect the performance of other applications or processes on those hosts.

They require additional configuration and maintenance, such as setting up inputs, outputs, load

balancing, security, monitoring, and troubleshooting.

They can create data duplication or inconsistency if they are not configured properly, such as when

using cloning or routing rules.

Some of the

that support this answer are:

Configure an intermediate forwarder, which states: “Intermediate forwarding is where a forwarder

receives data from one or more forwarders and then sends that data on to another indexer. This kind

of setup is useful when, for example, you have many hosts in different geographical regions and you

want to send data from those forwarders to a central host in that region before forwarding the data

to an indexer. All forwarder types can act as an intermediate forwarder. However, this adds

complexity to your deployment and can affect performance, so use it only when necessary.”

Intermediate data routing using universal and heavy forwarders, which states: “This document

outlines a variety of Splunk options for routing data that address both technical and business

requirements. Overall benefits Using splunkd intermediate data routing offers the following overall

benefits: … The routing strategies described in this document enable flexibility for reliably processing

data at scale. Intermediate routing enables better security in event-level data as well as in transit.

The following is a list of use cases and enablers for splunkd intermediate data routing: … Limitations

splunkd intermediate data routing has the following limitations: … Increased complexity and

resource consumption. splunkd intermediate data routing adds complexity to the data pipeline and

consumes resources on the hosts where it runs. This can affect the performance and reliability of

data ingestion and other applications or processes on those hosts. Therefore, intermediate routing

should be avoided when possible, and used only when there is a clear benefit or requirement for it.”

Use forwarders to get data into Splunk Enterprise, which states: “The forwarders take the Apache

data and send it to your Splunk Enterprise deployment for indexing, which consolidates, stores, and

makes the data available for searching. Because of their reduced resource footprint, forwarders have

a minimal performance impact on the Apache servers. … Note: You can also configure a forwarder to

send data to another forwarder, which then sends the data to the indexer. This is called intermediate

forwarding. However, this adds complexity to your deployment and can affect performance, so use it

only when necessary.”

A best practice to maximize indexing performance is to minimize configuration generality.

Configuration generality refers to the use of generic or default settings for data inputs, such as source

type, host, index, and timestamp. Minimizing configuration generality means using specific and

accurate settings for each data input, which can reduce the processing overhead and improve the

indexing throughput. Using automatic source typing, using the Splunk default settings, and not using

pre-trained source types are examples of configuration generality, which can negatively affect the

indexing performance

In the context of splunkd.log events written to the _internal index, the field that identifies the

specific log channel is the "channel" field. This information is confirmed by the Splunk Common

Information Model (CIM) documentation, where "channel" is listed as a field name associated with

Splunk Audit Logs  .

Decreasing the data model acceleration range will reduce the disk size requirements for a cluster of

indexers running Splunk Enterprise Security. Data model acceleration creates tsidx files that consume

disk space on the indexers. Reducing the acceleration range will limit the amount of data that is

accelerated and thus save disk space. Setting the cluster search factor or replication factor to N-1 will

not reduce the disk size requirements, but rather increase the risk of data loss. Increasing the

number of buckets per index will also increase the disk size requirements, as each bucket has a

minimum size. For more information, see Data model acceleration and Bucket size in the Splunk

documentation.

The splunk_instrumentation.log file is the least helpful in troubleshooting a crash, because it

contains information about the Splunk Instrumentation feature, which collects and sends usage data

to Splunk Inc. for product improvement purposes. This file does not contain any information about

the Splunk processes, errors, or crashes. The other options are more helpful in troubleshooting a

crash, because they contain relevant information about the Splunk daemon, the standard error

output, and the crash report12

1:

https://docs.splunk.com/Documentation/Splunk/9.1.2/Troubleshooting/WhatSplunklogsaboutitself

#splunk_instrumentation.log 2:

https://docs.splunk.com/Documentation/Splunk/9.1.2/Troubleshooting/WhatSplunklogsaboutitself

#splunkd_stderr.log

As a best practice, the internal licensing logs should be stored on the license server. The license

server is a Splunk instance that manages the distribution and enforcement of licenses in a Splunk

deployment. The license server generates internal licensing logs that contain information about the

license usage, violations, warnings, and pools. The internal licensing logs should be stored on the

license server itself, because they are relevant to the license server’s role and function. Storing the

internal licensing logs on the license server also simplifies the license monitoring and

troubleshooting process. The internal licensing logs should not be stored on the indexing layer, the

deployment layer, or the search head layer, because they are not related to the roles and functions of

these layers. Storing the internal licensing logs on these layers would also increase the network

traffic and disk space consumption

The deployer distributes apps and non-search related and manual configuration file changes to the

search head cluster members. The deployer does not bootstrap a clean Splunk install for a search

head cluster, as this is done by the captain. The deployer also does not distribute runtime knowledge

object changes made by users across the search head cluster, as this is done by the replication factor.

For more information, see Use the deployer to distribute apps and configuration updates in the

Splunk documentation.

The correct answer is A. Change frozenTimePeriodInSecs to a larger value. This is a possible solution

to reduce the need to thaw buckets, as it increases the time period before a bucket is frozen and

removed from the index1. The frozenTimePeriodInSecs attribute specifies the maximum age, in

seconds, of the data that the index can contain1. By setting it to a larger value, the Splunk

administrator can keep the data in the index for a longer time, and avoid having to thaw the buckets

frequently. The other options are not effective solutions to reduce the need to thaw buckets. Option

B, changing maxTotalDataSizeMB to a smaller value, would actually increase the need to thaw

buckets, as it decreases the maximum size, in megabytes, of an index2. This means that the index

would reach its size limit faster, and more buckets would be frozen and removed. Option C, changing

maxHotSpanSecs to a larger value, would not affect the need to thaw buckets, as it only changes the

maximum lifetime, in seconds, of a hot bucket3. This means that the hot bucket would stay hot for a

longer time, but it would not prevent the bucket from being frozen eventually. Option D, changing

coldToFrozenDir to a different location, would not reduce the need to thaw buckets, as it only

changes the destination directory for the frozen buckets4. This means that the buckets would still be

frozen and removed from the index, but they would be stored in a different location. Therefore,

option A is the correct answer, and options B, C, and D are incorrect.

1: Set a retirement and archiving policy 2: Configure index size 3: Bucket rotation and retention 4:

Archive indexed data