SPLK-2002 Questions and Answers

The Splunk Enterprise Security and Encryption documentation specifies that the primary mechanism for securing data in motion within a Splunk environment is to enable TLS/SSL encryption between forwarders and indexers. This ensures that log data transmitted from Universal Forwarders or Heavy Forwarders to Indexers is fully encrypted and protected from interception or tampering.

The correct configuration involves setting up signed SSL certificates on both forwarders and indexers:

On the forwarder, TLS settings are defined in outputs.conf, specifying parameters like sslCertPath, sslPassword, and sslRootCAPath.

On the indexer, TLS is enabled in inputs.conf and server.conf using the same shared CA for validation.

Splunk’s documentation explicitly states that this configuration protects data-in-transit between the collection (forwarder) and indexing (storage) tiers — which is the critical link where sensitive log data is most vulnerable.

Other communication channels (e.g., deployment server to clients or browser to Splunk Web) can also use encryption but do not secure the ingestion pipeline that handles the indexed data stream. Therefore, TLS should be implemented between Splunk forwarders and indexers.

References (Splunk Enterprise Documentation):

• Securing Data in Transit with SSL/TLS

• Configure Forwarder-to-Indexer Encryption Using SSL Certificates

• Server and Forwarder Authentication Setup Guide

• Splunk Enterprise Admin Manual – Security and Encryption Best Practices

inputs.conf is a configuration file that contains settings for various types of data inputs, such as files, directories, network ports, scripts, and so on1.

initCrcLength is a setting that specifies the number of characters that the input uses to calculate the CRC (cyclic redundancy check) of a file1. The CRC is a value that uniquely identifies a file based on its content2.

crcSalt is another setting that adds a string to the CRC calculation to force the input to consume files that have matching CRCs1. This can be useful when files have identical headers or when files are renamed or rolled over2.

When troubleshooting a situation where some files within a directory are not being indexed, the ignored files are discovered to have long headers, the first thing that should be added to inputs.conf is to increase the value of initCrcLength. This is because by default, the input only performs CRC checks against the first 256 bytes of a file, which means that files with long headers may have matching CRCs and be skipped by the input2. By increasing the value of initCrcLength, the input can use more characters from the file to calculate the CRC, which can reduce the chances of CRC collisions and ensure that different files are indexed3.

Option C is the correct answer because it reflects the best practice for troubleshooting this situation. Option A is incorrect because decreasing the value of initCrcLength would make the CRC calculation less reliable and more prone to collisions. Option B is incorrect because adding a crcSalt with a static string would not help differentiate files with long headers, as they would still have matching CRCs. Option D is incorrect because adding a crcSalt with the attribute would add the full directory path to the CRC calculation, which would not help if the files are in the same directory2.

The Splunk Enterprise Capacity Planning Manual states that running Splunk in a virtualized environment typically results in a performance reduction of approximately 20% to 45% compared to equivalent deployments on physical hardware.

This degradation is primarily due to the virtualization overhead inherent in hypervisor environments (such as VMware, Hyper-V, or KVM), which can affect:

Disk I/O throughput and latency — the most critical factor for indexers.

CPU scheduling efficiency, particularly for multi-threaded indexing processes.

Network latency between clustered components.

Splunk’s documentation strongly emphasizes that while virtualized environments offer operational flexibility, they cannot match bare-metal performance, especially under heavy indexing loads.

To mitigate performance loss, Splunk recommends:

Reserving dedicated CPU and I/O resources for Splunk VMs.

Avoiding over-commitment of hardware resources.

Using high-performance SSD storage or paravirtualized disk controllers.

These optimizations can narrow the performance gap, but a 20–45% reduction remains a realistic expectation under typical conditions.

References (Splunk Enterprise Documentation):

• Splunk Enterprise Capacity Planning Manual – Virtualization Performance Considerations

• Splunk on Virtual Infrastructure – Best Practices and Performance Tuning

• Indexer and Search Head Hardware Recommendations

• Performance Testing Guidelines for Splunk Deployments

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.

The average run time of all searches increases as the number of CPU cores on the indexers decreases. The CPU cores are the processing units that execute the instructions and calculations for the data. The number of CPU cores on the indexers affects the search performance, because the indexers are responsible for retrieving and filtering the data from the indexes. The more CPU cores the indexers have, the faster they can process the data and return the results. The less CPU cores the indexers have, the slower they can process the data and return the results. Therefore, the average run time of all searches is inversely proportional to the number of CPU cores on the indexers. The average run time of all searches is not independent of the number of CPU cores on the indexers, because the CPU cores are an important factor for the search performance. The average run time of all searches does not decrease as the number of CPU cores on the indexers decreases, because this would imply that the search performance improves with less CPU cores, which is not true. The average run time of all searches does not increase as the number of CPU cores on the indexers increases, because this would imply that the search performance worsens with more CPU cores, which is not true

According to the Splunk Search Head Clustering Troubleshooting Guide, when a Search Head Cluster (SHC) member is reverted from a backup or experiences configuration drift (e.g., an outdated Raft state), it can fail to rejoin the cluster due to inconsistent Raft metadata. The Raft database stores the SHC’s internal consensus and replication state, including knowledge object synchronization, captain election history, and peer membership information.

If this Raft metadata becomes corrupted or outdated (as in the scenario where a node is restored from backup), the recommended and Splunk-supported remediation is to clean the Raft metadata using:

splunk clean raft

This command resets the node’s local Raft state so it can re-synchronize with the current SHC captain and rejoin the cluster cleanly.

The steps generally are:

Stop the affected SHC member.

Run splunk clean raft on that node.

Restart Splunk.

Verify that it successfully rejoins the SHC.

Deleting configuration stanzas or forcing re-addition (Options B and C) can lead to further inconsistency or data loss. Reviewing logs (Option A) helps diagnose issues but does not resolve Raft corruption.

References (Splunk Enterprise Documentation):

• Troubleshooting Raft Metadata Corruption in Search Head Clusters

• splunk clean raft Command Reference

• Search Head Clustering: Recovering from Backup and Membership Failures

• Splunk Enterprise Admin Manual – Raft Consensus and SHC Maintenance

The Monitoring Console (MC) is the Splunk Enterprise monitoring tool that lets you view detailed topology and performance information about your Splunk Enterprise deployment1. The MC can be installed on any Splunk Enterprise instance that can access the data from all the instances in the deployment2. However, following the Splunk recommendations, the MC should be installed on the search head cluster deployer, which is a dedicated instance that manages the configuration bundle for the search head cluster members3. This way, the MC can monitor the search head cluster as well as the indexer cluster and the forwarders, without affecting the performance or availability of the other instances4. The other options are not recommended because they either introduce additional load on the existing instances (such as A and D) or do not have access to the data from the search head cluster (such as B).

1: About the Monitoring Console - Splunk Documentation 2: Add Splunk Enterprise instances to the Monitoring Console 3: Configure the deployer - Splunk Documentation 4: [Monitoring Console setup and use - Splunk Documentation]

The client filters available in serverclass.conf are DNS name, IP address, and platform (machine type). These filters allow the administrator to specify which forwarders belong to a server class and receive the apps and configurations from the deployment server. The Splunk server role is not a valid client filter in serverclass.conf, as it is not a property of the forwarder. For more information, see [Use forwarder management filters] in the Splunk documentation.

When using the props.conf LINE_BREAKER attribute to delimit multi-line events, the SHOULD_LINEMERGE attribute should be set to false. This tells Splunk not to merge events that have been broken by the LINE_BREAKER. Setting the SHOULD_LINEMERGE attribute to true, auto, or none will cause Splunk to ignore the LINE_BREAKER and merge events based on other criteria. For more information, see Configure event line breaking in the Splunk documentation.

Data retention is optional in the data source assessment because it is not directly related to the ingestion process. Data retention is determined by the index configuration and the storage capacity of the Splunk platform. Data format, data location, and data volume are all essential information for planning how to collect, parse, and index the data source.

 The splunk add cluster-master command is used to configure the same search head to join another indexer cluster. A search head can search multiple indexer clusters by adding multiple cluster-master entries in its server.conf file. The splunk add cluster-master command can be used to add a new cluster-master entry to the server.conf file, by specifying the host name and port number of the master node of the other indexer cluster. The splunk add cluster-config command is used to configure the search head to join the first indexer cluster, not the second one. The splunk edit cluster-config command is used to edit the existing cluster configuration of the search head, not to add a new one. The splunk edit cluster-master command does not exist, and it is not a valid command.

The Splunk server name of the member can typically be determined by the serverName attribute in the server.conf file, which is not explicitly shown in the provided snippet. However, based on the provided configuration snippet, we can infer that this search head cluster member is configured to communicate with a cluster master (master_uri) located at node1 and a management node (mgmt_uri) located at node3. The serverName is not the same as the master_uri or mgmt_uri; these URIs indicate the location of the master and management nodes that this member interacts with.

Since the serverName is not provided in the snippet, one would typically look for a setting under the [general] stanza in server.conf. However, given the options and the common naming conventions in a Splunk environment, node3 would be a reasonable guess for the server name of this member, since it is indicated as the management URI within the [shclustering] stanza, which suggests it might be the name or address of the server in question.

For accurate identification, you would need to access the full server.conf file or the Splunk Web on the search head cluster member and look under Settings > Server settings > General settings to find the actual serverName. Reference for these details would be found in the Splunk documentation regarding the configuration files, particularly server.conf.

The correct tasks that the cluster manager performs in an indexer cluster are A. Generates and maintains the list of primary searchable buckets, B. If Indexer Discovery is enabled, provides the list of available peer nodes to forwarders, and D. Distributes app bundles to peer nodes. According to the Splunk documentation1, the cluster manager is responsible for these tasks, as well as managing the replication and search factors, coordinating the replication and search activities, and providing a web interface for monitoring and managing the cluster. Option C, ensuring all peer nodes are always using the same version of Splunk, is not a task of the cluster manager, but a requirement for the cluster to function properly2. Therefore, option C is incorrect, and options A, B, and D are correct.

1: About the cluster manager 2: Requirements and compatibility for indexer clusters

Splunk configuration files are files that contain settings that control various aspects of Splunk behavior, such as data inputs, outputs, indexing, searching, clustering, and so on1. Troubleshooting Splunk configuration files involves identifying and resolving issues that affect the functionality or performance of Splunk due to incorrect or conflicting configuration settings. Some of the tools and methods that can help with troubleshooting Splunk configuration files are:

search.log: This is a file that contains detailed information about the execution of a search, such as the search pipeline, the search commands, the search results, the search errors, and the search performance2. This file can help troubleshoot issues related to search configuration, such as props.conf, transforms.conf, macros.conf, and so on3.

btool output: This is a command-line tool that displays the effective configuration settings for a given Splunk component, such as inputs, outputs, indexes, props, and so on4. This tool can help troubleshoot issues related to configuration precedence, inheritance, and merging, as well as identify the source of a configuration setting5.

diagnostic logs: These are files that contain information about the Splunk system, such as the Splunk version, the operating system, the hardware, the license, the indexes, the apps, the users, the roles, the permissions, the configuration files, the log files, and the metrics6. These files can help troubleshoot issues related to Splunk installation, deployment, performance, and health7.

Option A is the correct answer because crash logs are the least helpful in troubleshooting Splunk configuration files. Crash logs are files that contain information about the Splunk process when it crashes, such as the stack trace, the memory dump, and the environment variables8. These files can help troubleshoot issues related to Splunk stability, reliability, and security, but not necessarily related to Splunk configuration9.

This is where in the Job Inspector details can be found to help determine where performance is affected, as it shows the time and resources spent by each component of the search, such as commands, subsearches, lookups, and post-processing1. The Execution Costs > Components section can help identify the most expensive or inefficient parts of the search, and suggest ways to optimize or improve the search performance1. The other options are not as useful as the Execution Costs > Components section for finding performance issues. Option A, Search Job Properties > runDuration, shows the total time, in seconds, that the search took to run2. This can indicate the overall performance of the search, but it does not provide any details on the specific components or factors that affected the performance. Option B, Search Job Properties > runtime, shows the time, in seconds, that the search took to run on the search head2. This can indicate the performance of the search head, but it does not account for the time spent on the indexers or the network. Option C, Job Details Dashboard > Total Events Matched, shows the number of events that matched the search criteria3. This can indicate the size and scope of the search, but it does not provide any information on the performance or efficiency of the search. Therefore, option D is the correct answer, and options A, B, and C are incorrect.

1: Execution Costs > Components 2: Search Job Properties 3: Job Details Dashboard

Two indexers clustered is the recommended deployment for a customer who plans to ingest 600 GB of data per day into Splunk, has six concurrent users, and wants high data availability and high search performance. This deployment will provide enough indexing capacity and search concurrency for the customer’s needs, while also ensuring data replication and searchability across the cluster. The customer can also save on the hardware cost by using only two indexers. Two indexers not in a cluster will not provide high data availability, as there is no data replication or failover. Three indexers not in a cluster will provide more indexing capacity and search concurrency, but also more hardware cost and no data availability. The customer’s data retention period, number of long searches, or volume of saved/scheduled searches are not relevant for determining the number of indexers. For more information, see [Reference hardware] and [About indexer clusters and index replication] in the Splunk documentation.

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

According to the Splunk documentation1, the Splunk Deployer deploys app content to the etc/slave-apps/ directory on the search head cluster members by default. This directory contains the apps that the deployer distributes to the members as part of the configuration bundle. The other options are false because:

The etc/apps/ directory contains the apps that are installed locally on each member, not the apps that are distributed by the deployer2.

The etc/shcluster/ directory contains the configuration files for the search head cluster, not the apps that are distributed by the deployer3.

The etc/deploy-apps/ directory is not a valid Splunk directory, as it does not exist in the Splunk file system structure4.

Splunk provides various methods to change the internal logging levels in a Splunk environment to troubleshoot an issue. All of the options are valid ways to do so. Option A is correct because the Monitoring Console (MC) allows the administrator to view and modify the logging levels of various Splunk components through a graphical interface. Option B is correct because the Splunk command line provides the splunk set log-level command to change the logging levels of specific components or categories. Option C is correct because the Splunk Web provides the Settings > Server settings > Server logging page to change the logging levels of various components through a web interface. Option D is correct because the log-local.cfg file allows the administrator to manually edit the logging levels of various components by overriding the default settings in the log.cfg file123

1: https://docs.splunk.com/Documentation/Splunk/9.1.2/Troubleshooting/Enabledebuglogging 2: https://docs.splunk.com/Documentation/Splunk/9.1.2/Admin/Serverlogging 3: https://docs.splunk.com/Documentation/Splunk/9.1.2/Admin/Loglocalcfg

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.

This is a mandatory Splunk component when implementing a search head cluster, as it is responsible for distributing the configuration updates and app bundles to the cluster members1. The deployer is a separate instance that communicates with the cluster manager and pushes the changes to the search heads1. The other options are not mandatory components for a search head cluster. Option A, Captain Server, is not a component, but a role that is dynamically assigned to one of the search heads in the cluster2. The captain coordinates the replication and search activities among the cluster members2. Option C, Cluster Manager, is a component for an indexer cluster, not a search head cluster3. The cluster manager manages the replication and search factors, and provides a web interface for monitoring and managing the indexer cluster3. Option D, RAFT Server, is not a component, but a protocol that is used by the search head cluster to elect the captain and maintain the cluster state4. Therefore, option B is the correct answer, and options A, C, and D are incorrect.

1: Use the deployer to distribute apps and configuration updates 2: About the captain 3: About the cluster manager 4: How a search head cluster works

 The following artifacts are included in a Splunk diag file:

Internal logs. These are the log files that Splunk generates to record its own activities, such as splunkd.log, metrics.log, audit.log, and others. These logs can help troubleshoot Splunk issues and monitor Splunk performance.

Configuration files. These are the files that Splunk uses to configure various aspects of its operation, such as server.conf, indexes.conf, props.conf, transforms.conf, and others. These files can help understand Splunk settings and behavior. The following artifacts are not included in a Splunk diag file:

OS settings. These are the settings of the operating system that Splunk runs on, such as the kernel version, the memory size, the disk space, and others. These settings are not part of the Splunk diag file, but they can be collected separately using the diag --os option.

Customer data. These are the data that Splunk indexes and makes searchable, such as the rawdata and the tsidx files. These data are not part of the Splunk diag file, as they may contain sensitive or confidential information. For more information, see Generate a diagnostic snapshot of your Splunk Enterprise deployment in the Splunk documentation.

The master node is the Splunk server role that regulates the functioning of the indexer cluster. The master node coordinates the activities of the peer nodes, such as data replication, data searchability, and data recovery. The master node also manages the cluster configuration bundle and distributes it to the peer nodes. The indexer is the Splunk server role that indexes the incoming data and makes it searchable. The deployer is the Splunk server role that distributes apps and configuration updates to the search head cluster members. The monitoring console is the Splunk server role that monitors the health and performance of the Splunk deployment. For more information, see About indexer clusters and index replication in the Splunk documentation.

 The AggregatorMiningProcessor component in the splunkd.log file will log information related to bad event breaking. The AggregatorMiningProcessor is responsible for breaking the incoming data into events and applying the props.conf settings. If there is a problem with the event breaking, such as incorrect timestamps, missing events, or merged events, the AggregatorMiningProcessor will log the error or warning messages in the splunkd.log file. The Audittrail component logs information about the audit events, such as user actions, configuration changes, and search activity. The EventBreaking component logs information about the event breaking rules, such as the LINE_BREAKER and SHOULD_LINEMERGE settings. The IndexingPipeline component logs information about the indexing pipeline, such as the parsing, routing, and indexing phases. For more information, see About Splunk Enterprise logging and [Configure event line breaking] in the Splunk documentation.

In search head clustering, there are two methods to transfer captaincy to a different member. One method is to use the Search Head Clustering settings menu from Splunk Web on any member. This method allows the user to select a specific member to become the new captain, or to let Splunk choose the best candidate. The other method is to run the splunk transfer shcluster-captain command from the member that the user wants to become the new captain. This method requires the user to know the name of the target member and to have access to the CLI of that member. Using the Monitoring Console is not a method to transfer captaincy, because the Monitoring Console does not have the option to change the captain. Running the splunk transfer shcluster-captain command from the current captain is not a method to transfer captaincy, because this command will fail with an error message

According to Splunk Enterprise Search Performance and Deployment Optimization guidelines, the phone home interval (configured for deployment clients communicating with a Deployment Server) has no impact on search performance.

The phone home mechanism controls how often deployment clients check in with the Deployment Server for configuration updates or new app bundles. This process occurs independently of the search subsystem and does not consume indexer or search head resources that affect query speed, indexing throughput, or search concurrency.

In contrast:

Increasing the number of indexers (Option B) improves search performance by distributing indexing and search workloads across more nodes.

Workload Management (Option C) allows admins to prioritize compute and memory resources for critical searches, optimizing performance under load.

Increasing search heads (Option D) can enhance concurrency and user responsiveness by distributing search scheduling and ad-hoc query workloads.

Therefore, adjusting the phone home interval is strictly an administrative operation and has no measurable effect on Splunk search or indexing performance.

References (Splunk Enterprise Documentation):

• Deployment Server: Managing Phone Home Intervals

• Search Performance Optimization and Resource Management

• Distributed Search Architecture and Scaling Best Practices

• Workload Management Overview – Resource Allocation in Search Operations

Splunk Enterprise performs a CRC check against the first and last 256 bytes of a file by default, as stated in the inputs.conf specification. This is controlled by the initCrcLength parameter, which can be changed if needed. The CRC check helps Splunk Enterprise to avoid re-indexing the same file twice, even if it is renamed or rotated, as long as the content does not change. However, this also means that Splunk Enterprise might miss some files that have the same CRC but different content, especially if they have identical headers. To avoid this, the crcSalt parameter can be used to add some extra information to the CRC calculation, such as the full file path or a custom string. This ensures that each file has a unique CRC and is indexed by Splunk Enterprise. You can read more about crcSalt and initCrcLength in the How log file rotation is handled documentation.

 The index-time props.conf attributes that impact indexing performance are LINE_BREAKER and SHOULD_LINEMERGE. These attributes determine how Splunk breaks the incoming data into events and whether it merges multiple events into one. These operations can affect the indexing speed and the disk space consumption. The REPORT attribute does not impact indexing performance, as it is used to apply transforms at search time. The ANNOTATE_PUNCT attribute does not impact indexing performance, as it is used to add punctuation metadata to events at search time. For more information, see [About props.conf and transforms.conf] in the Splunk documentation.

A dedicated deployment server is a Splunk instance that manages the distribution of configuration updates and apps to a set of deployment clients, such as forwarders, indexers, or search heads. A dedicated deployment server should be used when there are more than 50 deployment clients, because this number exceeds the recommended limit for a non-dedicated deployment server. A non-dedicated deployment server is a Splunk instance that also performs other roles, such as indexing or searching. Using a dedicated deployment server can improve the performance, scalability, and reliability of the deployment process. Option C is the correct answer. Option A is incorrect because the number of search peers does not affect the need for a dedicated deployment server. Search peers are indexers that participate in a distributed search. Option B is incorrect because the number of apps to deploy does not affect the need for a dedicated deployment server. Apps are packages of configurations and assets that provide specific functionality or views in Splunk. Option D is incorrect because the number of server classes does not affect the need for a dedicated deployment server. Server classes are logical groups of deployment clients that share the same configuration updates and apps12

1: https://docs.splunk.com/Documentation/Splunk/9.1.2/Updating/Aboutdeploymentserver 2: https://docs.splunk.com/Documentation/Splunk/9.1.2/Updating/Whentousedeploymentserver

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.

Splunk indexing is read/write intensive, as it involves reading data from various sources, writing data to disk, and reading data from disk for searching and reporting. Therefore, it is important to select the appropriate disk storage solution for each deployment, based on the performance, reliability, and cost requirements. The recommended RAID setup for Splunk indexers is RAID 10 (1 + 0), as it provides the best balance of performance and reliability. RAID 10 combines the advantages of RAID 1 (mirroring) and RAID 0 (striping), which means that it offers both data redundancy and data distribution. RAID 10 can tolerate multiple disk failures, as long as they are not in the same mirrored pair, and it can improve the read and write speed, as it can access multiple disks in parallel2

High performance SAN (Storage Area Network) can be used for Splunk indexers, but it is not recommended, as it is more expensive and complex than local disks. SAN also introduces additional network latency and dependency, which can affect the performance and availability of Splunk indexers. SAN is more suitable for Splunk search heads, as they are less read/write intensive and more CPU intensive2

NFS (Network File System) should not be used for storing hot and warm buckets, as it can cause data corruption, data loss, and performance degradation. NFS is a network-based file system that allows multiple clients to access the same files on a remote server. NFS is not compatible with Splunk index replication and search head clustering, as it can cause conflicts and inconsistencies among the Splunk instances. NFS is also slower and less reliable than local disks, as it depends on the network bandwidth and availability. NFS can be used for storing cold and frozen buckets, as they are less frequently accessed and less critical for Splunk operations2

Virtualized environments are not usually preferred over bare metal for Splunk indexers, as they can introduce additional overhead and complexity. Virtualized environments can affect the performance and reliability of Splunk indexers, as they share the physical resources and the network with other virtual machines. Virtualized environments can also complicate the monitoring and troubleshooting of Splunk indexers, as they add another layer of abstraction and configuration. Virtualized environments can be used for Splunk indexers, but they require careful planning and tuning to ensure optimal performance and availability2

The splunk offline --enforce-counts command is the official and documented method used to gracefully decommission a search peer (indexer) from an indexer cluster in Splunk Enterprise. This command ensures that all replication and search factors are maintained before the peer is removed.

When executed, Splunk initiates a controlled shutdown process for the peer node. The Cluster Manager verifies that sufficient replicated copies of all bucket data exist across the remaining peers according to the configured replication_factor (RF) and search_factor (SF). The --enforce-counts flag specifically enforces that replication and search counts remain intact before the peer fully detaches from the cluster, ensuring no data loss or availability gap.

The sequence typically includes:

Validating cluster state and replication health.

Rolling off the peer’s data responsibilities to other peers.

Removing the peer from the active cluster membership list once replication is complete.

Other options like disablepeer, decommission, or remove cluster-peers are not valid Splunk commands. Therefore, the correct documented method is to use:

splunk offline --enforce-counts

References (Splunk Enterprise Documentation):

• Indexer Clustering: Decommissioning a Peer Node

• Managing Peer Nodes and Maintaining Data Availability

• Splunk CLI Command Reference – splunk offline

• Cluster Manager and Peer Maintenance Procedures

According to the Indexer Clustering Administration Guide, configuration bundles pushed from the Cluster Manager (Master Node) overwrite the contents of the $SPLUNK_HOME/etc/slave-apps/ directory on each search peer (indexer). However, Splunk provides a special persistent location — the _cluster app’s local directory — for files that must survive bundle redeployments.

Specifically, any configuration files placed in:

$SPLUNK_HOME/etc/slave-apps/_cluster/local/

will persist after future bundle pushes because this directory is excluded from the automatic overwrite process.

This is particularly useful for maintaining local overrides or custom configurations that should not be replaced by the Cluster Manager, such as environment-specific inputs, temporary test settings, or monitoring configurations unique to that peer.

Other directories under slave-apps are overwritten each time a configuration bundle is pushed, ensuring consistency across the cluster. Likewise, master-apps exists only on the Cluster Manager and is used for deployment, not persistence.

Thus, the _cluster/local folder is the only safe, Splunk-documented location for configurations that need to survive bundle redeployment.

References (Splunk Enterprise Documentation):

• Indexer Clustering: How Configuration Bundles Work

• Maintaining Local Configurations on Clustered Indexers

• slave-apps and _cluster App Structure and Behavior

• Splunk Enterprise Admin Manual – Cluster Configuration Management Best Practices

 The Splunk Universal Forwarder is the only Splunk Enterprise offering that has its own license. The Splunk Universal Forwarder license allows the forwarder to send data to any Splunk Enterprise or Splunk Cloud instance without consuming any license quota. The Splunk Heavy Forwarder does not have its own license, but rather consumes the license quota of the Splunk Enterprise or Splunk Cloud instance that it sends data to. The Splunk Cloud Forwarder and the Splunk Forwarder Management are not separate Splunk Enterprise offerings, but rather features of the Splunk Cloud service. For more information, see [About forwarder licensing] in the Splunk documentation.

 The splunk diag --exclude command is a way to exclude search artifacts when creating a diag. A diag is a diagnostic snapshot of a Splunk instance that contains various logs, configurations, and other information. Search artifacts are temporary files that are generated by search jobs and stored in the dispatch directory. Search artifacts can be excluded from the diag by using the --exclude option and specifying the dispatch directory. The splunk diag --debug --refresh command is a way to create a diag with debug logging enabled and refresh the diag if it already exists. The splunk diag --disable=dispatch command is not a valid command, because the --disable option does not exist. The splunk diag --filter-searchstrings command is a way to filter out sensitive information from the search strings in the diag

According to the Splunk documentation1, increasing the current deployment client phone home interval can minimize performance issues by reducing the frequency of communication between the clients and the deployment server. This can also reduce the network traffic and the load on the deployment server. The other options are false because:

Modifying deploymentclient.conf to change from a Pull to Push mechanism is not possible, as Splunk does not support a Push mechanism for deployment server2.

Reducing the number of apps in the Manager Node repository will not affect the performance of the deployment server, as the apps are only downloaded when there is a change in the configuration or a new app is added3.

Decreasing the current deployment client phone home interval will increase the performance issues, as it will increase the frequency of communication between the clients and the deployment server, resulting in more network traffic and load on the deployment server1.

Splunk Enterprise Search Optimization documentation consistently emphasizes that filtering data as early as possible in the search pipeline is the most effective way to improve search performance. The base search (the part before the first pipe |) determines the volume of raw events Splunk retrieves from the indexers. Therefore, by applying restrictive conditions early—such as time ranges, indexed fields, and metadata filters—you can drastically reduce the number of events that need to be fetched and processed downstream.

The best practice is to use indexed field filters (e.g., index=security sourcetype=syslog host=server01) combined with search or where clauses at the start of the query. This minimizes unnecessary data movement between indexers and the search head, improving both search speed and system efficiency.

Using non-streaming commands early (Option C) can degrade performance because they require full result sets before producing output. Likewise, focusing solely on shortening queries (Option A) or excessive use of the not operator (Option D) does not guarantee efficiency, as both may still process large datasets.

Filtering early leverages Splunk’s distributed search architecture to limit data at the indexer level, reducing processing load and network transfer.

References (Splunk Enterprise Documentation):

• Search Performance Tuning and Optimization Guide

• Best Practices for Writing Efficient SPL Queries

• Understanding Streaming and Non-Streaming Commands

• Search Job Inspector: Analyzing Execution Costs

The correct answer is B. Set the Replication Factor based on allowed indexer failure. This is a best practice for adding data resiliency to a single-site indexer cluster, as it ensures that there are enough copies of each bucket to survive the loss of one or more indexers without affecting the searchability of the data1. The Replication Factor is the number of copies of each bucket that the cluster maintains across the set of peer nodes2. The Replication Factor should be set according to the number of indexers that can fail without compromising the cluster’s ability to serve data1. For example, if the cluster can tolerate the loss of two indexers, the Replication Factor should be set to three1.

The other options are not best practices for adding data resiliency. Option A, setting the Replication Factor to 49, is not recommended, as it would create too many copies of each bucket and consume excessive disk space and network bandwidth1. Option C, always using the default Replication Factor of 3, is not optimal, as it may not match the customer’s requirements and expectations for data availability and performance1. Option D, setting the Replication Factor based on allowed search head failure, is not relevant, as the Replication Factor does not affect the search head availability, but the searchability of the data on the indexers1. Therefore, option B is the correct answer, and options A, C, and D are incorrect.

1: Configure the replication factor 2: About indexer clusters and index replication

Within the [clustering] stanza of the server.conf file, the mode attribute defines the functional role of a Splunk instance within an indexer cluster. Splunk documentation identifies three valid modes:

mode = manager

Defines the node as the Cluster Manager (formerly called the Master Node).

Responsible for coordinating peer replication, managing configurations, and ensuring data integrity across indexers.

mode = peer

Defines the node as an Indexer (Peer Node) within the cluster.

Handles data ingestion, replication, and search operations under the control of the manager node.

mode = searchhead

Defines a Search Head that connects to the cluster for distributed searching and data retrieval.

The value “deployer” (Option C) is not valid within the [clustering] stanza; it applies to Search Head Clustering (SHC) configurations, where it is defined separately in server.conf under [shclustering].

Each mode must be accompanied by other critical attributes such as manager_uri, replication_port, and pass4SymmKey to enable proper communication and security between cluster members.

References (Splunk Enterprise Documentation):

• Indexer Clustering: Configure Manager, Peer, and Search Head Modes

• server.conf Reference – [clustering] Stanza Attributes

• Distributed Search and Cluster Node Role Configuration

• Splunk Enterprise Admin Manual – Cluster Deployment Architecture

The index=_internal component=DC* host= search will show all deployment client messages from the universal forwarder. The component field indicates the type of Splunk component that generated the message, and the host field indicates the host name of the machine that sent the message. The index=_audit component=DC* host= search will not return any results, because the deployment client messages are not stored in the _audit index. The index=_internal component=DS* host= search will show the deployment server messages from the deployment server, not the client. The index=_audit component=DS* host= search will also not return any results, for the same reason as above

Increasing the search factor in the cluster will best address the requirement of high availability for searchable data. The search factor determines how many copies of searchable data are maintained by the cluster. A higher search factor means that more indexers can serve the data in case of a failure or a maintenance event. Increasing the replication factor will improve the availability of raw data, but not searchable data. Increasing the number of search heads or CPUs on the indexers will improve the search performance, but not the availability of searchable data. For more information, see Replication factor and search factor in the Splunk documentation.

Number of concurrent users: This is an important factor because it affects the search performance and resource utilization of the Splunk environment. More users mean more concurrent searches, which require more CPU, memory, and disk I/O. The number of concurrent users also determines the search head capacity and the search head clustering configuration12

Volume of incoming data: This is another crucial factor because it affects the indexing performance and storage requirements of the Splunk environment. More data means more indexing throughput, which requires more CPU, memory, and disk I/O. The volume of incoming data also determines the indexer capacity and the indexer clustering configuration13

Existence of premium apps: This is a relevant factor because some premium apps, such as Splunk Enterprise Security and Splunk IT Service Intelligence, have additional requirements and recommendations for the Splunk environment. For example, Splunk Enterprise Security requires a dedicated search head cluster and a minimum of 12 CPU cores per search head. Splunk IT Service Intelligence requires a minimum of 16 CPU cores and 64 GB of RAM per search head45

According to Splunk Enterprise documentation for the Monitoring Console (MC), the data displayed in its dashboards is sourced primarily from two internal mechanisms — REST API calls and metrics.log.

The Monitoring Console (formerly known as the Distributed Management Console, or DMC) uses REST API endpoints to collect system-level information from all connected instances, such as indexer clustering status, license usage, and search head performance. These REST calls pull real-time configuration and performance data from Splunk’s internal management layer (/services/server/status, /services/licenser, /services/cluster/peers, etc.).

Additionally, the metrics.log file is one of the main data sources used by the Monitoring Console. This log records Splunk’s internal performance metrics, including pipeline latency, queue sizes, indexing throughput, CPU usage, and memory statistics. Dashboards like “Indexer Performance,” “Search Performance,” and “Resource Usage” are powered by searches over the _internal index that reference this log.

Other tools listed — such as btool (configuration troubleshooting utility) and diag (diagnostic archive generator) — are not used as runtime data sources for Monitoring Console dashboards. They assist in troubleshooting but are not actively queried by the MC.

References (Splunk Enterprise Documentation):

• Monitoring Console Overview – Data Sources and Architecture

• metrics.log Reference – Internal Performance Data Collection

• REST API Usage in Monitoring Console

• Distributed Management Console Configuration Guide

To expand the search head cluster by adding a new member, node2, the first step is to initialize the cluster configuration on node2 using the splunk init shcluster-config command. This command sets the required parameters for the cluster member, such as the management URI, the replication port, and the shared secret key. The management URI must be unique for each cluster member and must match the URI that the deployer uses to communicate with the member. The replication port must be the same for all cluster members and must be different from the management port. The secret key must be the same for all cluster members and must be encrypted using the splunk _encrypt command. The master_uri parameter is optional and specifies the URI of the cluster captain. If not specified, the cluster member will use the captain election process to determine the captain. Option C shows the correct syntax and parameters for the splunk init shcluster-config command. Option A is incorrect because the splunk bootstrap shcluster-config command is used to bring up the first cluster member as the initial captain, not to add a new member. Option B is incorrect because the master_uri parameter is not required and the mgmt_uri parameter is missing. Option D is incorrect because the splunk add shcluster-member command is used to add an existing search head to the cluster, not to initialize a new member12

1: https://docs.splunk.com/Documentation/Splunk/9.1.2/DistSearch/SHCdeploymentoverview#Initialize_cluster_members 2: https://docs.splunk.com/Documentation/Splunk/9.1.2/DistSearch/SHCconfigurationdetails#Configure_the_cluster_members

The splunk rebuild command is used for thawing the archive bucket. Thawing is the process of restoring frozen data back to Splunk for searching. Frozen data is data that has been archived or deleted from Splunk after reaching the end of its retention period. To thaw a bucket, the user needs to copy the bucket from the archive location to the thaweddb directory under SPLUNK_HOME/var/lib/splunk and run the splunk rebuild command to rebuild the .tsidx files for the bucket. The splunk collect command is used for collecting diagnostic data from a Splunk instance. The splunk convert command is used for converting configuration files from one format to another. The splunk dbinspect command is used for inspecting the status and properties of the buckets in an index.

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

Index files (. tsidx files) are the main components of an index that store the raw data and the inverted index of terms. They take the most space in an index, especially if the raw data has many unique terms that increase the size of the inverted index. Bloom filters, source metadata, and sourcetype metadata are much smaller in comparison and do not depend on the number of unique terms in the raw data.

The best practice for ingesting syslog data from network devices on port 514 into Splunk is to configure syslog to write logs and use a Splunk forwarder to collect the logs. This practice will ensure that the data is reliably collected and forwarded to Splunk, without losing any data or overloading the Splunk indexer. Configuring syslog to send the data to multiple Splunk indexers will not guarantee data reliability, as syslog is a UDP protocol that does not provide acknowledgment or delivery confirmation. Using a Splunk indexer to collect a network input on port 514 directly will not provide data reliability or load balancing, as the indexer may not be able to handle the incoming data volume or distribute it to other indexers. Using a Splunk forwarder to collect the input on port 514 and forward the data will not provide data reliability, as the forwarder may not be able to receive the data from syslog or buffer it in case of network issues. For more information, see [Get data from TCP and UDP ports] and [Best practices for syslog data] in the Splunk documentation.

 When adding or rejoining a member to a search head cluster, and the following error is displayed: Error pulling configurations from the search head cluster captain; consider performing a destructive configuration resync on this search head cluster member.

The corrective action that should be taken is to run the splunk resync shcluster-replicated-config command on this member. This command will delete the existing configuration files on this member and replace them with the latest configuration files from the captain. This will ensure that the member has the same configuration as the rest of the cluster. Restarting the search head, running the splunk apply shcluster-bundle command from the deployer, or running the clean raft command on all members of the search head cluster are not the correct actions to take in this scenario. For more information, see Resolve configuration inconsistencies across cluster members in the Splunk documentation.

Splunk Enterprise uses the _audit index to log and store all user activity and audit-related information. This includes details such as user logins, searches executed, configuration changes, role modifications, and app management actions.

The _audit index is populated by data collected from the Splunkd audit logger and records actions performed through both Splunk Web and the CLI. Each event in this index typically includes fields like user, action, info, search_id, and timestamp, allowing administrators to track activity across all Splunk users and components for security, compliance, and accountability purposes.

The _internal index, by contrast, contains operational logs such as metrics.log and scheduler.log used for system performance and health monitoring. _kvstore stores internal KV Store metadata, and _telemetry is used for optional usage data reporting to Splunk.

The _audit index is thus the authoritative source for user behavior monitoring within Splunk environments and is a key component of compliance and security auditing.

References (Splunk Enterprise Documentation):

• Audit Logs and the _audit Index – Monitoring User Activity

• Splunk Enterprise Security and Compliance: Tracking User Actions

• Splunk Admin Manual – Overview of Internal Indexes (_internal, _audit, _introspection)

• Splunk Audit Logging and User Access Monitoring

The splunk offline --enforce-counts command will permanently decommission a peer node operating in an indexer cluster. This command will remove the peer node from the cluster and delete its data. This command should be used when the peer node is no longer needed or is being replaced by another node. The splunk stop -f command will stop the Splunk service on the peer node, but it will not decommission it from the cluster. The splunk offline -f command will take the peer node offline, but it will not delete its data or enforce the replication and search factors. The splunk decommission --enforce-counts command is not a valid Splunk command. For more information, see Remove a peer node from an indexer cluster in the Splunk documentation.

In Splunk Enterprise, manually editing the serverclass.conf file on a Deployment Server can lead to the loss of UI edit functionality for server classes in Splunk Web.

The Deployment Server manages app distribution to Universal Forwarders and other deployment clients through server classes, which are defined in serverclass.conf. This file maps deployment clients to specific app configurations and defines filtering rules, restart behaviors, and inclusion/exclusion criteria.

When this configuration file is modified manually (outside of Splunk Web), the syntax, formatting, or logical relationships between entries may not match what Splunk Web expects. As a result, Splunk Web may no longer be able to parse or display those server classes correctly. Once this happens, administrators cannot modify deployment settings through the GUI until the configuration file is corrected or reverted to a valid state.

Other files such as deploymentclient.conf, inputs.conf, and deploymentserver.conf control client settings, data inputs, and core server parameters but do not affect the UI-driven deployment management functionality.

Therefore, Splunk explicitly warns administrators in its Deployment Server documentation to use Splunk Web or the CLI when modifying serverclass.conf, and to avoid manual editing unless fully confident in its syntax.

References (Splunk Enterprise Documentation):

• Deployment Server Overview – Managing Server Classes and App Deployment

• serverclass.conf Reference and Configuration Best Practices

• Splunk Enterprise Admin Manual – GUI Limitations After Manual Edits

• Troubleshooting Deployment Server and Serverclass Configuration Issues

A search head cluster is a group of Splunk Enterprise search heads that share configurations, job scheduling, and search artifacts1. The deployer is a Splunk Enterprise instance that distributes apps and other configurations to the cluster members1. The local folder of each Splunk app contains the custom configurations that override the default settings2. The default folder of each Splunk app contains the default configurations that are provided by the app2.

By default, when the deployer pushes an app to the search head cluster, it merges the local folder of the app into the default folder and deploys the merged folder to the search heads3. This means that the custom configurations in the local folder will take precedence over the default settings in the default folder. However, this also means that the local folder of the app on the search heads will be empty, unless the app is modified through the search head UI3.

Option B is the correct answer because it reflects the default behavior of the deployer when pushing apps to the search head cluster. Option A is incorrect because the local folder is not copied to the local folder on the search heads, but merged into the default folder. Option C is incorrect because all the .conf files in the local folder are deployed to the search heads, not only certain ones. Option D is incorrect because the local folder is not ignored, but merged into the default folder.

The default interval at which metrics.log generates a periodic report regarding license utilization is 60 seconds. This report contains information about the license usage and quota for each Splunk instance, as well as the license pool and stack. The report is generated every 60 seconds by default, but this interval can be changed by modifying the license_usage stanza in the metrics.conf file. The other intervals (10 seconds, 30 seconds, and 300 seconds) are not the default values, but they can be set by the administrator if needed. For more information, see About metrics.log and Configure metrics.log in the Splunk documentation.

 The following artifacts are included in a Splunk diag file:

Server specs. These are the specifications of the server that Splunk runs on, such as the CPU model, the memory size, the disk space, and the network interface. These specs can help understand the Splunk hardware requirements and performance.

Current open connections. These are the connections that Splunk has established with other Splunk instances or external sources, such as forwarders, indexers, search heads, license masters, deployment servers, and data inputs. These connections can help understand the Splunk network topology and communication.

Internal Splunk log files. These are the log files that Splunk generates to record its own activities, such as splunkd.log, metrics.log, audit.log, and others. These logs can help troubleshoot Splunk issues and monitor Splunk performance.

Index listings. These are the listings of the indexes that Splunk has created and configured, such as the index name, the index location, the index size, and the index attributes. These listings can help understand the Splunk data management and retention. The following artifacts are not included in a Splunk diag file:

Search history. This is the history of the searches that Splunk has executed, such as the search query, the search time, the search results, and the search user. This history is not part of the Splunk diag file, but it can be accessed from the Splunk Web interface or the audit.log file.

Splunk users and their roles. These are the users that Splunk has created and assigned roles to, such as the user name, the user password, the user role, and the user capabilities. These users and roles are not part of the Splunk diag file, but they can be accessed from the Splunk Web interface or the authentication.conf and authorize.conf files.

KV store listings. These are the listings of the KV store collections and documents that Splunk has created and stored, such as the collection name, the collection schema, the document ID, and the document fields. These listings are not part of the Splunk diag file, but they can be accessed from the Splunk Web interface or the mongod.log file.

Indexed data. These are the data that Splunk indexes and makes searchable, such as the rawdata and the tsidx files. These data are not part of the Splunk diag file, as they may contain sensitive or confidential information. For more information, see Generate a diagnostic snapshot of your Splunk Enterprise deployment in the Splunk documentation.