Pass Guaranteed Quiz 2026 Realistic Verified Free SPLK-2002 Exam Dumps [Q15-Q37]

Pass Guaranteed Quiz 2026 Realistic Verified Free SPLK-2002 Exam Dumps

Free Splunk Enterprise Certified Architect SPLK-2002 Ultimate Study Guide (Updated 207 Questions)

NEW QUESTION # 15
Which index-time props.conf attributes impact indexing performance? (Select all that apply.)

• A. ANNOTATE_PUNCT
• B. SHOULD_LINEMERGE
• C. LINE_BREAKER
• D. REPORT

Answer: B,C

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

NEW QUESTION # 16
How many cluster managers are required for a multisite indexer cluster?

• A. Two for the entire cluster.
• B. One for each site.
• C. Two for each site.
• D. One for the entire cluster.

Answer: D

Explanation:
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

NEW QUESTION # 17
Which of the following would be the least helpful in troubleshooting contents of Splunk configuration files?

• A. diagnostic logs
• B. search.log
• C. crash logs
• D. btool output

Answer: C

Explanation:
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]

NEW QUESTION # 18
Which two sections can be expanded using the Search Job Inspector?

• A. Saved search history.
• B. Execution costs.
• C. Search job properties.
• D. Optimization suggestions.

Answer: C,D

Explanation:
Explanation
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

NEW QUESTION # 19
A new Splunk customer is using syslog to collect data from their network devices on port 514. What is the best practice for ingesting this data into Splunk?

• A. Configure syslog to write logs and use a Splunk forwarder to collect the logs.
• B. Configure syslog to send the data to multiple Splunk indexers.
• C. Use a Splunk indexer to collect a network input on port 514 directly.
• D. Use a Splunk forwarder to collect the input on port 514 and forward the data.

Answer: A

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

NEW QUESTION # 20
Which of the following is a good practice for a search head cluster deployer?

• A. The deployer must be used to distribute non-replicable configurations to search head cluster members.
• B. The deployer only distributes configurations to search head cluster members when they "phone home".
• C. The deployer only distributes configurations to search head cluster members with splunk apply shcluster-bundle.
• D. The deployer must distribute configurations to search head cluster members to be valid configurations.

Answer: A

Explanation:
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.

NEW QUESTION # 21
To expand the search head cluster by adding a new member, node2, what first step is required?

• A. splunk init shcluster-config -mgmt_uri https://node2:8089 -replication_port 9200 -secret supersecretkey
• B. splunk init shcluster-config -master_uri https://node2:8089 -replication_port 9200 -secret supersecretkey
• C. splunk add shcluster-member -new_member_uri https://node2:8089 -replication_port 9200 -secret supersecretkey
• D. splunk bootstrap shcluster-config -mgmt_uri https://node2:8089 -replication_port 9200 -secret supersecretkey

Answer: A

Explanation:
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

NEW QUESTION # 22
A Splunk user successfully extracted an ip address into a field called src_ip. Their colleague cannot see that field in their search results with events known to have src_ip. Which of the following may explain the problem? (Select all that apply.)

• A. The field was extracted as a private knowledge object.
• B. The colleague did not explicitly use the field in the search and the search was set to Fast Mode.
• C. The events are tagged as communicate, but are missing the network tag.
• D. The Typing Queue, which does regular expression replacements, is blocked.

Answer: A,B

Explanation:
Explanation
The following may explain the problem of why a colleague cannot see the src_ip field in their search results:
The field was extracted as a private knowledge object, and the colleague did not explicitly use the field in the search and the search was set to Fast Mode. A knowledge object is a Splunk entity that applies some knowledge or intelligence to the data, such as a field extraction, a lookup, or a macro. A knowledge object can have different permissions, such as private, app, or global. A private knowledge object is only visible to the user who created it, and it cannot be shared with other users. A field extraction is a type of knowledge object that extracts fields from the raw data at index time or search time. If a field extraction is created as a private knowledge object, then only the user who created it can see the extracted field in their search results. A search mode is a setting that determines how Splunk processes and displays the search results, such as Fast, Smart, or Verbose. Fast mode is the fastest and most efficient search mode, but it also limits the number of fields and events that are displayed. Fast mode only shows the default fields, such as _time, host, source, sourcetype, and
_raw, and any fields that are explicitly used in the search. If a field is not used in the search and it is not a default field, then it will not be shown in Fast mode. The events are tagged as communicate, but are missing the network tag, and the Typing Queue, which does regular expression replacements, is blocked, are not valid explanations for the problem. Tags are labels that can be applied to fields or field values to make them easier to search. Tags do not affect the visibility of fields, unless they are used as filters in the search. The Typing Queue is a component of the Splunk data pipeline that performs regular expression replacements on the data, such as replacing IP addresses with host names. The Typing Queue does not affect the field extraction process, unless it is configured to do so

NEW QUESTION # 23
A customer plans to have 20,000 Splunk-managed forwarders. What is a common step to ensure Splunk forwarder management performance is not impacted?

• A. Increase the phone-home interval for deployment clients.
• B. Use workload management to ensure client pools.
• C. Ensure that server classes have no more than 5,000 deployment clients.
• D. Reduce the polling interval for clients on the Deployment Server.

Answer: C

Explanation:
Splunk Deployment Server documentation clearly states that server class scalability is a primary factor in managing large numbers of forwarders. Each server class contains one or more apps and targets a set of deployment clients. Splunk recommends limiting the number of deployment clients per server class to maintain responsiveness and avoid configuration bottlenecks.
For large environments with tens of thousands of forwarders, Splunk explicitly advises splitting deployment clients across multiple server classes, typically in blocks of several thousand clients per class. This ensures that the Deployment Server can efficiently process configuration bundles, client check-ins, and app updates without delays or timeouts.
Increasing the phone-home interval (option A) may reduce check-in frequency but does not address server class scalability. Workload management (option B) is unrelated to Deployment Server operations. Reducing polling intervals (option C) actually increases load and is discouraged at scale.
Therefore, ensuring that server classes do not exceed approximately 5,000 deployment clients is the correct and recommended approach.
References:
Splunk Deployment Server Manual; Forwarder Management at Scale; Deployment Server Performance Best Practices.

NEW QUESTION # 24
Why should intermediate forwarders be avoided when possible?

• A. Because intermediate forwarders cannot be managed by a deployment server.
• B. To decrease mean time between failures.
• C. To eliminate potential performance bottlenecks.
• D. To minimize license usage and cost.

Answer: C

Explanation:
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."

NEW QUESTION # 25
(Which of the following is a benefit of using SmartStore?)

• A. Separating storage from compute.
• B. Cluster Manager is no longer required.
• C. Knowledge Object replication.
• D. Automatic selection of replication and search factors.

Answer: A

Explanation:
According to the Splunk SmartStore Architecture Guide, the primary benefit of SmartStore is the separation of storage from compute resources within an indexer cluster. SmartStore enables Splunk to decouple indexer storage (data at rest) from the compute layer (indexers that perform searches and indexing).
With SmartStore, active (hot/warm) data remains on local disk for fast access, while older, less frequently searched (remote) data is stored in an external object storage system such as Amazon S3, Google Cloud Storage, or on-premises S3-compatible storage. This separation reduces the storage footprint on indexers, allowing organizations to scale compute and storage independently.
This architecture improves cost efficiency and scalability by:
* Lowering on-premises storage costs using object storage for retention.
* Enabling dynamic scaling of indexers without impacting total data availability.
* Reducing replication overhead since SmartStore manages data objects efficiently.
SmartStore does not affect replication or search factors (Option A), does not handle Knowledge Object replication (Option C), and the Cluster Manager is still required (Option D) to coordinate cluster activities.
References (Splunk Enterprise Documentation):
* SmartStore Overview and Architecture Guide
* SmartStore Deployment and Configuration Manual
* Managing Storage and Compute Independence in Indexer Clusters
* Splunk Enterprise Capacity Planning - SmartStore Sizing Guidelines

NEW QUESTION # 26
Which of the following items are important sizing parameters when architecting a Splunk environment? (select all that apply)

• A. Existence of premium apps.
• B. Volume of incoming data.
• C. Number of concurrent users.
• D. Number of indexes.

Answer: A,B,C

Explanation:
* Number of concurrent users: This is an important factor because it affects the search performance and resource utilization of the Splunk environment. More users mean more concurrent searches, which require more CPU, memory, and disk I/O. The number of concurrent users also determines the search head capacity and the search head clustering configuration12
* Volume of incoming data: This is another crucial factor because it affects the indexing performance and storage requirements of the Splunk environment. More data means more indexing throughput, which requires more CPU, memory, and disk I/O. The volume of incoming data also determines the indexer capacity and the indexer clustering configuration13
* Existence of premium apps: This is a relevant factor because some premium apps, such as Splunk
* Enterprise Security and Splunk IT Service Intelligence, have additional requirements and recommendations for the Splunk environment. For example, Splunk Enterprise Security requires a dedicated search head cluster and a minimum of 12 CPU cores per search head. Splunk IT Service Intelligence requires a minimum of 16 CPU cores and 64 GB of RAM per search head45 References:
1: Splunk Validated Architectures 2: Search head capacity planning 3: Indexer capacity planning 4: Splunk Enterprise Security Hardware and Software Requirements 5: [Splunk IT Service Intelligence Hardware and Software Requirements]

NEW QUESTION # 27
What is the algorithm used to determine captaincy in a Splunk search head cluster?

• A. Rapt distributed consensus.
• B. Rift distributed consensus.
• C. Round-robin distribution consensus.
• D. Raft distributed consensus.

Answer: D

Explanation:
Explanation
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

NEW QUESTION # 28
Which server.confattribute should be added to the master node's server.conffile when
decommissioning a site in an indexer cluster?

• A. site_replication_factor
• B. site_search_factor
• C. site_mappings
• D. available_sites

Answer: C

Explanation:
Explanation/Reference: https://docs.splunk.com/Documentation/Splunk/7.3.2/Indexer/Decommissionasite

NEW QUESTION # 29
Which command is used for thawing the archive bucket?

• A. Splunk convert
• B. Splunk rebuild
• C. Splunk collect
• D. Splunk dbinspect

Answer: B

Explanation:
Explanation/Reference: https://answers.splunk.com/answers/337025/after-frozen-data-restore-thawed-data-not- working.html

NEW QUESTION # 30
Which Splunk cluster feature requires additional indexer storage?

• A. Search Head Clustering
• B. Indexer Acknowledgement
• C. Indexer Discovery
• D. Index Summarization

Answer: D

Explanation:
Comprehensive and Detailed Explanation (From Splunk Enterprise Documentation)Splunk's documentation on summary indexing and data-model acceleration clarifies that summary data is stored as additional indexed data on the indexers. Summary indexing produces new events-aggregations, rollups, scheduled search outputs-and stores them in summary indexes. Splunk explains that these summaries accumulate over time and require additional bucket storage, retention considerations, and sizing adjustments.
The documentation for accelerated data models further confirms that acceleration summaries are stored alongside raw data on indexers, increasing disk usage proportional to the acceleration workload. This makes summary indexing the only listed feature that strictly increases indexer storage demand.
In contrast, Search Head Clustering replicates configuration and knowledge objects across search heads-not on indexers. Indexer Discovery affects forwarder behavior, not storage. Indexer Acknowledgement controls data-delivery guarantees but does not create extra indexed content.
Therefore, only Index Summarization (summary indexing) directly increases indexer storage requirements.
References:Splunk Summary Indexing Documentation; Splunk Data Model Acceleration Guidelines; Splunk Storage and Capacity Planning Documentation.

NEW QUESTION # 31
Splunk configuration parameter settings can differ between multiple .conf files of the same name contained within different apps. Which of the following directories has the highest precedence?

• A. App default directories, in ASCII order.
• B. App local directories, in ASCII order.
• C. System default directory.
• D. System local directory.

Answer: D

Explanation:
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.

NEW QUESTION # 32
Which search head cluster component is responsible for pushing knowledge bundles to search peers, replicating configuration changes to search head cluster members, and scheduling jobs across the search head cluster?

• A. Deployer
• B. Master
• C. Deployment server
• D. Captain

Answer: D

Explanation:
Explanation
The captain is the search head cluster component that is responsible for pushing knowledge bundles to search peers, replicating configuration changes to search head cluster members, and scheduling jobs across the search head cluster. The captain is elected from among the search head cluster members and performs these tasks in addition to serving search requests. The master is the indexer cluster component that is responsible for managing the replication and availability of data across the peer nodes. The deployer is the standalone instance that is responsible for distributing apps and other configurations to the search head cluster members. The deployment server is the instance that is responsible for distributing apps and other configurations to the deployment clients, such as forwarders

NEW QUESTION # 33
(A customer creates a saved search that runs on a specific interval. Which internal Splunk log should be viewed to determine if the search ran recently?)

• A. metrics.log
• B. btool.log
• C. kvstore.log
• D. scheduler.log

Answer: D

Explanation:
According to Splunk's Search Scheduler and Job Management documentation, the scheduler.log file, located within the _internal index, records the execution of scheduled and saved searches. This log provides a detailed record of when each search is triggered, how long it runs, and its success or failure status.
Each time a scheduled search runs (for example, alerts, reports, or summary index searches), an entry is written to scheduler.log with fields such as:
* sid (search job ID)
* app (application context)
* savedsearch_name (name of the saved search)
* user (owner)
* status (success, skipped, or failed)
* run_time and result_count
By searching the _internal index for sourcetype=scheduler (or directly viewing scheduler.log), administrators can confirm whether a specific saved search executed as expected and diagnose skipped or delayed runs due to resource contention or concurrency limits.
Other internal logs serve different purposes:
* metrics.log records performance metrics.
* kvstore.log tracks KV Store operations.
* btool.log does not exist - btool outputs configuration data to the console, not a log file.
Hence, scheduler.log is the definitive and Splunk-documented source for validating scheduled search activity.
References (Splunk Enterprise Documentation):
* Saved Searches and Alerts - Scheduler Operation Details
* scheduler.log Reference - Monitoring Scheduled Search Execution
* Monitoring Console: Search Scheduler Health Dashboard
* Troubleshooting Skipped or Delayed Scheduled Searches

NEW QUESTION # 34
Which of the following are true statements about Splunk indexer clustering?

• A. The search head must run the same or a later Splunk version than the peer nodes.
• B. All peer nodes must run exactly the same Splunk version.
• C. The master node must run the same or a later Splunk version than search heads.
• D. The peer nodes must run the same or a later Splunk version than the master node.

Answer: A,B

Explanation:
Explanation
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.

NEW QUESTION # 35
What is the algorithm used to determine captaincy in a Splunk search head cluster?

• A. Rapt distributed consensus.
• B. Rift distributed consensus.
• C. Round-robin distribution consensus.
• D. Raft distributed consensus.

Answer: D

NEW QUESTION # 36
In the deployment planning process, when should a person identify who gets to see network data?

• A. Deployment schedule
• B. Data source inventory
• C. Topology diagramming
• D. Data policy definition

Answer: B

NEW QUESTION # 37
......

Splunk is a leading provider of software solutions for monitoring, analyzing, and visualizing machine-generated data. The company offers a range of products and services designed to help organizations harness the power of their data to gain valuable insights and make informed business decisions. One of the key offerings from Splunk is the SPLK-2002 (Splunk Enterprise Certified Architect) Certification Exam.

 

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