SPLK-2002 Questions and Answers

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.

 In a distributed environment, knowledge object bundles are replicated from the search head to the SPLUNK_HOME/var/run/searchpeers directory on the search peer(s). A knowledge object bundle is a compressed file that contains the knowledge objects, such as fields, lookups, macros, and tags, that are required for a search. A search peer is a Splunk instance that provides data to a search head in a distributed search. A search head is a Splunk instance that coordinates and executes a search across multiple search peers. When a search head initiates a search, it creates a knowledge object bundle and replicates it to the search peers that are involved in the search. The search peers store the knowledge object bundle in the SPLUNK_HOME/var/run/searchpeers directory, which is a temporary directory that is cleared when the Splunk service restarts. The search peers use the knowledge object bundle to apply the knowledge objects to the data and return the results to the search head. The SPLUNK_HOME/var/lib/searchpeers, SPLUNK_HOME/var/log/searchpeers, and SPLUNK_HOME/var/spool/searchpeers directories are not the locations where the knowledge object bundles are replicated, because they do not exist in the Splunk file system

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 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

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

According to the Splunk documentation1, metrics.log is a file that contains various metrics data for reviewing product behavior, such as pipeline, queue, thruput, and tcpout_connections. Metrics.log is stored in the _internal index by default2, which is a special index that contains internal logs and metrics for Splunk Enterprise. The other options are false because:

• main is the default index for user data, not internal data3.
• _telemetry is an index that contains data collected by the Splunk Telemetry feature, which sends anonymous usage and performance data to Splunk4.
• _introspection is an index that contains data collected by the Splunk Monitoring Console, which monitors the health and performance of Splunk components.

• The deployer is a Splunk Enterprise instance that distributes apps and other configurations to the members of a search head cluster1.
• The deployer cannot share functionality with any other Splunk Enterprise instance, including the license master, the master node, or the monitoring console2.
• However, the search head cluster members can share functionality with the master node and the monitoring console, as long as they are not designated as the captain of the cluster3.
• Therefore, the correct answer is B. License master, as it is the only instance that cannot share functionality with the deployer under any circumstances.

References: 1: About the deployer 2: Deployer system requirements 3: Search head cluster architecture

According to the Splunk documentation1, when migrating an indexer cluster from single-site to multi-site, you must remove the existing single-site attributes from the server.conf file of each peer node. These attributes include replication_factor, search_factor, and cluster_label. You must also restart each peer node after removing the attributes. The other options are false because:

• Multi-site policies will apply only to the data created after migration, unless you configure the manager node to convert legacy buckets to multi-site1.
• All peer nodes do not need to run the same version of Splunk, as long as they are compatible with the manager node2.
• Single-site buckets can be converted to multi-site buckets by changing the constrain_singlesite_buckets setting in the manager node’s server.conf file to "false"1.

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]

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 __introspection log file contains data about the impact of the Splunk software on the host system, such as CPU, memory, disk, and network usage, as well as KV store performance1. This log file is monitored by default and the contents are sent to the _introspection index1. The other options are not related to the __introspection log file. File monitor input configurations are stored in inputs.conf2. File monitor checkpoint offset is stored in fishbucket3. User activities and knowledge objects are stored in the _audit and _internal indexes respectively4.

A multisite indexer cluster is a type of indexer cluster that spans multiple geographic locations or sites. A multisite indexer cluster requires only one cluster manager, also known as the master node, for the entire cluster. The cluster manager is responsible for coordinating the replication and search activities among the peer nodes across all sites. The cluster manager can reside in any site, but it must be accessible by all peer nodes and search heads in the cluster. Option C is the correct answer. Option A is incorrect because having two cluster managers for the entire cluster would introduce redundancy and complexity. Option B is incorrect because having one cluster manager for each site would create separate clusters, not a multisite cluster. Option D is incorrect because having two cluster managers for each site would be unnecessary and inefficient12

1: https://docs.splunk.com/Documentation/Splunk/9.1.2/Indexer/Multisiteoverview  2: https://docs.splunk.com/Documentation/Splunk/9.1.2/Indexer/Clustermanageroverview

The Indexer Discovery feature enables forwarders to dynamically connect to the available peer nodes in an indexer cluster. To use this feature, the manager node must be configured with the [indexer_discovery] stanza and a pass4SymmKey value. The forwarders must also be configured with the same pass4SymmKey value and the master_uri of the manager node. The pass4SymmKey value must be encrypted using the splunk _encrypt command. Therefore, option A indicates that the Indexer Discovery feature has not been fully configured on the manager node, because the pass4SymmKey value is not encrypted. The other options are not related to the Indexer Discovery feature. Option B shows the configuration of a forwarder that is part of an indexer cluster. Option C shows the configuration of a manager node that is part of an indexer cluster. Option D shows an invalid configuration of the [indexer_discovery] stanza, because the pass4SymmKey value is not encrypted and does not match the forwarders’ pass4SymmKey value12

1: https://docs.splunk.com/Documentation/Splunk/9.1.2/Indexer/indexerdiscovery  2: https://docs.splunk.com/Documentation/Splunk/9.1.2/Security/Secureyourconfigurationfiles#Encrypt_the_pass4SymmKey_setting_in_server.conf

 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.

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​​.

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

The correct action to take first if a deployment client is not updating apps is to choose a corrective action based on the splunkd.log of the deployment client. This log file contains information about the communication between the deployment server and the deployment client, and it can help identify the root cause of the problem1. The other actions may or may not help, depending on the situation, but they are not the first steps to take. Choosing a longer phone home interval may reduce the load on the deployment server, but it will also delay the updates for the deployment clients2. Increasing the number of CPU cores or the amount of memory for the deployment server may improve its performance, but it will not fix the issue if the problem is on the deployment client side3. Therefore, option C is the correct answer, and options A, B, and D are incorrect.

1: Troubleshoot deployment server issues 2: Configure deployment clients 3: Hardware and software requirements for the deployment server

The following security option must be explicitly configured, as it is not enabled by default:

• Certificate authentication between forwarders and indexers. This option allows the forwarders and indexers to verify each other’s identity using SSL certificates, which prevents unauthorized data transmission or spoofing attacks. This option is not enabled by default, as it requires the administrator to generate and distribute the certificates for the forwarders and indexers. For more information, see [Secure the communication between forwarders and indexers] in the Splunk documentation. The following security options are enabled by default:
• Data encryption between Splunk Web and splunkd. This option encrypts the communication between the Splunk Web interface and the splunkd daemon using SSL, which prevents data interception or tampering. This option is enabled by default, as Splunk provides a self-signed certificate for this purpose. For more information, see [About securing Splunk Enterprise with SSL] in the Splunk documentation.
• Certificate authentication between Splunk Web and search head. This option allows the Splunk Web interface and the search head to verify each other’s identity using SSL certificates, which prevents unauthorized access or spoofing attacks. This option is enabled by default, as Splunk provides a self-signed certificate for this purpose. For more information, see [About securing Splunk Enterprise with SSL] in the Splunk documentation.
• Data encryption for distributed search between search heads and indexers. This option encrypts the communication between the search heads and the indexers using SSL, which prevents data interception or tampering. This option is enabled by default, as Splunk provides a self-signed certificate for this purpose. For more information, see [Secure your distributed search environment] in the Splunk documentation.

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.

Indexed extraction configurations are processed in the indexing phase of the Splunk Enterprise data pipeline. The data pipeline is the process that Splunk uses to ingest, parse, index, and search data. Indexed extraction configurations are settings that determine how Splunk extracts fields from data at index time, rather than at search time. Indexed extraction can improve search performance, but it also increases the size of the index. Indexed extraction configurations are applied in the indexing phase, which is the phase where Splunk writes the data and the .tsidx files to the index. The input phase is the phase where Splunk receives data from various sources and formats. The parsing phase is the phase where Splunk breaks the data into events, timestamps, and hosts. The search phase is the phase where Splunk executes search commands and returns results.

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

 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.

Primary rebalancing automatically occurs when a rolling restart completes, a master node rejoins the cluster, or a peer node joins or rejoins the cluster. These events can cause the distribution of primary buckets to become unbalanced, so the master node will initiate a rebalancing process to ensure that each peer node has roughly the same number of primary buckets. Primary rebalancing does not occur when a captain joins or rejoins the cluster, because the captain is a search head cluster component, not an indexer cluster component. The captain is responsible for search head clustering, not indexer clustering

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.

References:

1: Search head clustering architecture - Splunk Documentation 2: About configuration files - Splunk Documentation 3: Use the deployer to distribute apps and configuration updates - Splunk Documentation

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.

References:

1: About configuration files - Splunk Documentation 2: Use the search.log file - Splunk Documentation 3: Troubleshoot search-time field extraction - Splunk Documentation 4: Use btool to troubleshoot configurations - Splunk Documentation 5: Troubleshoot configuration issues - Splunk Documentation 6: About the diagnostic utility - Splunk Documentation 7: Use the diagnostic utility - Splunk Documentation 8: About crash logs - Splunk Documentation 9: [Troubleshoot Splunk Enterprise crashes - Splunk Documentation]

 The Splunk instance with the given settings in SPLUNK_HOME/etc/system/local/server.conf is missing the master_uri attribute and needs to be restarted. The master_uri attribute is required for the master node to communicate with the peer nodes and the search head cluster. The master_uri attribute specifies the host name and port number of the master node. Without this attribute, the master node cannot function properly. The Splunk instance also needs to be restarted for the changes in the server.conf file to take effect. The replication_factor setting determines how many copies of each bucket are maintained across the peer nodes. The search factor is a separate setting that determines how many searchable copies of each bucket are maintained across the peer nodes. The search factor is not specified in the given settings, so it defaults to the same value as the replication factor, which is 2. This is not a multi-site cluster, because the site attribute is not specified in the clustering stanza. A multi-site cluster is a cluster that spans multiple geographic locations, or sites, and has different replication and search factors for each site.

The KV store forms its own cluster within a SHC. The maximum number of SHC members KV store will form is 50. The KV store cluster is a subset of the SHC members that are responsible for replicating and storing the KV store data. The KV store cluster can have up to 50 members, but only 20 of them can be active at any given time. The other members are standby members that can take over if an active member fails. The KV store cluster cannot have more than 50 members, nor can it have an unlimited number of members. The KV store cluster cannot have 25 or 100 members, because these numbers are not multiples of 5, which is the minimum replication factor for the KV store cluster

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.

All of the options are possible causes of a crash in Splunk. According to the Splunk documentation1, incorrect ulimit settings can lead to file descriptor exhaustion, which can cause Splunk to crash or hang. Insufficient disk IOPS can also cause Splunk to crash or become unresponsive, as Splunk relies heavily on disk performance2. Insufficient memory can cause Splunk to run out of memory and crash, especially when running complex searches or handling large volumes of data3. Running out of disk space can cause Splunk to stop indexing data and crash, as Splunk needs enough disk space to store its data and logs4.

1: Configure ulimit settings for Splunk Enterprise 2: Troubleshoot Splunk performance issues 3: Troubleshoot memory usage 4: Troubleshoot disk space issues

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.

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

The guidance Splunk gives for estimating size on for syslog data is 50% of original data size. This divides between files in the index as follows: rawdata is 15%, tsidx is 35%. The rawdata is the compressed version of the original data, which typically takes about 15% of the original data size. The tsidx is the index file that contains the time-series metadata and the inverted index, which typically takes about 35% of the original data size. The total size of the rawdata and the tsidx is about 50% of the original data size. For more information, see [Estimate your storage requirements] in the Splunk documentation.

To ensure that high-velocity sources will not have forwarding delays to the indexers, the default limit for maxKBps in limits.conf should be increased. This parameter controls the maximum bandwidth that a forwarder can use to send data to the indexers. By default, it is set to 256 KBps, which may not be sufficient for high-volume data sources. Increasing this limit can reduce the forwarding latency and improve the performance of the forwarders. However, this should be done with caution, as it may affect the network bandwidth and the indexer load. Option B is the correct answer. Option A is incorrect because the sessionTimeout parameter in server.conf controls the duration of a TCP connection between a forwarder and an indexer, not the bandwidth limit. Option C is incorrect because the forceTimebasedAutoLB parameter in outputs.conf controls the frequency of load balancing among the indexers, not the bandwidth limit. Option D is incorrect because the phoneHomelntervallnSecs parameter in deploymentclient.conf controls the interval at which a forwarder contacts the deployment server, not the bandwidth limit12

1: https://docs.splunk.com/Documentation/Splunk/9.1.2/Admin/Limitsconf#limits.conf.spec  2: https://docs.splunk.com/Documentation/Splunk/9.1.2/Forwarding/Routeandfilterdatad#Set_the_maximum_bandwidth_usage_for_a_forwarder

The correct answer is C. Knowledge Object replication. This is a valid use case that a search head cluster addresses, as it ensures that all the search heads in the cluster have the same set of knowledge objects, such as saved searches, dashboards, reports, and alerts1. The search head cluster replicates the knowledge objects across the cluster members, and synchronizes any changes or updates1. This provides a consistent user experience and avoids data inconsistency or duplication1. The other options are not valid use cases that a search head cluster addresses. Option A, providing redundancy in the event a search peer fails, is not a use case for a search head cluster, but for an indexer cluster, which maintains multiple copies of the indexed data and can recover from indexer failures2. Option B, search affinity, is not a use case for a search head cluster, but for a multisite indexer cluster, which allows the search heads to preferentially search the data on the local site, rather than on a remote site3. Option D, increased Search Factor (SF), is not a use case for a search head cluster, but for an indexer cluster, which determines how many searchable copies of each bucket are maintained across the indexers4. Therefore, option C is the correct answer, and options A, B, and D are incorrect.

1: About search head clusters 2: About indexer clusters and index replication 3: Configure search affinity 4: Configure the search factor

 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

 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.

According to the Splunk documentation1, one of the benefits of search head clustering is the automatic replication of user knowledge objects, such as dashboards, reports, alerts, and tags. This ensures that all cluster members have the same set of knowledge objects and can serve the same search results to the users. The other options are false because:

• Allowing indexers to maintain multiple searchable copies of all data is a benefit of indexer clustering, not search head clustering2.
• Input settings are not synchronized between search heads, as search head clusters do not collect data from inputs. Data collection is done by forwarders or independent search heads3.
• Fewer network ports are not required to be opened between search heads, as search head clusters use several ports for communication and replication among the members4.

The _internal index contains license-related events, such as the license usage, the license quota, the license pool, the license stack, and the license violations. These events are logged by the license manager in the license_usage.log file, which is part of the _internal index. The _audit index contains audit events, such as user actions, configuration changes, and search activity. These events are logged by the audit trail in the audit.log file, which is part of the _audit index. The _license index does not exist in Splunk, as the license-related events are stored in the _internal index. The _introspection index contains platform instrumentation data, such as the resource usage, the disk objects, the search activity, and the data ingestion. These data are logged by the introspection generator in various log files, such as resource_usage.log, disk_objects.log, search_activity.log, and data_ingestion.log, which are part of the _introspection index. For more information, see About Splunk Enterprise logging and [About the _internal index] in the Splunk documentation.

According to the Splunk documentation1, in a search head cluster, the KV Store Primary is the same node as the search head cluster captain. The KV Store Primary is responsible for coordinating the replication of KV Store data across the cluster members. When any node receives a write request, the KV Store delegates the write to the KV Store Primary. The KV Store keeps the reads local, however. This ensures that the KV Store data is consistent and available across the cluster.

References:

• About the app key value store
• KV Store and search head clusters

When using ingest-based licensing, there are no Splunk roles that require the license manager to scale, because the license manager does not need to handle any additional load or complexity. Ingest-based licensing is a new licensing model that allows customers to pay for the data they ingest into Splunk, regardless of the data source, volume, or use case. Ingest-based licensing simplifies the licensing process and eliminates the need for license pools, license stacks, license slaves, and license warnings. The license manager is still responsible for enforcing the license quota and generating license usage reports, but it does not need to communicate with any other Splunk instances or monitor their license usage. Therefore, option C is the correct answer. Option A is incorrect because search peers are indexers that participate in a distributed search. They do not affect the license manager’s scalability, because they do not report their license usage to the license manager. Option B is incorrect because search heads are Splunk instances that coordinate searches across multiple indexers. They do not affect the license manager’s scalability, because they do not report their license usage to the license manager. Option D is incorrect because deployment clients are Splunk instances that receive configuration updates and apps from a deployment server. They do not affect the license manager’s scalability, because they do not report their license usage to the license manager12

1: https://docs.splunk.com/Documentation/Splunk/9.1.2/Admin/AboutSplunklicensing  2: https://docs.splunk.com/Documentation/Splunk/9.1.2/Admin/HowSplunklicensingworks

 The following statements are true about Splunk indexer clustering:

• All peer nodes must run exactly the same Splunk version. This is a requirement for indexer clustering, as different Splunk versions may have different data formats or features that are incompatible with each other. All peer nodes must run the same Splunk version as the master node and the search heads that connect to the cluster.
• The search head must run the same or a later Splunk version than the peer nodes. This is a recommendation for indexer clustering, as a newer Splunk version may have new features or bug fixes that improve the search functionality or performance. The search head should not run an older Splunk version than the peer nodes, as this may cause search errors or failures. The following statements are false about Splunk indexer clustering:
• The master node must run the same or a later Splunk version than the search heads. This is not a requirement or a recommendation for indexer clustering, as the master node does not participate in the search process. The master node should run the same Splunk version as the peer nodes, as this ensures the cluster compatibility and functionality.
• The peer nodes must run the same or a later Splunk version than the master node. This is not a requirement or a recommendation for indexer clustering, as the peer nodes do not coordinate the cluster activities. The peer nodes should run the same Splunk version as the master node, as this ensures the cluster compatibility and functionality. For more information, see [About indexer clusters and index replication] and [Upgrade an indexer cluster] 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.

 Search head clustering is a Splunk feature that allows a group of search heads to share configurations, apps, and knowledge objects, and to provide high availability and scalability for searching. Search head clustering has the following characteristics:

• A deployer is required. A deployer is a Splunk instance that distributes the configurations and apps to the members of the search head cluster. The deployer is not a member of the cluster, but a separate instance that communicates with the cluster master.
• At least three search heads are needed. A search head cluster must have at least three search heads to form a quorum and to ensure high availability. If the cluster has less than three search heads, it cannot function properly and will enter a degraded mode.
• The deployer must have sufficient CPU and network resources to process service requests and push configurations. The deployer is responsible for handling the requests from the cluster master and the cluster members, and for pushing the configurations and apps to the cluster members. Therefore, the deployer must have enough CPU and network resources to perform these tasks efficiently and reliably.

Search heads do not need to meet the high-performance reference server requirements, as this is not a mandatory condition for search head clustering. The high-performance reference server requirements are only recommended for optimal performance and scalability of Splunk deployments, but they are not enforced by Splunk.