SPLK-2002 Splunk Enterprise Certified Architect Free Practice Exam Questions (2025 Updated)

According to the Splunk blog1, the best method for sizing or scaling a search head cluster is to estimate the maximum concurrent number of searches and divide by the number of CPU cores per search head. This gives you an idea of how many search heads you need to handle the peak search load without overloading the CPU resources. The other options are false because:

Estimating the maximum daily ingest volume in gigabytes and dividing by the number of CPU cores per search head is not a good method for sizing or scaling a search head cluster, as it does not account for the complexity and frequency of the searches. The ingest volume is more relevant for sizing or scaling the indexers, not the search heads2.

Estimating the total number of searches per day and dividing by the number of CPU cores available on the search heads is not a good method for sizing or scaling a search head cluster, as it does not account for the concurrency and duration of the searches. The total number of searches per day is an average metric that does not reflect the peak search load or the search performance2.

Dividing the number of indexers by three to achieve the correct number of search heads is not a good method for sizing or scaling a search head cluster, as it does not account for the search load or the search head capacity. The number of indexers is not directly proportional to the number of search heads, as different types of data and searches may require different amounts of resources2.

The correct Splunk deployment to have the recommended minimum components for a high-availability search head cluster is 3 search heads, 1 deployer, 3 indexers. This configuration ensures that the search head cluster has at least three members, which is the minimum number required for a quorum and failover1. The deployer is a separate instance that manages the configuration updates for the search head cluster2. The indexers are the nodes that store and index the data, and having at least three of them provides redundancy and load balancing3. The other options are not recommended, as they either have less than three search heads or less than three indexers, which reduces the availability and reliability of the cluster. Therefore, option B is the correct answer, and options A, C, and D are incorrect.

1: About search head clusters 2: Use the deployer to distribute apps and configuration updates 3: About indexer clusters and index replication

 In a four site indexer cluster, the configuration that stores two searchable copies at the origin site, one searchable copy at site2, and a total of four searchable copies is site_search_factor = origin:2, site2:1, total:4. This configuration tells the cluster to maintain two copies of searchable data at the site where the data originates, one copy of searchable data at site2, and a total of four copies of searchable data across all sites. The site_search_factor determines how many copies of searchable data are maintained by the cluster for each site. The site_replication_factor determines how many copies of raw data are maintained by the cluster for each site. For more information, see Configure multisite indexer clusters with server.conf in the Splunk documentation.

According to the Splunk documentation1, the “Unknown sid” error message means that the search job associated with the link has expired or been deleted. The sid (search ID) is a unique identifier for each search job, and it is used to retrieve the results of the search. If the sid is not found, the search cannot be displayed. The other options are false because:

The users having insufficient permissions would result in a different error message, such as “You do not have permission to view this page” or "You do not have permission to run this search"1.

An add-on needing to be updated would not affect the validity of the sid, unless the add-on changes the search syntax or the data source in a way that makes the search invalid or inaccessible1.

One or more indexers being down would not cause the “Unknown sid” error, as the sid is stored on the search head, not the indexers. However, it could cause other errors, such as “Unable to distribute to peer” or "Search peer has the following message: not enough disk space"1.

The telnet and tcpdump tools can be leveraged to diagnose connection problems between an indexer and forwarder. The telnet tool can be used to test the connectivity and port availability between the indexer and forwarder. The tcpdump tool can be used to capture and analyze the network traffic between the indexer and forwarder. The splunk btool command can be used to check the configuration files of the indexer and forwarder, but it cannot diagnose the connection problems. The splunk btprobe command does not exist, and it is not a valid tool.

 Configurations from the deployer are merged into the SPLUNK_HOME/etc/apps/APP_HOME/local directory on the search head cluster member. The deployer distributes apps and other configurations to the search head cluster members in the form of a configuration bundle. The configuration bundle contains the contents of the SPLUNK_HOME/etc/shcluster/apps directory on the deployer. When a search head cluster member receives the configuration bundle, it merges the contents of the bundle into its own SPLUNK_HOME/etc/apps directory. The configurations in the local directory take precedence over the configurations in the default directory. The SPLUNK_HOME/etc/system/local directory is used for system-level configurations, not app-level configurations. The SPLUNK_HOME/etc/apps/search/default directory is used for the default configurations of the search app, not the configurations from the deployer.

Migration from single-site to multisite index replication only affects new data, not existing data. Multisite policies apply to new data only, meaning that data that is ingested after the migration will follow the multisite replication and search factors. Existing data, or data that was ingested before the migration, will retain the single-site policies, unless they are manually converted to multisite buckets. Single-site buckets do not instantly receive the multisite policies, nor do they automatically convert to multisite buckets. Multisite total values can exceed any single-site factors, as long as they do not exceed the number of peer nodes in the cluster. A master node is not required at each site, only one master node is needed for the entire cluster

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

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

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

The 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

 The splunk diag --exclude command is a way to exclude search artifacts when creating a diag. A diag is a diagnostic snapshot of a Splunk instance that contains various logs, configurations, and other information. Search artifacts are temporary files that are generated by search jobs and stored in the dispatch directory. Search artifacts can be excluded from the diag by using the --exclude option and specifying the dispatch directory. The splunk diag --debug --refresh command is a way to create a diag with debug logging enabled and refresh the diag if it already exists. The splunk diag --disable=dispatch command is not a valid command, because the --disable option does not exist. The splunk diag --filter-searchstrings command is a way to filter out sensitive information from the search strings in the diag

The correct tasks that the cluster manager performs in an indexer cluster are A. Generates and maintains the list of primary searchable buckets, B. If Indexer Discovery is enabled, provides the list of available peer nodes to forwarders, and D. Distributes app bundles to peer nodes. According to the Splunk documentation1, the cluster manager is responsible for these tasks, as well as managing the replication and search factors, coordinating the replication and search activities, and providing a web interface for monitoring and managing the cluster. Option C, ensuring all peer nodes are always using the same version of Splunk, is not a task of the cluster manager, but a requirement for the cluster to function properly2. Therefore, option C is incorrect, and options A, B, and D are correct.

1: About the cluster manager 2: Requirements and compatibility for indexer clusters

The correct answer is B. Set the Replication Factor based on allowed indexer failure. This is a best practice for adding data resiliency to a single-site indexer cluster, as it ensures that there are enough copies of each bucket to survive the loss of one or more indexers without affecting the searchability of the data1. The Replication Factor is the number of copies of each bucket that the cluster maintains across the set of peer nodes2. The Replication Factor should be set according to the number of indexers that can fail without compromising the cluster’s ability to serve data1. For example, if the cluster can tolerate the loss of two indexers, the Replication Factor should be set to three1.

The other options are not best practices for adding data resiliency. Option A, setting the Replication Factor to 49, is not recommended, as it would create too many copies of each bucket and consume excessive disk space and network bandwidth1. Option C, always using the default Replication Factor of 3, is not optimal, as it may not match the customer’s requirements and expectations for data availability and performance1. Option D, setting the Replication Factor based on allowed search head failure, is not relevant, as the Replication Factor does not affect the search head availability, but the searchability of the data on the indexers1. Therefore, option B is the correct answer, and options A, C, and D are incorrect.

1: Configure the replication factor 2: About indexer clusters and index replication

 The following statements are true regarding Splunk Enterprise performance:

Adding search peers increases the search throughput as search load increases. This is because adding more search peers distributes the search workload across more indexers, which reduces the load on each indexer and improves the search speed and concurrency.

Adding search heads provides additional CPU cores to run more concurrent searches. This is because adding more search heads increases the number of search processes that can run in parallel, which improves the search performance and scalability. The following statements are false regarding Splunk Enterprise performance:

Adding search peers does not increase the maximum size of search results. The maximum size of search results is determined by the maxresultrows setting in the limits.conf file, which is independent of the number of search peers.

Adding RAM to an existing search head does not provide additional search capacity. The search capacity of a search head is determined by the number of CPU cores, not the amount of RAM. Adding RAM to a search head may improve the search performance, but not the search capacity. For more information, see Splunk Enterprise performance in the Splunk documentation.

 When planning a search head cluster, the following statement is true: All indexers must belong to the underlying indexer cluster (no standalone indexers). A search head cluster is a group of search heads that share configurations, apps, and search jobs. A search head cluster requires an indexer cluster as its data source, meaning that all indexers that provide data to the search head cluster must be members of the same indexer cluster. Standalone indexers, or indexers that are not part of an indexer cluster, cannot be used as data sources for a search head cluster. All search heads do not have to use the same operating system, as long as they are compatible with the Splunk version and the indexer cluster. All search heads do not have to be members of the cluster, as standalone search heads can also search the indexer cluster, but they will not have the benefits of configuration replication and load balancing. The search head captain does not have to be assigned to the largest search head in the cluster, as the captain is dynamically elected from among the cluster members based on various criteria, such as CPU load, network latency, and search load.

This is the fall-back method for Splunk if .delta replication fails during knowledge bundle replication. Knowledge bundle replication is the process of distributing the knowledge objects, such as lookups, macros, and field extractions, from the search head cluster to the indexer cluster1. Splunk uses two methods of knowledge bundle replication: .delta replication and .bundle replication1. .Delta replication is the default and preferred method, as it only replicates the changes or updates to the knowledge objects, which reduces the network traffic and disk space usage1. However, if .delta replication fails for some reason, such as corrupted files or network errors, Splunk automatically switches to .bundle replication, which replicates the entire knowledge bundle, regardless of the changes or updates1. This ensures that the knowledge objects are always synchronized between the search head cluster and the indexer cluster, but it also consumes more network bandwidth and disk space1. The other options are not valid fall-back methods for Splunk. Option A, restarting splunkd, is not a method of knowledge bundle replication, but a way to restart the Splunk daemon on a node2. This may or may not fix the .delta replication failure, but it does not guarantee the synchronization of the knowledge objects. Option B, .delta replication, is not a fall-back method, but the primary method of knowledge bundle replication, which is assumed to have failed in the question1. Option D, restarting mongod, is not a method of knowledge bundle replication, but a way to restart the MongoDB daemon on a node3. This is not related to the knowledge bundle replication, but to the KV store replication, which is a different process3. Therefore, option C is the correct answer, and options A, B, and D are incorrect.

1: How knowledge bundle replication works 2: Start and stop Splunk Enterprise 3: Restart the KV store

When designing the number and size of indexes, the following considerations should be applied:

Expected daily ingest volumes: This is the amount of data that will be ingested and indexed by the Splunk platform per day. This affects the storage capacity, the indexing performance, and the license usage of the Splunk deployment. The number and size of indexes should be planned according to the expected daily ingest volumes, as well as the peak ingest volumes, to ensure that the Splunk deployment can handle the data load and meet the business requirements12.

Data retention time policies: This is the duration for which the data will be stored and searchable by the Splunk platform. This affects the storage capacity, the data availability, and the data compliance of the Splunk deployment. The number and size of indexes should be planned according to the data retention time policies, as well as the data lifecycle, to ensure that the Splunk deployment can retain the data for the desired period and meet the legal or regulatory obligations13.

Access controls: This is the mechanism for granting or restricting access to the data by the Splunk users or roles. This affects the data security, the data privacy, and the data governance of the Splunk deployment. The number and size of indexes should be planned according to the access controls, as well as the data sensitivity, to ensure that the Splunk deployment can protect the data from unauthorized or inappropriate access and meet the ethical or organizational standards14.

Option D is the correct answer because it reflects the most relevant and important considerations for designing the number and size of indexes. Option A is incorrect because the number of concurrent users is not a direct factor for designing the number and size of indexes, but rather a factor for designing the search head capacity and the search head clustering configuration5. Option B is incorrect because the number of installed apps is not a direct factor for designing the number and size of indexes, but rather a factor for designing the app compatibility and the app performance. Option C is incorrect because it omits the expected daily ingest volumes, which is a crucial factor for designing the number and size of indexes.

References:

1: Splunk Validated Architectures 2: [Indexer capacity planning] 3: [Set a retirement and archiving policy for your indexes] 4: [About securing Splunk Enterprise] 5: [Search head capacity planning] : [App installation and management overview]

Adding more search peers and making sure forwarders distribute data evenly across all indexers will provide the most search performance improvement when the distributed deployment is approaching its capacity. Adding more search peers will increase the search concurrency and reduce the load on each indexer. Distributing data evenly across all indexers will ensure that the search workload is balanced and no indexer becomes a bottleneck. Replacing the indexer storage to SSD will improve the search performance, but it is a costly and time-consuming option. Adding more search heads will not improve the search performance if the indexers are the bottleneck. Rescheduling slow searches to run during an off-peak time will reduce the search contention, but it will not improve the search performance for each individual search. For more information, see [Scale your indexer cluster] and [Distribute data across your indexers] in the Splunk documentation.

In the deployment planning process, a person should identify who gets to see network data in the data policy definition step. This step involves defining the data access policies and permissions for different users and roles in Splunk. The deployment schedule step involves defining the timeline and milestones for the deployment project. The topology diagramming step involves creating a visual representation of the Splunk architecture and components. The data source inventory step involves identifying and documenting the data sources and types that will be ingested by Splunk