SPLK-2002 Exam Dumps - Splunk Enterprise Certified Architect

According to the Splunk blog1, the Universal Forwarder is ideal for collecting data from high-velocity data sources, such as a syslog server, due to its smaller footprint and faster performance. The Universal Forwarder performs minimal processing and sends raw or unparsed data to the indexers, reducing the network traffic and the load on the forwarders. The other options are false because:

• When most of the data requires masking, a Heavy Forwarder is needed, as it can perform advanced filtering and data transformation before forwarding the data2.
• When data comes directly from a database server, a Heavy Forwarder is needed, as it can run modular inputs such as DB Connect to collect data from various databases2.
• When a modular input is needed, a Heavy Forwarder is needed, as the Universal Forwarder does not include a bundled version of Python, which is required for most modular inputs2.

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.

According to the Splunk documentation1, the Splunk deployment topology is the part of the deployment plan that is vital prior to installing Splunk indexer clusters and search head clusters. The deployment topology defines the number and type of Splunk components, such as forwarders, indexers, search heads, and deployers, that you need to install and configure for your distributed deployment. The deployment topology also determines the network and hardware requirements, the data flow and replication, the high availability and disaster recovery options, and the security and performance considerations for your deployment2. The other options are false because:

• Data source inventory is not the part of the deployment plan that is vital prior to installing Splunk indexer clusters and search head clusters, as it is a preliminary step that helps you identify the types, formats, locations, and volumes of data that you want to collect and analyze with Splunk. Data source inventory is important for planning your data ingestion and retention strategies, but it does not directly affect the installation and configuration of Splunk components3.
• Data policy definitions are not the part of the deployment plan that is vital prior to installing Splunk indexer clusters and search head clusters, as they are the rules and guidelines that govern how you handle, store, and protect your data. Data policy definitions are important for ensuring data quality, security, and compliance, but they do not directly affect the installation and configuration of Splunk components4.
• Education and training plans are not the part of the deployment plan that is vital prior to installing Splunk indexer clusters and search head clusters, as they are the learning resources and programs that help you and your team acquire the skills and knowledge to use Splunk effectively. Education and training plans are important for enhancing your Splunk proficiency and productivity, but they do not directly affect the installation and configuration of Splunk components5.

According to the Splunk documentation1, the CHARSET setting in props.conf specifies the character set encoding of the source data. This setting has the least impact on indexing performance, as it only affects how Splunk interprets the bytes of the data, not how it processes or transforms the data. The other options are false because:

• The SHOULD_LINEMERGE setting in props.conf determines whether Splunk breaks events based on timestamps or newlines. This setting has a significant impact on indexing performance, as it affects how Splunk parses the data and identifies the boundaries of the events2.
• The TRUNCATE setting in props.conf specifies the maximum number of characters that Splunk indexes from a single line of a file. This setting has a moderate impact on indexing performance, as it affects how much data Splunk reads and writes to the index3.
• The TIME_PREFIX setting in props.conf specifies the prefix that directly precedes the timestamp in the event data. This setting has a moderate impact on indexing performance, as it affects how Splunk extracts the timestamp and assigns it to the event

As a best practice, the internal licensing logs should be stored on the license server. The license server is a Splunk instance that manages the distribution and enforcement of licenses in a Splunk deployment. The license server generates internal licensing logs that contain information about the license usage, violations, warnings, and pools. The internal licensing logs should be stored on the license server itself, because they are relevant to the license server’s role and function. Storing the internal licensing logs on the license server also simplifies the license monitoring and troubleshooting process. The internal licensing logs should not be stored on the indexing layer, the deployment layer, or the search head layer, because they are not related to the roles and functions of these layers. Storing the internal licensing logs on these layers would also increase the network traffic and disk space consumption

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

• disk_objects.log. This log contains information about the disk objects that Splunk creates and manages, such as buckets, indexes, and files. This log can help monitor the disk space usage and the bucket lifecycle.
• resource_usage.log. This log contains information about the resource usage of Splunk processes, such as CPU, memory, disk, and network. This log can help monitor the Splunk performance and identify any resource bottlenecks. The following logs are not included in the _introspection index, but rather in the _internal index, which contains data that Splunk generates for internal logging:
• audit.log. This log contains information about the audit events that Splunk records, such as user actions, configuration changes, and search activity. This log can help audit the Splunk operations and security.
• metrics.log. This log contains information about the performance metrics that Splunk collects, such as data throughput, data latency, search concurrency, and search duration. This log can help measure the Splunk performance and efficiency. For more information, see About Splunk Enterprise logging and [About the _introspection index] in the Splunk documentation.

The TailingProcessor channel in the splunkd.log file would help troubleshoot this issue, because it contains information about the files that Splunk monitors and indexes, such as the file path, size, modification time, and CRC checksum. It also logs any errors or warnings that occur during the file monitoring process, such as permission issues, file rotation, or file truncation. The TailingProcessor channel can help identify if Splunk is reading the new data from the monitor input file or not, and what might be causing the problem. Option B is the correct answer. Option A is incorrect because the ModularInputs channel logs information about the modular inputs that Splunk uses to collect data from external sources, such as scripts, APIs, or custom applications. It does not log information about the monitor input file. Option C is incorrect because the ChunkedLBProcessor channel logs information about the load balancing process that Splunk uses to distribute data among multiple indexers. It does not log information about the monitor input file. Option D is incorrect because the ArchiveProcessor channel logs information about the archive process that Splunk uses to move data from the hot/warm buckets to the cold/frozen buckets. It does not log information about the monitor input file12

1: https://docs.splunk.com/Documentation/Splunk/9.1.2/Troubleshooting/WhatSplunklogsaboutitself#splunkd.log  2: https://docs.splunk.com/Documentation/Splunk/9.1.2/Troubleshooting/Didyouloseyourfishbucket#Check_the_splunkd.log_file

The correct configuration to meet the customer’s requirements is site_replication_factor = origin:1, site4:1, total:5. This means that each bucket will have one copy at the origin site, one copy at the disaster recovery site (site4), and three copies at any other sites. The total number of copies will be five, as required by the customer. The site_replication_factor determines how many copies of each bucket are stored across the sites in a multisite indexer cluster1. The site_search_factor determines how many copies of each bucket are searchable across the sites in a multisite indexer cluster2. Therefore, option B is the correct answer, and options A, C, and D are incorrect.

1: Configure the site replication factor 2: Configure the site search factor

A deployment plan should include business continuity and disaster recovery plans, current logging details and data source inventory, and current and future topology diagrams of the IT environment. These elements are essential for planning, designing, and implementing a Splunk deployment that meets the business and technical requirements. A comprehensive list of stakeholders, either direct or indirect, is not part of the deployment plan, but rather part of the project charter. For more information, see Deployment planning in the Splunk documentation.

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

The correct topology to ensure a scalable and performant deployment for the customer’s use case is two search head clusters, one for ITSI and one for ES. This configuration provides high availability, load balancing, and isolation for each Splunk app. According to the Splunk documentation1, ITSI and ES should not be installed on the same search head or search head cluster, as they have different requirements and may interfere with each other. Having two separate search head clusters allows each app to have its own dedicated resources and configuration, and avoids potential conflicts and performance issues1. The other options are not recommended, as they either have only one search head or search head cluster, which reduces the availability and scalability of the deployment, or they have both ITSI and ES installed on the same search head or search head cluster, which violates the best practices and may cause problems. Therefore, option B is the correct answer, and options A, C, and D are incorrect.

1: Splunk IT Service Intelligence and Splunk Enterprise Security compatibility

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.

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.

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

A single-site indexer cluster is a group of Splunk Enterprise instances that index and replicate data across the cluster1. A bucket is a directory that contains indexed data, along with metadata and other information2. A replication factor is the number of copies of each bucket that the cluster maintains1. A search factor is the number of searchable copies of each bucket that the cluster maintains1. A searchable copy is a copy that contains both the raw data and the index files3. A search head is a Splunk Enterprise instance that coordinates the search activities across the peer nodes1.

Option D is the correct answer because it reflects the definitions of replication factor and search factor. The cluster will ensure that there are at least three copies of each bucket, one on each peer node, to satisfy the replication factor of 3. The cluster will also ensure that there are at least two searchable copies of each bucket, one primary and one searchable, to satisfy the search factor of 2. The primary copy is the one that the search head uses to run searches, and the searchable copy is the one that can be promoted to primary if the original primary copy becomes unavailable3.

Option A is incorrect because it confuses the replication factor and the search factor. The cluster will ensure there are at least three copies of each bucket, not two, to meet the replication factor of 3. The cluster will ensure there are at least two copies of searchable metadata, not three, to meet the search factor of 2.

Option B is incorrect because it uses the wrong terms. The cluster will ensure there are at least, not at most, three copies of each bucket, to meet the replication factor of 3. The cluster will ensure there are at least, not at most, two copies of searchable metadata, to meet the search factor of 2.

Option C is incorrect because it has nothing to do with the replication factor or the search factor. The cluster does not limit the number of search heads that can access the bucket at the same time. The search head can search across multiple clusters, and the cluster can serve multiple search heads1.

1: The basics of indexer cluster architecture - Splunk Documentation 2: About buckets - Splunk Documentation 3: Search factor - Splunk Documentation

 The following statements are true regarding Splunk Enterprise performance:

• Adding search peers increases the search throughput as search load increases. This is because adding more search peers distributes the search workload across more indexers, which reduces the load on each indexer and improves the search speed and concurrency.
• Adding search heads provides additional CPU cores to run more concurrent searches. This is because adding more search heads increases the number of search processes that can run in parallel, which improves the search performance and scalability. The following statements are false regarding Splunk Enterprise performance:
• Adding search peers does not increase the maximum size of search results. The maximum size of search results is determined by the maxresultrows setting in the limits.conf file, which is independent of the number of search peers.
• Adding RAM to an existing search head does not provide additional search capacity. The search capacity of a search head is determined by the number of CPU cores, not the amount of RAM. Adding RAM to a search head may improve the search performance, but not the search capacity. For more information, see Splunk Enterprise performance in the Splunk documentation.

The splunk edit licenser-localslave command is used to convert a Splunk instance to a license slave. This command will configure the Splunk instance to contact a license master and receive a license from it. This command should be used when the Splunk instance is part of a distributed deployment and needs to share a license pool with other instances. The splunk add licenses command is used to add a license to a Splunk instance, not to convert it to a license slave. The splunk list licenser-slaves command is used to list the license slaves that are connected to a license master, not to convert a Splunk instance to a license slave. The splunk list licenser-localslave command is used to list the license master that a license slave is connected to, not to convert a Splunk instance to a license slave. For more information, see Configure license slaves in the Splunk documentation.

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

According to the Splunk documentation1, a bucket within a clustered index contains two key types of files: the raw data in compressed form (rawdata) and the indexes that point to the raw data (tsidx files). A bucket can be either replicated or searchable, depending on whether it has both types of files or only the rawdata file. A replicated bucket is a bucket that has been copied from one peer node to another for the purpose of data replication. A searchable bucket is a bucket that has both the rawdata and the tsidx files, and can be searched by the search heads. The types of files that exist in a bucket within a clustered index are:

• Inside a searchable bucket, there is tsidx and rawdata. This is true because a searchable bucket contains both the data and the index files, and can be searched by the search heads1.
• Inside a replicated bucket, there is both tsidx and rawdata. This is true because a replicated bucket can also be a searchable bucket, if it has both the data and the index files. However, not all replicated buckets are searchable, as some of them might only have the rawdata file, depending on the replication factor and the search factor settings1.

The other options are false because:

• Inside a replicated bucket, there is only rawdata. This is false because a replicated bucket can also have the tsidx file, if it is a searchable bucket. A replicated bucket only has the rawdata file if it is a non-searchable bucket, which means that it cannot be searched by the search heads until it gets the tsidx file from another peer node1.
• Inside a searchable bucket, there is only tsidx. This is false because a searchable bucket always has both the tsidx and the rawdata files, as they are both required for searching the data. A searchable bucket cannot exist without the rawdata file, as it contains the actual data that the tsidx file points to1.

 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.

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

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

The site_mappings attribute should be added to the master node’s server.conf file when decommissioning a site in an indexer cluster. The site_mappings attribute is used to specify how the master node should reassign the buckets from the decommissioned site to the remaining sites. The site_mappings attribute is a comma-separated list of site pairs, where the first site is the decommissioned site and the second site is the destination site. For example, site_mappings = site1:site2,site3:site4 means that the buckets from site1 will be moved to site2, and the buckets from site3 will be moved to site4. The available_sites attribute is used to specify which sites are currently available in the cluster, and it is automatically updated by the master node. The site_search_factor and site_replication_factor attributes are used to specify the number of searchable and replicated copies of each bucket for each site, and they are not affected by the decommissioning process

 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.

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.

 The following is a good practice for a search head cluster deployer: The deployer must be used to distribute non-replicable configurations to search head cluster members. Non-replicable configurations are the configurations that are not replicated by the search factor, such as the apps and the server.conf settings. The deployer is the Splunk server role that distributes these configurations to the search head cluster members, ensuring that they have the same configuration. The deployer does not only distribute configurations to search head cluster members when they “phone home”, as this would cause configuration inconsistencies and delays. The deployer does not distribute configurations to search head cluster members to be valid configurations, as this implies that the configurations are invalid without the deployer. The deployer does not only distribute configurations to search head cluster members with splunk apply shcluster-bundle, as this would require manual intervention by the administrator. For more information, see Use the deployer to distribute apps and configuration updates in the Splunk documentation.

 The algorithm used to determine captaincy in a Splunk search head cluster is Raft distributed consensus. Raft is a consensus algorithm that is used to elect a leader among a group of nodes in a distributed system. In a Splunk search head cluster, Raft is used to elect a captain among the cluster members. The captain is the cluster member that is responsible for coordinating the search activities, replicating the configurations and apps, and pushing the knowledge bundles to the search peers. The captain is dynamically elected based on various criteria, such as CPU load, network latency, and search load. The captain can change over time, depending on the availability and performance of the cluster members. Rapt, Rift, and Round-robin are not valid algorithms for determining captaincy in a Splunk search head cluster

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

Search is not locked out when a customer has installed a 500GB Enterprise license and a 300GB, no enforcement license on the same license master. The no enforcement license allows the customer to exceed the license quota without locking search, but violations are still recorded. The customer can ingest up to 800GB of data per day without violating the license, but if they ingest more than that, they will incur a violation. However, the violation will not lock search, as the no enforcement license overrides the enforcement policy of the Enterprise license. For more information, see [No enforcement licenses] and [License violations] in the Splunk documentation.

• 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.

References:

1: inputs.conf - Splunk Documentation 2: How the Splunk platform handles log file rotation 3: Solved: Configure CRC salt - Splunk Community

Before deploying Splunk, it is important to gather some information about the current environment, such as:

• Overall goals for the deployment: This includes the business objectives, the use cases, the expected outcomes, and the success criteria for the Splunk deployment. This information helps to define the scope, the requirements, the design, and the validation of the Splunk solution1.
• Key users: This includes the roles, the responsibilities, the expectations, and the needs of the different types of users who will interact with the Splunk deployment, such as administrators, analysts, developers, and end users. This information helps to determine the user access, the user experience, the user training, and the user feedback for the Splunk solution1.
• Data sources: This includes the types, the formats, the volumes, the locations, and the characteristics of the data that will be ingested, indexed, and searched by the Splunk deployment. This information helps to estimate the data throughput, the data retention, the data quality, and the data analysis for the Splunk solution1.

Option B, C, and D are the correct answers because they reflect the essential information that is needed before deploying Splunk. Option A is incorrect because the list of vendors for network devices is not a relevant information for the Splunk deployment. The network devices may be part of the data sources, but the vendors are not important for the Splunk solution.

References:

1: Splunk Validated Architectures

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 __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.

Intermediate forwarders are forwarders that receive data from other forwarders and then send that data to indexers. They can be useful in some scenarios, such as when network bandwidth or security constraints prevent direct forwarding to indexers, or when data needs to be routed, cloned, or modified in transit. However, intermediate forwarders also introduce additional complexity and overhead to the data pipeline, which can affect the performance and reliability of data ingestion. Therefore, intermediate forwarders should be avoided when possible, and used only when there is a clear benefit or requirement for them. Some of the drawbacks of intermediate forwarders are:

• They increase the number of hops and connections in the data flow, which can introduce latency and increase the risk of data loss or corruption.
• They consume more resources on the hosts where they run, such as CPU, memory, disk, and network bandwidth, which can affect the performance of other applications or processes on those hosts.
• They require additional configuration and maintenance, such as setting up inputs, outputs, load balancing, security, monitoring, and troubleshooting.
• They can create data duplication or inconsistency if they are not configured properly, such as when using cloning or routing rules.

Some of the references that support this answer are:

• Configure an intermediate forwarder, which states: “Intermediate forwarding is where a forwarder receives data from one or more forwarders and then sends that data on to another indexer. This kind of setup is useful when, for example, you have many hosts in different geographical regions and you want to send data from those forwarders to a central host in that region before forwarding the data to an indexer. All forwarder types can act as an intermediate forwarder. However, this adds complexity to your deployment and can affect performance, so use it only when necessary.”
• Intermediate data routing using universal and heavy forwarders, which states: “This document outlines a variety of Splunk options for routing data that address both technical and business requirements. Overall benefits Using splunkd intermediate data routing offers the following overall benefits: … The routing strategies described in this document enable flexibility for reliably processing data at scale. Intermediate routing enables better security in event-level data as well as in transit. The following is a list of use cases and enablers for splunkd intermediate data routing: … Limitations splunkd intermediate data routing has the following limitations: … Increased complexity and resource consumption. splunkd intermediate data routing adds complexity to the data pipeline and consumes resources on the hosts where it runs. This can affect the performance and reliability of data ingestion and other applications or processes on those hosts. Therefore, intermediate routing should be avoided when possible, and used only when there is a clear benefit or requirement for it.”
• Use forwarders to get data into Splunk Enterprise, which states: “The forwarders take the Apache data and send it to your Splunk Enterprise deployment for indexing, which consolidates, stores, and makes the data available for searching. Because of their reduced resource footprint, forwarders have a minimal performance impact on the Apache servers. … Note: You can also configure a forwarder to send data to another forwarder, which then sends the data to the indexer. This is called intermediate forwarding. However, this adds complexity to your deployment and can affect performance, so use it only when necessary.”

The correct answer is C. 100 GB per day. This is the expected minimum amount of storage required for data across an indexer cluster with the given input and parameters. The storage requirement can be calculated by adding the raw data size and the index files size, and then multiplying by the Replication Factor and the Search Factor1. In this case, the calculation is:

(15 GB + 35 GB) x 2 x 2 = 100 GB

The Replication Factor is the number of copies of each bucket that the cluster maintains across the set of peer nodes2. The Search Factor is the number of searchable copies of each bucket that the cluster maintains across the set of peer nodes3. Both factors affect the storage requirement, as they determine how many copies of the data are stored and searchable on the indexers. The other options are not correct, as they do not match the result of the calculation. Therefore, option C is the correct answer, and options A, B, and D are incorrect.

1: Estimate storage requirements 2: About indexer clusters and index replication 3: Configure the search factor

 The parallelIngestionPipelines setting can be adjusted on the indexers and forwarders to improve Splunk performance. The parallelIngestionPipelines setting determines how many concurrent data pipelines are used to process the incoming data. Increasing the parallelIngestionPipelines setting can improve the data ingestion and indexing throughput, especially for high-volume data sources. The parallelIngestionPipelines setting can be adjusted on the indexers and forwarders by editing the limits.conf file. The parallelIngestionPipelines setting cannot be adjusted on the search head or the cluster master, because they are not involved in the data ingestion and indexing process.

According to the Splunk documentation1, multi-site clustering is an indexer cluster that spans multiple physical sites, such as data centers. Each site has its own set of peer nodes and search heads. Each site also obeys site-specific replication and search factor rules. The use cases that are made possible by multi-site clustering are:

• Greatly reduce WAN traffic by preferentially searching assigned site (search affinity). This means that if you configure each site so that it has both a search head and a full set of searchable data, the search head on each site will limit its searches to local peer nodes. This eliminates any need, under normal conditions, for search heads to access data on other sites, greatly reducing network traffic between sites2.
• Seamlessly route searches to a redundant site in case of a site failure. This means that by storing copies of your data at multiple locations, you maintain access to the data if a disaster strikes at one location. Multisite clusters provide site failover capability. If a site goes down, indexing and searching can continue on the remaining sites, without interruption or loss of data2.

The other options are false because:

• Use blockchain technology to audit search activity from geographically dispersed data centers. This is not a use case of multi-site clustering, as Splunk does not use blockchain technology to audit search activity. Splunk uses its own internal logs and metrics to monitor and audit search activity3.
• Enable a forwarder to send data to multiple indexers. This is not a use case of multi-site clustering, as forwarders can send data to multiple indexers regardless of whether they are in a single-site or multi-site cluster. This is a basic feature of forwarders that allows load balancing and high availability of data ingestion4.

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.

The following statements describe licensing in a clustered Splunk deployment: Free licenses do not support clustering, and replicated data does not count against licensing. Free licenses are limited to 500 MB of daily indexing volume and do not allow distributed searching or clustering. To enable clustering, a license with a higher volume limit and distributed features is required. Replicated data is data that is copied from one peer node to another for the purpose of high availability and load balancing. Replicated data does not count against licensing, because it is not new data that is ingested by Splunk. Only the original data that is indexed by the peer nodes counts against licensing. Each cluster member does not require its own clustering license, because clustering licenses are shared among the cluster members. Cluster members must share the same license pool and license master, because the license master is responsible for distributing licenses to the cluster members and enforcing the license limits

According to the Splunk documentation1, any search head in the cluster can update the KV store collection. The KV store collection is replicated across all the cluster members, and any write operation is delegated to the KV store captain, who then synchronizes the changes with the other members. The KV store primary search head is not a valid term, as there is no such role in a search head cluster. The other options are false because:

• The search head cluster captain is not the only node that can update the KV store collection, as any member can initiate a write operation1.
• Any search head except the captain can also update the KV store collection, as the write operation will be delegated to the captain1.

 The tailing_processor.log file would be the best place to search if you suspect there is a problem interpreting a regular expression in a monitor stanza. This log file contains information about how Splunk monitors files and directories, including any errors or warnings related to parsing the monitor stanza. The splunkd.log file contains general information about the Splunk daemon, but it may not have the specific details about the monitor stanza. The btool.log file contains information about the configuration files, but it does not log the runtime behavior of the monitor stanza. The metrics.log file contains information about the performance metrics of Splunk, but it does not log the event breaking issues. For more information, see About Splunk Enterprise logging in the Splunk documentation.

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 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

Searching for closed_txn=0 in this search filters results to situations where Splunk was started, but not stopped. This means that the transaction was not completed, and Splunk crashed before it could finish the pipelines. The closed_txn field is added by the transaction command, and it indicates whether the transaction was closed by an event that matches the endswith condition1. A value of 0 means that the transaction was not closed, and a value of 1 means that the transaction was closed1. Therefore, option D is the correct answer, and options A, B, and C are incorrect.

1: transaction command overview

A lookup table is a file that contains a list of values that can be used to enrich or modify the data during search time1. Lookup tables can be stored in CSV files or in the KV Store1. Troubleshooting lookup tables involves identifying and resolving issues that prevent the lookup tables from being accessed, updated, or applied correctly by the Splunk searches. Some of the tools and methods that can help with troubleshooting lookup tables are:

• web_access.log: This is a file that contains information about the HTTP requests and responses that occur between the Splunk web server and the clients2. This file can help troubleshoot issues related to lookup table permissions, availability, and errors, such as 404 Not Found, 403 Forbidden, or 500 Internal Server Error34.
• 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 on5. This tool can help troubleshoot issues related to lookup table definitions, locations, and precedence, as well as identify the source of a configuration setting6.
• 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 performance. This file can help troubleshoot issues related to lookup table commands, arguments, fields, and outputs, such as lookup, inputlookup, outputlookup, lookup_editor, and so on .

Option B is the correct answer because web_access.log is the best place to start troubleshooting lookup table issues, as it can provide the most relevant and immediate information about the lookup table access and status. Option A is incorrect because btool output is not a log file, but a command-line tool. Option C is incorrect because health.log is a file that contains information about the health of the Splunk components, such as the indexer cluster, the search head cluster, the license master, and the deployment server. This file can help troubleshoot issues related to Splunk deployment health, but not necessarily related to lookup tables. Option D is incorrect because configuration_change.log is a file that contains information about the changes made to the Splunk configuration files, such as the user, the time, the file, and the action. This file can help troubleshoot issues related to Splunk configuration changes, but not necessarily related to lookup tables.

References:

1: About lookups - Splunk Documentation 2: web_access.log - Splunk Documentation 3: Troubleshoot lookups to the Splunk Enterprise KV Store 4: Troubleshoot lookups in Splunk Enterprise Security - Splunk Documentation 5: Use btool to troubleshoot configurations - Splunk Documentation 6: Troubleshoot configuration issues - Splunk Documentation : Use the search.log file - Splunk Documentation : Troubleshoot search-time field extraction - Splunk Documentation : [Troubleshoot lookups - Splunk Documentation] : [health.log - Splunk Documentation] : [configuration_change.log - Splunk Documentation]