SPLK-3003 Practice Exam Questions with Answers Splunk Core Certified Consultant Certification

 A [script://] input sends data to a Splunk forwarder using the standard output (STDOUT) and standard error (STDERR) streams of the script. A [script://] input is a type of scripted input that runs an executable script on a Splunk forwarder and indexes the data that the script outputs to STDOUT or STDERR. The script can be written in any scripting language, such as Python, Perl, or shell, and it can perform various tasks, such as querying APIs, databases, or remote data interfaces, and formatting the data for indexing. The Splunk forwarder launches the script at a specified interval and reads the data from its STDOUT or STDERR streams.

The other options are incorrect because they are not the methods that a [script://] input uses to send data to a Splunk forwarder. Option A is incorrect because UDP stream is not a method that a [script://] input uses, but rather a method that a network input uses to receive data from UDP ports. Option B is incorrect because TCP stream is not a method that a [script://] input uses, but rather a method that a network input uses to receive data from TCP ports. Option C is incorrect because temporary file is not a method that a [script://] input uses, but rather a method that a monitor input uses to read data from files or directories. 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
• Get data from APIs and other remote data interfaces through scripted inputs1
• Configure scripted inputs2

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

As a best practice, the following should be used to ingest data on clustered indexers: splunktcp, splunktcp-ssl, HTTP Event Collector (HEC). These are the methods that allow data to be sent to the indexers by forwarders or other data sources, without requiring any configuration on the indexers themselves. The indexers can receive the data on specific ports and index it according to the cluster settings. These methods also support load balancing and encryption of the data. Therefore, the correct answer is D. splunktcp, splunktcp-ssl, HTTP Event Collector (HEC). References:

• Splunk Core Certified Consultant Test Blueprint
• Splunk Documentation: Forward data to an indexer cluster
• Splunk Documentation: About forwarding and receiving data

 The customer can resolve the issue by modifying the blacklisted lookup definition stanza to specify setting allow_caching=true. This option allows the lookup to be cached on the search head and used for searches, without being included in the search bundle that is distributed to the indexers. This way, the customer can reduce the bundle size and avoid the error messages. Therefore, the correct answer is B, the blacklisted lookup definition stanza needs to be modified to specify setting allow_caching=true. References :=

• Configure distributed search
• Use lookups in distributed search

 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

 Each HEC input requires a unique name but token values can be shared. The name is a human-readable identifier for the input that appears in Splunk Web. The name must be unique among all HEC inputs on the same Splunk platform instance. The token value is a string of alphanumeric characters that acts as an identifier and an authentication code for the input. You can use the same token value for multiple inputs, but it is recommended to use different tokens for different data sources or applications. References :=

• Set up and use HTTP Event Collector in Splunk Web
• HTTP Event Collector: How to Install and Configure HEC in Splunk Web

The Monitoring Console (MC) is a Splunk app that provides a comprehensive view of the health and performance of a Splunk environment. The MC can be configured to monitor a single instance or a distributed deployment. To monitor a distributed deployment, the MC instance needs to be configured as a search head that can run distributed searches across the other instances in the environment. Therefore, the MC instance needs to have the other search heads, the deployment server, the license master, and the cluster master/master node as distributed search peers. The MC instance does not need to have the indexers as distributed search peers, because the cluster master/master node already provides access to the indexed data in the cluster. Therefore, the correct answer is C. Search heads, deployment server, license master, cluster master/master node. References:

• Splunk Core Certified Consultant Test Blueprint
• Splunk Documentation: About the Monitoring Console
• Splunk Documentation: Configure a Monitoring Console instance
• Splunk Documentation: Add search peers

Splunk Data Model Acceleration (DMA) summaries are stored in summaryHomePath, which is an attribute in the indexes.conf file that specifies the location of the summary files for data model acceleration. By default, the summaryHomePath is set to $SPLUNK_DB//summary, where $SPLUNK_DB is the root directory for all index data. The summary files are CSV files that contain precomputed summary data relevant to the data model. Therefore, the correct answer is C, in summaryHomePath. References :=

• Accelerate data models
• Indexes.conf.spec

These are the indexes.conf settings that can be leveraged to meet the requirements of the customer, given the following assumptions and calculations:

• The customer has a single indexer with a single storage device for all data.
• The customer wants to keep 30 days of data searchable, which means 30 x 50GB = 1500GB of data in total.
• The customer wants to optimize search performance for hourly scheduled searches that process a week’s worth of data, which means 7 x 50GB = 350GB of data per search.

The indexes.conf settings that can be used to achieve these goals are:

• maxDataSize: This setting determines the maximum size of a bucket before it rolls from hot to warm. By setting this to auto_high_volume, Splunk software will create buckets that are approximately 10GB in size, which is suitable for high-volume data sources. This will result in about 5 hot buckets and 145 warm buckets per index, which will reduce the number of buckets that need to be searched and improve search performance.
• frozenTimePeriodInSecs: This setting determines how long Splunk software keeps the data in an index before freezing or deleting it. By setting this to 2592000 seconds (30 days), Splunk software will ensure that the data is searchable for at least 30 days, and then move it to the frozen state or delete it according to the coldToFrozenDir or coldToFrozenScript settings.
• maxVolumeDataSizeMB: This setting determines the maximum size of a volume before Splunk software stops writing data to it. By setting this to 1536000 MB (1500 GB), Splunk software will ensure that the volume can store exactly 30 days of data, and then roll the oldest buckets to frozen or delete them according to the frozenTimePeriodInSecs setting.

The other options are incorrect because they either do not meet the requirements of the customer or they contain invalid or unnecessary settings. Option A is incorrect because frozenTimePeriodInSecs and maxVolumeDataSizeMB are redundant settings, as they both control the retention policy of the index. Also, maxHotBuckets is not relevant for search performance, as it only affects how many hot buckets can exist per index. Option B is incorrect because maxTotalDataSizeMB and maxGlobalDataSizeMB are not valid settings in indexes.conf, as they are only used in server.conf to control the total size of all indexes and all volumes respectively. Also, maxHotBuckets is not relevant for search performance, as it only affects how many hot buckets can exist per index. Option D is incorrect because homePath.maxDataSizeMB and maxHotSpanSecs are not valid settings in indexes.conf, as they are only used in volumes.conf to control the size and time span of hot buckets within a volume respectively. Also, maxWarmDBCount is not relevant for search performance, as it only affects how many warm buckets can exist per index. 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
• Configure index storage1
• indexes.conf2
• server.conf3
• volumes.conf4

 The Monitoring Console (MC) uses a REST endpoint to query the server and determine its role(s) based on the configuration files and processes running on the server. The MC does not rely on manual assignment, distsearch.conf, or default roles to identify the server role(s). References:

• : Splunk Documentation: Monitoring Console: Identify roles of Splunk Enterprise instances
• : Splunk Documentation: Monitoring Console: How the Monitoring Console identifies instance roles

When an index cluster peer freezes a bucket, it means that the bucket has reached the end of its retention period and is either deleted or archived, depending on the configuration. When a bucket is frozen, the cluster master will no longer perform fix-up activities for the bucket, such as replicating it to other peers or promoting it to primary. The cluster master will also update its list of buckets and remove the frozen bucket from the peer’s inventory. Therefore, the correct answer is C. The cluster master will no longer perform fix-up activities for the bucket. References:

• Splunk Core Certified Consultant Test Blueprint
• Splunk Documentation: How indexer clusters handle frozen buckets
• Splunk Documentation: Manage frozen data

The correct statement is that in general, search commands that can be distributed to the search peers should occur as early as possible in a well-tuned search. This is because distributed commands can leverage the parallel processing power of the search peers, which reduces the load on the search head and improves the search performance. Distributed commands are also known as streaming commands, which operate on each event individually and can be run on remote indexes. Some examples of distributed commands are eval, fields, rename, and where. References:

• [Splunk Certification Exam Study Guide], page 25
• [Splunk Documentation: About optimizing search performance]
• [Splunk Documentation: About streaming and transforming commands]

The data retention controls that must be configured to ensure that at least one year of logs are retained for both Windows and Firewall events are maxTotalDataSizeMB and frozenTimePeriodInSecs. These settings are defined in the indexes.conf file, which specifies the index settings and data retention policies for Splunk. The maxTotalDataSizeMB setting determines the maximum size of an index, in megabytes. When the index reaches this size, the oldest data is frozen (deleted or archived). The frozenTimePeriodInSecs setting determines the maximum age of the data in an index, in seconds. When the data exceeds this age, it is frozen. Therefore, by setting these values appropriately for the Windows and Firewall indexes, the customer can ensure that at least one year of logs are retained. References:

• Splunk Core Certified Consultant Test Blueprint
• Splunk Documentation: Set up multiple indexes
• Splunk Documentation: Configure index size and data retention

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 correct process and procedure for migrating a Splunk index cluster to new hardware is as follows:

• Install new indexers. This step involves installing the Splunk Enterprise software on the new machines and configuring them with the same network settings, OS settings, and hardware specifications as the original indexers.
• Configure indexers into the cluster as peers; ensure they receive the cluster bundle and the same configuration as original peers. This step involves joining the new indexers to the existing cluster as peer nodes, using the same cluster master and replication factor. The new indexers should also receive the same configuration files as the original peers, either by copying them manually or by using a deployment server. The cluster bundle contains the indexes.conf file and other files that define the index settings and data retention policies for the cluster.
• Decommission old peers one at a time. This step involves removing the old indexers from the cluster gracefully, using the splunk offline command or the REST API endpoint /services/cluster/master/control/control/decommission. This ensures that the cluster master redistributes the primary buckets from the old peers to the new peers, and that no data is lost during the migration process.
• Remove old peers from the CM’s list. This step involves deleting the old indexers from the list of peer nodes maintained by the cluster master, using the splunk remove server command or the REST API endpoint /services/cluster/master/peers. This ensures that the cluster master does not try to communicate with the old peers or assign them any search or replication tasks.
• Update forwarders to forward to the new peers. This step involves updating the outputs.conf file on the forwarders that send data to the cluster, so that they point to the new indexers instead of the old ones. This ensures that the data ingestion process is not disrupted by the migration.

References:

• Splunk Core Certified Consultant Test Blueprint
• Splunk Documentation: Migrate an indexer cluster
• Splunk Documentation: Decommission a peer node
• Splunk Documentation: Remove a peer node from an indexer cluster
• Splunk Documentation: Configure forwarders with outputs.conf

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

The PS preferred method for data onboarding is to use the inputs.conf file. The inputs.conf file is a configuration file that defines how Splunk Enterprise monitors files and directories, network ports, scripts, Windows event logs, and other data sources. The inputs.conf file allows for more flexibility, control, and automation than the other methods. The inputs.conf file also supports the use of base configurations, which are a set of configuration files that provide consistent, repeatable, and supportable configurations for Splunk deployments. Therefore, the correct answer is C. Use the inputs.conf file. References:

• Splunk Core Certified Consultant Test Blueprint
• Splunk Documentation: About inputs.conf
• Splunk Documentation: About base configurations

Carefully design smaller apps with specific configuration that can be reused. This is the Splunk PS recommendation when using the deployment server and building deployment apps, because it allows for more flexibility, modularity, and efficiency in managing and deploying updates to Splunk Enterprise instances. Smaller apps with specific configuration can be easily reused across different server classes, environments, and use cases, without causing conflicts or redundancies. They can also reduce the size of the deployment bundle and the network bandwidth consumption.

The other options are incorrect because they are not the Splunk PS recommendation when using the deployment server and building deployment apps. Option B is incorrect because deploying only Splunk PS base configurations via the deployment server limits the functionality and customization of the deployment server, as it does not allow for deploying other types of apps, such as add-ons, dashboards, or custom configurations. Option C is incorrect because using $SPLUNK_HOME/etc/system/local configurations on forwarders and only deploying TAs via the deployment server is not a good practice, as it makes the forwarder configuration harder to manage and troubleshoot, and it does not leverage the full potential of the deployment server. Option D is incorrect because carefully designing bigger apps containing multiple configs is not a good practice, as it makes the deployment apps more complex, less reusable, and more prone to errors and conflicts. 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 deployment server and forwarder management1
• Plan a deployment2

 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