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

This is where in the Job Inspector details can be found to help determine where performance is affected, as it shows the time and resources spent by each component of the search, such as commands, subsearches, lookups, and post-processing1. The Execution Costs > Components section can help identify the most expensive or inefficient parts of the search, and suggest ways to optimize or improve the search performance1. The other options are not as useful as the Execution Costs > Components section for finding performance issues. Option A, Search Job Properties > runDuration, shows the total time, in seconds, that the search took to run2. This can indicate the overall performance of the search, but it does not provide any details on the specific components or factors that affected the performance. Option B, Search Job Properties > runtime, shows the time, in seconds, that the search took to run on the search head2. This can indicate the performance of the search head, but it does not account for the time spent on the indexers or the network. Option C, Job Details Dashboard > Total Events Matched, shows the number of events that matched the search criteria3. This can indicate the size and scope of the search, but it does not provide any information on the performance or efficiency of the search. Therefore, option D is the correct answer, and options A, B, and C are incorrect.

1: Execution Costs > Components 2: Search Job Properties 3: Job Details Dashboard

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

Comprehensive and Detailed Explanation (From Splunk Enterprise Documentation)Splunk Enterprise documentation clarifies that none of the listed configurations are prohibited in production. Splunk allows the Cluster Manager to be colocated with the Monitoring Console in small deployments because both are management-plane functions and do not handle ingestion or search traffic. The documentation also states that the Search Head Cluster Deployer is not a runtime component and has minimal performance requirements, so it may be colocated with the Monitoring Console or Licensing Master when hardware resources permit.

Splunk also supports virtual machines for both search heads and indexers, provided they are deployed with dedicated CPU, storage throughput, and predictable performance. Splunk’s official hardware guidance specifies that while bare metal often yields higher performance, virtualized deployments are fully supported in production as long as sizing principles are met.

Because Splunk explicitly supports all four configurations under proper sizing and best-practice guidelines, there is no correct selection for “unsupported.” The question is outdated relative to current Splunk Enterprise recommendations.

Setting site=site0 on all Search Head Cluster members disables search site affinity. Search site affinity is a feature that allows search heads to preferentially search the peer nodes that are in the same site as the search head, to reduce network latency and bandwidth consumption. By setting site=site0, which is a special value that indicates no site, the search heads will search all peer nodes regardless of their site. Setting site=site0 does not set all members to dynamic captaincy, enable multisite search artifact replication, or enable automatic search site affinity discovery. Dynamic captaincy is a feature that allows any member to become the captain, and it is enabled by default. Multisite search artifact replication is a feature that allows search artifacts to be replicated across sites, and it is enabled by setting site_replication_factor to a value greater than 1. Automatic search site affinity discovery is a feature that allows search heads to automatically determine their site based on the network latency to the peer nodes, and it is enabled by setting site=auto

 The Monitoring Console is the Splunk tool that offers a health check for administrators to evaluate the health of their Splunk deployment. The Monitoring Console provides dashboards and alerts that show the status and performance of various Splunk components, such as indexers, search heads, forwarders, license usage, and search activity. The Monitoring Console can also run health checks on the deployment and identify any issues or recommendations. The btool is a command-line tool that shows the effective settings of the configuration files, but it does not offer a health check. The DiagGen is a tool that generates diagnostic snapshots of the Splunk environment, but it does not offer a health check. The SPL Clinic is a tool that analyzes and optimizes SPL queries, but it does not offer a health check. For more information, see About the Monitoring Console in the Splunk documentation.

Two indexers clustered is the recommended deployment for a customer who plans to ingest 600 GB of data per day into Splunk, has six concurrent users, and wants high data availability and high search performance. This deployment will provide enough indexing capacity and search concurrency for the customer’s needs, while also ensuring data replication and searchability across the cluster. The customer can also save on the hardware cost by using only two indexers. Two indexers not in a cluster will not provide high data availability, as there is no data replication or failover. Three indexers not in a cluster will provide more indexing capacity and search concurrency, but also more hardware cost and no data availability. The customer’s data retention period, number of long searches, or volume of saved/scheduled searches are not relevant for determining the number of indexers. For more information, see [Reference hardware] and [About indexer clusters and index replication] in the Splunk documentation.

When adding or decommissioning a member from a Search Head Cluster (SHC), the proper order of operations is:

Delete Splunk Enterprise, if it exists.

Install and initialize the instance.

Join the SHC.

This order of operations ensures that the member has a clean and consistent Splunk installation before joining the SHC. Deleting Splunk Enterprise removes any existing configurations and data from the instance. Installing and initializing the instance sets up the Splunk software and the required roles and settings for the SHC. Joining the SHC adds the instance to the cluster and synchronizes the configurations and apps with the other members. The other order of operations are not correct, because they either skip a step or perform the steps in the wrong order.

Comprehensive and Detailed Explanation (From Splunk Enterprise Documentation)Splunk’s Search Head Clustering documentation explains that the cluster uses a majority-based election system. A captain is elected only when a node sees more than half of the cluster. In a two-site design where site1 has the majority of members, Splunk states that the majority site continues normal operation during a network partition. The minority site (site2) is not allowed to elect a captain and should not promote itself.

Splunk specifically warns administrators not to enable static captain on a minority site during a network split. Doing so creates two independent clusters, leading to configuration divergence and severe data-consistency issues. The documentation emphasizes that static captain should only be used for a complete loss of majority, not for a site partition.

Because Site1 maintains majority, it remains the active cluster and site2 does not perform any actions. Splunk states that minority-site members should simply wait until network communication is restored.

Thus the correct answer is B: No action is required.

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

The _internal index contains license-related events, such as the license usage, the license quota, the license pool, the license stack, and the license violations. These events are logged by the license manager in the license_usage.log file, which is part of the _internal index. The _audit index contains audit events, such as user actions, configuration changes, and search activity. These events are logged by the audit trail in the audit.log file, which is part of the _audit index. The _license index does not exist in Splunk, as the license-related events are stored in the _internal index. The _introspection index contains platform instrumentation data, such as the resource usage, the disk objects, the search activity, and the data ingestion. These data are logged by the introspection generator in various log files, such as resource_usage.log, disk_objects.log, search_activity.log, and data_ingestion.log, which are part of the _introspection index. For more information, see About Splunk Enterprise logging and [About the _internal index] in the Splunk documentation.

Before deploying Splunk, it is important to gather some information about the current environment, such as:

Overall goals for the deployment: This includes the business objectives, the use cases, the expected outcomes, and the success criteria for the Splunk deployment. This information helps to define the scope, the requirements, the design, and the validation of the Splunk solution1.

Key users: This includes the roles, the responsibilities, the expectations, and the needs of the different types of users who will interact with the Splunk deployment, such as administrators, analysts, developers, and end users. This information helps to determine the user access, the user experience, the user training, and the user feedback for the Splunk solution1.

Data sources: This includes the types, the formats, the volumes, the locations, and the characteristics of the data that will be ingested, indexed, and searched by the Splunk deployment. This information helps to estimate the data throughput, the data retention, the data quality, and the data analysis for the Splunk solution1.

Option B, C, and D are the correct answers because they reflect the essential information that is needed before deploying Splunk. Option A is incorrect because the list of vendors for network devices is not a relevant information for the Splunk deployment. The network devices may be part of the data sources, but the vendors are not important for the Splunk solution.

According to the Splunk Enterprise Capacity Planning and Hardware Sizing Guidelines, a distributed Splunk environment’s minimum search head specification must ensure that the system can efficiently manage search parsing, ad-hoc query execution, and knowledge object replication. Splunk officially recommends using a 64-bit x86 architecture system with a minimum of two physical CPU cores (or four vCPUs) running at 2 GHz or higher per core for acceptable performance.

Search heads are CPU-intensive components, primarily constrained by processor speed and the number of concurrent searches they must handle. Memory and disk space should scale with user concurrency and search load, but CPU capability remains the baseline requirement. While 128 GB RAM (Option C) is suitable for high-demand or Enterprise Security (ES) deployments, it exceeds the minimum hardware specification for general distributed search environments.

Splunk no longer supports 32-bit architectures (Option B). While a 1Gb Ethernet NIC (Option A) is common, it is not part of the minimum computational specification required by Splunk for search heads. The critical specification is processor capability — two physical cores or equivalent.

References (Splunk Enterprise Documentation):

• Splunk Enterprise Capacity Planning Manual – Hardware and Performance Guidelines

• Search Head Sizing and System Requirements

• Distributed Deployment Manual – Recommended System Specifications

• Splunk Hardware and Performance Tuning Guide

Search is not locked out when a customer has installed a 500GB Enterprise license and a 300GB, no enforcement license on the same license master. The no enforcement license allows the customer to exceed the license quota without locking search, but violations are still recorded. The customer can ingest up to 800GB of data per day without violating the license, but if they ingest more than that, they will incur a violation. However, the violation will not lock search, as the no enforcement license overrides the enforcement policy of the Enterprise license. For more information, see [No enforcement licenses] and [License violations] in the Splunk documentation.

Three peers can fail. This is the maximum number of search peers that can fail before data becomes unsearchable in the indexer cluster with the given characteristics. The searchability of the data depends on the Search Factor, which is the number of searchable copies of each bucket that the cluster maintains across the set of peer nodes1. In this case, the Search Factor is 3, which means that each bucket has three searchable copies distributed among the 10 search peers. If three or fewer search peers fail, the cluster can still serve the data from the remaining searchable copies. However, if four or more search peers fail, the cluster may lose some searchable copies and the data may become unsearchable. The other options are not correct, as they either underestimate or overestimate the number of search peers that can fail before data becomes unsearchable. Therefore, option C is the correct answer, and options A, B, and D are incorrect.

1: Configure the search factor

 The following artifacts are included in a Splunk diag file:

Internal logs. These are the log files that Splunk generates to record its own activities, such as splunkd.log, metrics.log, audit.log, and others. These logs can help troubleshoot Splunk issues and monitor Splunk performance.

Configuration files. These are the files that Splunk uses to configure various aspects of its operation, such as server.conf, indexes.conf, props.conf, transforms.conf, and others. These files can help understand Splunk settings and behavior. The following artifacts are not included in a Splunk diag file:

OS settings. These are the settings of the operating system that Splunk runs on, such as the kernel version, the memory size, the disk space, and others. These settings are not part of the Splunk diag file, but they can be collected separately using the diag --os option.

Customer data. These are the data that Splunk indexes and makes searchable, such as the rawdata and the tsidx files. These data are not part of the Splunk diag file, as they may contain sensitive or confidential information. For more information, see Generate a diagnostic snapshot of your Splunk Enterprise deployment in the Splunk documentation.

A deployment plan should include business continuity and disaster recovery plans, current logging details and data source inventory, and current and future topology diagrams of the IT environment. These elements are essential for planning, designing, and implementing a Splunk deployment that meets the business and technical requirements. A comprehensive list of stakeholders, either direct or indirect, is not part of the deployment plan, but rather part of the project charter. For more information, see Deployment planning in the Splunk documentation.

A dedicated deployment server is a Splunk instance that manages the distribution of configuration updates and apps to a set of deployment clients, such as forwarders, indexers, or search heads. A dedicated deployment server should be used when there are more than 50 deployment clients, because this number exceeds the recommended limit for a non-dedicated deployment server. A non-dedicated deployment server is a Splunk instance that also performs other roles, such as indexing or searching. Using a dedicated deployment server can improve the performance, scalability, and reliability of the deployment process. Option C is the correct answer. Option A is incorrect because the number of search peers does not affect the need for a dedicated deployment server. Search peers are indexers that participate in a distributed search. Option B is incorrect because the number of apps to deploy does not affect the need for a dedicated deployment server. Apps are packages of configurations and assets that provide specific functionality or views in Splunk. Option D is incorrect because the number of server classes does not affect the need for a dedicated deployment server. Server classes are logical groups of deployment clients that share the same configuration updates and apps12

1: https://docs.splunk.com/Documentation/Splunk/9.1.2/Updating/Aboutdeploymentserver 2: https://docs.splunk.com/Documentation/Splunk/9.1.2/Updating/Whentousedeploymentserver

 The following artifacts are included in a Splunk diag file:

Server specs. These are the specifications of the server that Splunk runs on, such as the CPU model, the memory size, the disk space, and the network interface. These specs can help understand the Splunk hardware requirements and performance.

Current open connections. These are the connections that Splunk has established with other Splunk instances or external sources, such as forwarders, indexers, search heads, license masters, deployment servers, and data inputs. These connections can help understand the Splunk network topology and communication.

Internal Splunk log files. These are the log files that Splunk generates to record its own activities, such as splunkd.log, metrics.log, audit.log, and others. These logs can help troubleshoot Splunk issues and monitor Splunk performance.

Index listings. These are the listings of the indexes that Splunk has created and configured, such as the index name, the index location, the index size, and the index attributes. These listings can help understand the Splunk data management and retention. The following artifacts are not included in a Splunk diag file:

Search history. This is the history of the searches that Splunk has executed, such as the search query, the search time, the search results, and the search user. This history is not part of the Splunk diag file, but it can be accessed from the Splunk Web interface or the audit.log file.

Splunk users and their roles. These are the users that Splunk has created and assigned roles to, such as the user name, the user password, the user role, and the user capabilities. These users and roles are not part of the Splunk diag file, but they can be accessed from the Splunk Web interface or the authentication.conf and authorize.conf files.

KV store listings. These are the listings of the KV store collections and documents that Splunk has created and stored, such as the collection name, the collection schema, the document ID, and the document fields. These listings are not part of the Splunk diag file, but they can be accessed from the Splunk Web interface or the mongod.log file.

Indexed data. These are the data that Splunk indexes and makes searchable, such as the rawdata and the tsidx files. These data are not part of the Splunk diag file, as they may contain sensitive or confidential information. For more information, see Generate a diagnostic snapshot of your Splunk Enterprise deployment in the Splunk documentation.

 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