SPLK-3003 Splunk Core Certified Consultant Questions and Answers

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 replication 1

Monitoring Console: Where to install 2

According to the Splunk Core Consultant study guide, the correct mapping for the deployment of a new environment for a customer is Option D. This is because it follows the PS best practices for mapping, which include the use of the org_cluster_search_base, org_cluster_indexer_base, and org_all_indexes indexes. Additionally, Option D also includes the use of the etc/apps and etc/master-apps directories, which are recommended for the deployment of a new environment.  References :

Splunk Core Consultant study guide

Splunk Core Consultant test blueprint

 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 bec ause 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 inputs 1

Configure scripted inputs 2

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 check 1

: Splunk Documentation: Monitoring Console: Customize health check items 2

The Splunk Validated Architectures (SVAs) document provides a series of approved Splunk topologies that are designed to meet different deployment needs, such as scale, resilience, performance, and cost. The document also provides guidance on how to select the best topology for a customer’s requirements, as well as design principles and best practices to ensure a successful implementation. Therefore, the best way to use the SVAs document is to identify the customer’s requirements, provisionally choose an approved design that meets them, then consider design principles and best practices to come to an informed design decision. This approach allows the customer to find a topology that is suitable for their specific use cases and environment, while also following Splunk’s recommendations and standards.  References :

https://docs.splunk.com/Documentation/SVA/current/Architectures/Introduction 4

https://docs.splunk.com/Documentation/SVA/current/Architectures/Selectingatopology 5

https://docs.splunk.com/Documentation/SVA/current/Architectures/Designprinciplesandbestpractices

 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 bucket freezing process in a clustered indexer is controlled by the cluster master, which ensures that all copies of the bucket are frozen at the same time. This way, the cluster master can maintain the consistency and availability of the data across the cluster, and avoid any conflicts or errors due to mismatched bucket states.

The other options are incorrect because they do not reflect what happens when a bucket rolls from cold to frozen on a clustered indexer. Option A is incorrect because all replicated copies will not be rolled to frozen, while original copies will remain. This would violate the replication factor and search factor settings of the cluster, and cause data loss or unavailability. Option B is incorrect because replicated copies of the bucket will not remain on all other indexers, and the cluster master will not assign a new primary bucket. This would create duplicate and outdated data in the cluster, and cause search inefficiency or inconsistency. Option D is incorrect because nothing will not happen, and replicated copies of the bucket will not remain on all other indexers until a local retention rule causes it to roll. This would create different retention policies for different copies of the same bucket, and cause data fragmentation or corruption.  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 indexer clusters handle frozen data 1

How Splunk Enterprise handles frozen data 2

 What happens to the indexer cluster when the indexer Cluster Master (CM) runs out of disk space is that the indexer cluster will continue to operate as long as no indexers fail. The CM does not store any indexed data or participate in data replication or searching. It only manages the cluster by maintaining information about peer status, bucket status, and search head status. Therefore, if the CM runs out of disk space, it will not affect the normal functioning of the indexers or search heads, unless an indexer fails or needs to be added or removed from the cluster. In that case, the CM will not be able to perform its management tasks and may cause data unavailability or inconsistency in the cluster.  References :

https://docs.splunk.com/Documentation/Splunk/9.1.1/Indexer/Systemrequirements#Cluster_master_node

https://docs.splunk.com/Documentation/Splunk/9.1.1/Indexer/Masterfunctions

 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 architecture 1

Search head cluster captain election

 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/ < index_name > /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

The universal forwarder (UF) can cause truncation of events greater than 64K if it does not have the proper props.conf settings. The best practice magic 6 or great 8 props.conf settings are a set of attributes that control how the UF handles event breaking, line merging, timestamp extraction, and host extraction. These settings ensure that the UF preserves the integrity of the events and does not truncate or break them incorrectly. Therefore, the correct answer is B, configure the best practice magic 6 or great 8 props.conf settings.  References  :=

Configure event processing

The magic six or great eight props.conf settings

 The correct method to migrate the indexers from an old set of hardware to a new set of indexers is option C. This method ensures that the new indexers are added to the same site as the old indexers, and that the replication factor is increased by one to instruct the cluster to start replicating data to the new peers. This way, the cluster can maintain data availability and integrity during the migration process. After allowing enough time for the cluster master to fix and migrate buckets to the new hardware, the old indexers can be removed from the cluster master’s list.  References :

https://docs.splunk.com/Documentation/Splunk/9.1.1/Indexer/Migrateindexerstodifferenthardware 4

https://docs.splunk.com/Documentation/Splunk/9.1.1/Indexer/Migratetomultisite 5

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 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

 The primary driver behind implementing indexer clustering in a customer’s environment is to provide higher availability for buckets of data. Indexer clustering is a feature of Splunk Enterprise that allows a group of indexers to replicate each other’s data, so that the system keeps multiple copies of all data. This process is known as index replication. By maintaining multiple, identical copies of Splunk Enterprise data, clusters prevent data loss while promoting data availability for searching. Indexer clustering also provides load balancing and failover capabilities for search and indexing operations.

The other options are incorrect because they are not the main reasons for using indexer clustering. Option A is incorrect because indexer clustering does not improve resiliency as the search load increases, but rather as the indexer load increases. Resiliency refers to the ability of the cluster to maintain search and indexing performance under stress or failure conditions. Option B is incorrect because indexer clustering does not reduce indexing latency, but rather increases it slightly due to the overhead of replication. Indexing latency refers to the time it takes for data to be indexed and searchable after ingestion. Option D is incorrect because indexer clustering does not scale out a Splunk environment to offer higher performance capability, but rather scales up a Splunk environment to offer higher availability and resiliency. Scaling out refers to adding more nodes to a distributed system to increase its capacity and throughput, while scaling up refers to adding more resources to existing nodes to increase their performance and reliability.  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 replication 1

Indexer cluster architecture overview 2

 A subsearch is a search that runs within another search, and provides input to the outer search. A subsearch is useful when the input to the outer search is not known in advance, but depends on the results of another search. A subsearch is also useful when the input to the outer search is too large to be specified manually, but can be generated by another search. Therefore, a subsearch is the most appropriate in the scenario when dynamically filtering hosts. For example, if we want to filter the hosts that have a certain value of a field, we can use a subsearch to find those hosts and pass them to the outer search. For example:

This search will return the events from the main index that have a host value that matches the subsearch. The subsearch will find the hosts that have more than 100 events with status 404 in the access_combined sourcetype, and pass them to the outer search as a list of values. This way, we can dynamically filter the hosts based on another search criterion.

The other scenarios are not as suitable for using a subsearch. When joining results from multiple indexes, we can use the join command or append command instead of a subsearch. When filtering indexed fields, we can use the where command or the search command instead of a subsearch. When joining multiple large datasets, we can use the map command or the multisearch command instead of a subsearch.

References :

Splunk Core Certified Consultant Test Blueprint

Splunk Documentation: About subsearches

Splunk Documentation: Use subsearches

The best practice for ingesting data from a network device that transmits logs directly with UDP or TCP over SSL is to use a syslog server to aggregate the data to files and use a heavy forwarder to read and transmit the data to the indexing tier. This method has several advantages, such as:

It reduces the load on the network device by sending the data to a dedicated syslog server.

It provides a reliable and secure transport of data by using TCP over SSL between the syslog server and the heavy forwarder.

It allows the heavy forwarder to parse and enrich the data before sending it to the indexing tier.

It preserves the original timestamp and host information of the data by using the syslog-ng or Splunk Connect for Syslog solutions.

Therefore, the correct answer is C, use a syslog server to aggregate the data to files and use a heavy forwarder to read and transmit the data to the indexing tier.  References  :=

Get data from network sources

Use Splunk Connect for Syslog

Configure event processing

 A default behavior of a search head cluster captain is that it is a cluster member who performs normal search activities. This means that the captain can run searches, display dashboards, access knowledge objects, and perform other functions that any other search head can do. The captain also has additional responsibilities, such as coordinating artifact replication, managing search affinity, handling search head failures, and electing a new captain if needed.  References :

https://docs.splunk.com/Documentation/Splunk/9.1.1/DistSearch/SHCarchitecture

https://docs.splunk.com/Documentation/Splunk/9.1.1/DistSearch/Captainresponsibilities

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 least expensive and easiest way to improve search performance for a multisite cluster with limited bandwidth between sites is to configure site_search_factor to ensure a searchable copy exists in the local site for each search head. This option allows the search heads to use search affinity, which means they will prefer to search the data on their local site, avoiding network traffic across sites. This option also preserves the disaster recovery benefit of multisite clustering, as each site still has a full copy of the data. Therefore, the correct answer is A, configure site_search_factor to ensure a searchable copy exists in the local site for each search head.  References  :=

Multisite indexer clusters

Configure multisite indexer clusters with the CLI

Search affinity