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The following clarification steps should be taken if apps are not appearing on a deployment client:

Check serverclass.conf of the deployment server. This file defines the server classes and the apps and configurations that they should receive from the deployment server. Make sure that the deployment client belongs to the correct server class and that the server class has the desired apps and configurations.

Check deploymentclient.conf of the deployment client. This file specifies the deployment server that the deployment client contacts and the client name that it uses. Make sure that the deployment client is pointing to the correct deployment server and that the client name matches the server class criteria.

Search for relevant events in splunkd.log of the deployment server. This file contains information about the deployment server activities, such as sending apps and configurations to the deployment clients, detecting client check-ins, and logging any errors or warnings. Look for any events that indicate a problem with the deployment server or the deployment client.

Checking the content of SPLUNK_HOME/etc/apps of the deployment server is not a necessary clarification step, as this directory does not contain the apps and configurations that are distributed to the deployment clients. The apps and configurations for the deployment server are stored in SPLUNK_HOME/etc/deployment-apps. For more information, see Configure deployment server and clients in the Splunk documentation.

 When planning a search head cluster, the following statement is true: All indexers must belong to the underlying indexer cluster (no standalone indexers). A search head cluster is a group of search heads that share configurations, apps, and search jobs. A search head cluster requires an indexer cluster as its data source, meaning that all indexers that provide data to the search head cluster must be members of the same indexer cluster. Standalone indexers, or indexers that are not part of an indexer cluster, cannot be used as data sources for a search head cluster. All search heads do not have to use the same operating system, as long as they are compatible with the Splunk version and the indexer cluster. All search heads do not have to be members of the cluster, as standalone search heads can also search the indexer cluster, but they will not have the benefits of configuration replication and load balancing. The search head captain does not have to be assigned to the largest search head in the cluster, as the captain is dynamically elected from among the cluster members based on various criteria, such as CPU load, network latency, and search load.

The master node distributes configuration bundles to peer nodes in the slave-apps directory under $SPLUNK_HOME/etc. The configuration bundle method is the only supported method for managing common configurations and app deployment across the set of peers. It ensures that all peers use the same versions of these files1. Bundles typically contain a subset of files (configuration files and assets) from $SPLUNK_HOME/etc/system, $SPLUNK_HOME/etc/apps, and $SPLUNK_HOME/etc/users2. The process of distributing knowledge bundles means that peers by default receive nearly the entire contents of the search head’s apps3.

According to the Splunk Search Job Inspector documentation, the search.log file for a completed search job can be accessed through Splunk Web by navigating to the job’s detailed inspection view.

To access it:

Open the completed search in Splunk Web.

Click the Job menu (top right of the search interface).

Select Inspect Job.

In the Job Inspector window, click the search.log link.

This log provides in-depth diagnostic details about how the search was parsed, distributed, and executed across the search head and indexers. It contains valuable performance metrics, command execution order, event sampling information, and any error or warning messages encountered during search processing.

The search.log file is generated for every search job—scheduled, ad-hoc, or background—and is stored in the job’s dispatch directory ($SPLUNK_HOME/var/run/splunk/dispatch//).

Other listed options are incorrect:

Option A queries the _internal index, which does not store per-search logs.

Option B is used to view search configurations, not logs.

Option C is not a valid Splunk Web navigation option.

Thus, the only correct and Splunk-documented method is via Job → Inspect Job → search.log.

References (Splunk Enterprise Documentation):

• Search Job Inspector Overview and Usage

• Analyzing Search Performance Using search.log

• Search Job Management and Dispatch Directory Structure

• Splunk Enterprise Admin Manual – Troubleshooting Searches

The following statements about integrating with third-party systems are true: You can use Splunk alerts to provision actions on a third-party system, and you can forward data from Splunk forwarder to a third-party system without indexing it first. Splunk alerts are triggered events that can execute custom actions, such as sending an email, running a script, or calling a webhook. Splunk alerts can be used to integrate with third-party systems, such as ticketing systems, notification services, or automation platforms. For example, you can use Splunk alerts to create a ticket in ServiceNow, send a message to Slack, or trigger a workflow in Ansible. Splunk forwarders are Splunk instances that collect and forward data to other Splunk instances, such as indexers or heavy forwarders. Splunk forwarders can also forward data to third-party systems, such as Hadoop, Kafka, or AWS Kinesis, without indexing it first. This can be useful for sending data to other data processing or storage systems, or for integrating with other analytics or monitoring tools. A Hadoop application cannot search data in Splunk, because Splunk does not provide a native interface for Hadoop applications to access Splunk data. Splunk can search data in the Hadoop File System (HDFS), but only by using the Hadoop Connect app, which is a Splunk app that enables Splunk to index and search data stored in HDFS

Migration from single-site to multisite index replication only affects new data, not existing data. Multisite policies apply to new data only, meaning that data that is ingested after the migration will follow the multisite replication and search factors. Existing data, or data that was ingested before the migration, will retain the single-site policies, unless they are manually converted to multisite buckets. Single-site buckets do not instantly receive the multisite policies, nor do they automatically convert to multisite buckets. Multisite total values can exceed any single-site factors, as long as they do not exceed the number of peer nodes in the cluster. A master node is not required at each site, only one master node is needed for the entire cluster

The following logs are included in the _introspection index, which contains data that the Splunk Enterprise deployment logs for platform instrumentation:

disk_objects.log. This log contains information about the disk objects that Splunk creates and manages, such as buckets, indexes, and files. This log can help monitor the disk space usage and the bucket lifecycle.

resource_usage.log. This log contains information about the resource usage of Splunk processes, such as CPU, memory, disk, and network. This log can help monitor the Splunk performance and identify any resource bottlenecks. The following logs are not included in the _introspection index, but rather in the _internal index, which contains data that Splunk generates for internal logging:

audit.log. This log contains information about the audit events that Splunk records, such as user actions, configuration changes, and search activity. This log can help audit the Splunk operations and security.

metrics.log. This log contains information about the performance metrics that Splunk collects, such as data throughput, data latency, search concurrency, and search duration. This log can help measure the Splunk performance and efficiency. For more information, see About Splunk Enterprise logging and [About the _introspection index] in the Splunk documentation.

 In a four site indexer cluster, the configuration that stores two searchable copies at the origin site, one searchable copy at site2, and a total of four searchable copies is site_search_factor = origin:2, site2:1, total:4. This configuration tells the cluster to maintain two copies of searchable data at the site where the data originates, one copy of searchable data at site2, and a total of four copies of searchable data across all sites. The site_search_factor determines how many copies of searchable data are maintained by the cluster for each site. The site_replication_factor determines how many copies of raw data are maintained by the cluster for each site. For more information, see Configure multisite indexer clusters with server.conf in the Splunk documentation.

 The following statements are true regarding Splunk Enterprise performance:

Adding search peers increases the search throughput as search load increases. This is because adding more search peers distributes the search workload across more indexers, which reduces the load on each indexer and improves the search speed and concurrency.

Adding search heads provides additional CPU cores to run more concurrent searches. This is because adding more search heads increases the number of search processes that can run in parallel, which improves the search performance and scalability. The following statements are false regarding Splunk Enterprise performance:

Adding search peers does not increase the maximum size of search results. The maximum size of search results is determined by the maxresultrows setting in the limits.conf file, which is independent of the number of search peers.

Adding RAM to an existing search head does not provide additional search capacity. The search capacity of a search head is determined by the number of CPU cores, not the amount of RAM. Adding RAM to a search head may improve the search performance, but not the search capacity. For more information, see Splunk Enterprise performance in the Splunk documentation.

The system local directory has the highest precedence among the following directories that contain Splunk configuration files of the same name within different apps. Splunk configuration files are stored in various directories under the SPLUNK_HOME/etc directory. The precedence of these directories determines which configuration file settings take effect when there are conflicts or overlaps. The system local directory, which is located at SPLUNK_HOME/etc/system/local, has the highest precedence among all directories, because it contains the system-level configurations that are specific to the instance. The system default directory, which is located at SPLUNK_HOME/etc/system/default, has the lowest precedence among all directories, because it contains the system-level configurations that are provided by Splunk and should not be modified. The app local directories, which are located at SPLUNK_HOME/etc/apps/APP_NAME/local, have a higher precedence than the app default directories, which are located at SPLUNK_HOME/etc/apps/APP_NAME/default, because the local directories contain the app-level configurations that are specific to the instance, while the default directories contain the app-level configurations that are provided by the app and should not be modified. The app local and default directories have different precedences depending on the ASCII order of the app names, with the app names that come later in the ASCII order having higher precedences.