SPLK-3003 Splunk Core Certified Consultant Free Practice Exam Questions (2025 Updated)

Subsearches have a default result output limit of 10000. This means that a subsearch can return up to 10000 results to the main search. If the subsearch returns more than 10000 results, the main search will only use the first 10000 results and ignore the rest. This limit can be changed by using the maxout parameter of the format command or by setting the max_subsearch_results option in limits.conf. References:

https://docs.splunk.com/Documentation/Splunk/9.1.1/Search/Aboutsubsearches 1

https://docs.splunk.com/Documentation/Splunk/9.1.1/SearchReference/Format 2

https://docs.splunk.com/Documentation/Splunk/9.1.1/Admin/Limitsconf 3

To set up the HTTP Event Collector (HEC), each HEC input entry must contain a valid token. A token is a string of alphanumeric characters that acts as an identifier and an authentication code for the HEC input. You can generate a token when you create a new HEC input or use an existing token for multiple inputs. A token is required for sending data to HEC and for managing the HEC input settings. References :=

Set up and use HTTP Event Collector in Splunk Web

Configure the Splunk HTTP Event Collector for use with additional data sources

The pass4SymmKey is a security key that lets various components of Splunk Enterprise authenticate securely with one another. The pass4SymmKey for an indexer cluster is configured in the server.conf file under the [clustering] stanza. To find the pass4SymmKey of an indexer cluster, the most efficient command is C, $SPLUNK_HOME/bin/splunk btool server list clustering | grep pass4SymmKey. This command uses btool to list the effective settings for the clustering service from the server.conf file and filters the output by grep to show only the pass4SymmKey value. The other commands are either incorrect or less efficient. References :=

Secure Splunk Enterprise services with pass4SymmKey

Use btool to troubleshoot configurations

 Splunk does not support overlapping usernames between internal Splunk authentication and LDAP. If a username exists in both $SPLUNK_HOME/etc/passwd and LDAP, Splunk will try to use the internal Splunk authentication first, as explained in the previous question. However, if the user tries to change their password or edit their account settings, Splunk will error with a message like "Cannot edit user: User exists in multiple realms". This is because Splunk cannot determine which authentication scheme to use for these actions. Therefore, it is recommended to avoid overlapping usernames between internal Splunk authentication and LDAP. References:

https://community.splunk.com/t5/Security/Cannot-edit-user-User-exists-in-multiple-realms/m-p/10392 3

https://community.splunk.com/t5/Security/Cannot-edit-user-User-exists-in-multiple-realms/m-p/10392

This is because the index time parsing occurs on the Splunk instance that performs the parsing pipeline, which is the heavy forwarder in this case. The parsing pipeline is the process of breaking the incoming data into events, extracting default fields and timestamps, and applying transforms. The heavy forwarder is a type of Splunk forwarder that can perform the parsing pipeline on the data before forwarding it to the indexer. The universal forwarder is a type of Splunk forwarder that does not perform the parsing pipeline, but only forwards the raw data to another Splunk instance. The indexer is a Splunk instance that receives the parsed data from the heavy forwarder and performs the indexing pipeline, which is the process of compressing, encrypting, and writing the data to disk. The search head is a Splunk instance that coordinates searches across multiple indexers and displays the results to the user.

The other options are incorrect because they are not the Splunk instances that perform the index time parsing in this scenario. Option A is incorrect because the indexer does not perform the index time parsing, but only receives the parsed data from the heavy forwarder. Option B is incorrect because the universal forwarder does not perform the index time parsing, but only forwards the raw data to the heavy forwarder. Option C is incorrect because the search head does not perform the index time parsing, but only coordinates searches across multiple indexers. References:

Splunk Core Consultant knowledge source documents or study guide: https://www.splunk.com/en_us/resources/splunk-certification-exam-study-guide.html

Splunk Test Blueprint Consultant: https://www.splunk.com/en_us/pdfs/training/splunk-test-blueprint-consultant.pdf

How indexing works1

About forwarding and receiving data2

About Splunk Enterprise instances3

The Monitoring Console (MC) health check configuration items are stored in a configuration file called checklist.conf. This file contains the definitions of the health check items, such as the search, description, severity, tags, and categories. You can modify this file to customize the existing health check items or create new ones. You can also download new health check items from the Splunk Health Assistant Add-on on splunkbase. References:

: Splunk Documentation: Monitoring Console: Access and customize health check1

: Splunk Documentation: Monitoring Console: Customize health check items2

When Splunk indexes events, it extracts metadata fields such as host, source, and source type from the raw data. These fields are used to identify and categorize the events, and to enable efficient searching and filtering. Splunk also assigns a unique identifier (_cd) and a timestamp (_time) to each event. Splunk does not extract the top 10 fields, perform parsing, merging, and typing processes on universal forwarders, or create report acceleration summaries during indexing. These are separate processes that occur either before or after indexing. Therefore, the correct answer is B. Extracts metadata fields such as host, source, source type. References:

Splunk Core Certified Consultant Test Blueprint

Splunk Documentation: How Splunk Enterprise indexes data

Splunk Documentation: About default fields

 The indexer cluster is classed as ‘Indexing Ready’ when it has enough indexers to meet the replication factor. In this case, the replication factor is 2, which means that each bucket of data must have two copies across the indexers. Therefore, the cluster is ready to ingest new data after Step 6, when Indexer 2 joins the cluster and replicates the data from Indexer 1. Indexer 3 is not required for the cluster to be indexing ready, although it can provide additional redundancy and search performance. References :=

Indexer cluster configuration overview

The basics of indexer cluster architecture

In a single indexer cluster, the best practice is to install the Monitoring Console (MC) on the cluster master node. This is because the cluster master node has access to all the information about the cluster state, such as the bucket status, the peer status, the search head status, and the replication and search factors. The MC can use this information to monitor the health and performance of the cluster and alert on any issues or anomalies. The MC can also run distributed searches across all the peer nodes and collect metrics and logs from them.

The other options are incorrect because they are not recommended locations for installing the MC in a single indexer cluster. Option A is incorrect because the deployer should not share with the master cluster, as this can cause conflicts and errors in applying configuration bundles to the cluster. Option B is incorrect because the license master is not a good candidate for hosting the MC, as it does not have direct access to the cluster information and it might have a high load from managing license usage for many clients. Option D is incorrect because the production search head is not a good candidate for hosting the MC, as it might have a high load from serving user searches and dashboards, and it might not be able to run distributed searches across all the peer nodes if it is not part of the cluster. References:

Splunk Core Consultant knowledge source documents or study guide: https://www.splunk.com/en_us/resources/splunk-certification-exam-study-guide.html

Splunk Test Blueprint Consultant: https://www.splunk.com/en_us/pdfs/training/splunk-test-blueprint-consultant.pdf

About indexer clusters and index replication1

Monitoring Console: Where to install2

The parsing pipeline contains the regex replacement processor that would be called upon to run event masking routines on events as they are ingested. Event masking is a process of replacing sensitive data in events with a placeholder value, such as “XXXXX”. This is done by using the SEDCMD attribute in props.conf, which specifies a regular expression to apply to the raw data of an event. The regex replacement processor is responsible for executing the SEDCMD attribute on the events before they are indexed. References:

[Splunk Certification Exam Study Guide], page 17

[Splunk Documentation: Configure event processing]

[Splunk Documentation: Anonymize data]

 The search head that the user has logged onto will proxy the required artifact over to itself from a search head that currently holds a copy. A copy will also be replicated from that search head permanently, so it is available for future use. This is how the search head cluster handles search artifacts and ensures that they are accessible to all cluster members, regardless of the replication factor. The replication factor only determines the number of copies of each search artifact that the cluster maintains, not the availability of the search results to the users. The other options are incorrect because they imply that the user will not be able to view the search results or that some manual intervention is required to synchronize the artifacts across the search heads, which is not true. References:

: Splunk Documentation: Monitoring Console: Choose the replication factor for the search head cluster1

: Splunk Documentation: Monitoring Console: How the cluster handles search artifacts2

Search Job Inspector provides statistics to show how much time and the number of events each indexer has processed. This can help validate and understand the customer’s concerns about the search performance and identify any bottlenecks or issues with the indexer cluster configuration. For example, the Search Job Inspector can show if some indexers are overloaded or underutilized, if there are network latency or bandwidth problems, or if there are errors or warnings during the search execution. The Search Job Inspector can also show how much time each search command takes and how many events are processed by each command. References:

https://docs.splunk.com/Documentation/Splunk/9.1.1/Search/ViewsearchjobpropertieswiththeJobInspector 4

https://docs.splunk.com/Documentation/Splunk/9.1.1/Search/Troubleshootingsearchperformance

 This is the minimum and least disruptive change necessary to protect the searchability of the indexer cluster in case of indexer failure, because it ensures that there are always at least two copies of each bucket in the cluster, one of which is searchable. This way, if one indexer fails, the cluster can still serve search requests from the remaining copy. Increasing the replication factor and search factor also improves the cluster’s resiliency and availability.

The other options are incorrect because they either do not protect the searchability of the cluster, or they require more changes and disruptions to the cluster. Option A is incorrect because enabling maintenance mode on the CM does not prevent excessive fix-up, but rather delays it until maintenance mode is disabled. Maintenance mode also prevents searches from running on the cluster, which defeats the purpose of protecting searchability. Option B is incorrect because leaving replication_factor=2 means that there is only one searchable copy of each bucket in the cluster, which is not enough to protect searchability in case of indexer failure. Enabling summary_replication does not help with this issue, as it only applies to summary indexes, not all indexes. Option C is incorrect because converting the cluster to multi-site requires a lot of changes and disruptions to the cluster, such as reassigning site attributes to all nodes, reconfiguring network settings, and rebalancing buckets across sites. It also does not guarantee that there will always be a searchable copy of each bucket in each site, unless the site replication factor and site search factor are set accordingly. References:

Splunk Core Consultant knowledge source documents or study guide: https://www.splunk.com/en_us/resources/splunk-certification-exam-study-guide.html

Splunk Test Blueprint Consultant: https://www.splunk.com/en_us/pdfs/training/splunk-test-blueprint-consultant.pdf

 Network latency is the time it takes for data to travel from one point to another, and storage IOPS is the number of input/output operations per second. These factors can affect the performance of the migration and should be taken into account when planning and executing the migration.

The CLI commands that you have shown in the image are used to adjust the maximum load that a peer node can handle during bucket replication and rebuilding. These settings can affect the performance and efficiency of an index cluster migration to new hardware. Therefore, some of the factors that you should consider when running these commands are:

Data ingestion rate: The higher the data ingestion rate, the more buckets will be created and need to be replicated or rebuilt across the cluster. This will increase the load on the peer nodes and the network bandwidth. You might want to lower the max_peer_build_load and max_peer_rep_load settings to avoid overloading the cluster during migration.

Network latency and storage IOPS: The network latency and storage IOPS are measures of how fast the data can be transferred and stored between the peer nodes. The lower these values are, the longer it will take for the cluster to replicate or rebuild buckets. You might want to increase the max_peer_build_load and max_peer_rep_load settings to speed up the migration process, but not too high that it causes errors or timeouts.

Distance and location: The distance and location of the peer nodes can also affect the network latency and bandwidth. If the peer nodes are located in different geographic regions or data centers, the data transfer might be slower and more expensive than if they are in the same location. You might want to consider using site replication factor and site search factor settings to optimize the cluster for multisite deployment.

SSL data encryption: If you enable SSL data encryption for your cluster, it will add an extra layer of security for your data, but it will also consume more CPU resources and network bandwidth. This might slow down the data transfer and increase the load on the peer nodes. You might want to balance the trade-off between security and performance when using SSL data encryption.

References:

Splunk Core Consultant knowledge source documents or study guide: https://www.splunk.com/en_us/resources/splunk-certification-exam-study-guide.html

Splunk Test Blueprint Consultant: https://www.splunk.com/en_us/pdfs/training/splunk-test-blueprint-consultant.pdf

 The updated dashboard will not be available to the power user; they will see their modified version. This is because the Splunk App for AWS is a prebuilt app that is installed on the deployer and pushed to the search head cluster members. When a power user modifies a dashboard in the app on one of the search head cluster members, the changes are stored in the local directory of that member. When the app is upgraded to the latest version by following the instructions via the deployer, the changes in the default directory of the app are overwritten, but the changes in the local directory are preserved. Therefore, the power user will still see their modified version of the dashboard, while other users will see the updated version of the dashboard.

The other options are incorrect because they do not reflect what happens when a prebuilt app is upgraded in a search head cluster. Option A is incorrect because the updated dashboard will be deployed globally to all users, except for the power user who modified it. Option B is incorrect because applying the search head cluster bundle will not fail due to the conflict, as the local changes are not pushed back to the deployer. Option C is incorrect because the updated dashboard will not be available to the power user, as their local changes will take precedence over the default changes. References:

Splunk Core Consultant knowledge source documents or study guide: https://www.splunk.com/en_us/resources/splunk-certification-exam-study-guide.html

Splunk Test Blueprint Consultant: https://www.splunk.com/en_us/pdfs/training/splunk-test-blueprint-consultant.pdf

Install a prebuilt app on a search head cluster1

How configuration file precedence works2

The steps to ensure that the Monitoring Console (MC) is aware of the additional indexers are to use the MC setup UI, review and apply the changes. The MC setup UI is a graphical interface that allows you to configure and manage the MC instance and its data sources. When new indexers are added to an indexer cluster, the MC setup UI can detect them automatically and prompt you to review and apply the changes. This will update the MC data sources and enable the MC to monitor the new indexers. References:

https://docs.splunk.com/Documentation/Splunk/9.1.1/DMC/ConfiguretheMonitoringConsole

https://docs.splunk.com/Documentation/Splunk/9.1.1/DMC/Addinstances

 The SHC will function as expected as the minimum required number of nodes for a SHC is 3. This is because the SHC uses a quorum-based algorithm to determine the cluster state and elect the captain. A quorum is a majority of cluster members that can communicate with each other. As long as a quorum exists, the cluster can continue to operate normally and serve search requests. If a network outage occurs between the two data centers, each data center will have three SHC members, but only one of them will have a quorum. The data center with the quorum will elect a new captain if the previous one was in the other data center, and the other data center will lose its cluster status and stop serving searches until the network communication is restored.

The other options are incorrect because they do not reflect what happens when a network outage occurs between two data centers with a SHC. Option A is incorrect because the SHC deployer will not become the new captain, as it is not part of the SHC and does not participate in cluster activities. Option B is incorrect because the SHC will not stop all scheduled search activity, as it will still run scheduled searches on the data center with the quorum. Option D is incorrect because the SHC captain will not fall back to previous active captain in the remaining site, as it will be elected by the quorum based on several factors, such as load, availability, and priority. References:

Splunk Core Consultant knowledge source documents or study guide: https://www.splunk.com/en_us/resources/splunk-certification-exam-study-guide.html

Splunk Test Blueprint Consultant: https://www.splunk.com/en_us/pdfs/training/splunk-test-blueprint-consultant.pdf

Search head clustering architecture1

Search head cluster captain election

The search can be rewritten to maximize efficiency by using the index option. The index option is used to specify the index to search. This option is useful when you have multiple indexes and want to search only one of them. The index option is also useful when you want to search a specific index that is not the default index. The index option can reduce the search time and resource consumption by limiting the scope of the search. Therefore, the correct answer is C. Option C, which uses the index option to search only the main index for the sourcetype web_access. References:

Splunk Core Certified Consultant Test Blueprint

Splunk Documentation: Specify indexes in your search

Splunk Documentation: Use the index option