The index-time props.conf attributes that impact indexing performance are LINE_BREAKER and SHOULD_LINEMERGE. These attributes determine how Splunk breaks the incoming data into events and whether it merges multiple events into one. These operations can affect the indexing speed and the disk space consumption. The REPORT attribute does not impact indexing performance, as it is used to apply transforms at search time. The ANNOTATE_PUNCT attribute does not impact indexing performance, as it is used to add punctuation metadata to events at search time. For more information, see [About props.conf and transforms.conf] in the Splunk documentation.

Splunk Enterprise uses the _audit index to log and store all user activity and audit-related information. This includes details such as user logins, searches executed, configuration changes, role modifications, and app management actions.

The _audit index is populated by data collected from the Splunkd audit logger and records actions performed through both Splunk Web and the CLI. Each event in this index typically includes fields like user, action, info, search_id, and timestamp, allowing administrators to track activity across all Splunk users and components for security, compliance, and accountability purposes.

The _internal index, by contrast, contains operational logs such as metrics.log and scheduler.log used for system performance and health monitoring. _kvstore stores internal KV Store metadata, and _telemetry is used for optional usage data reporting to Splunk.

The _audit index is thus the authoritative source for user behavior monitoring within Splunk environments and is a key component of compliance and security auditing.

References (Splunk Enterprise Documentation):

• Audit Logs and the _audit Index – Monitoring User Activity

• Splunk Enterprise Security and Compliance: Tracking User Actions

• Splunk Admin Manual – Overview of Internal Indexes (_internal, _audit, _introspection)

• Splunk Audit Logging and User Access Monitoring

KV Store is a feature of Splunk Enterprise that allows apps to store and retrieve data within the context of an app1.

KV Store resides on search heads and replicates data across the members of a search head cluster1.

KV Store resiliency refers to the ability of KV Store to maintain data availability and consistency in the event of failures or disruptions2.

One of the factors that affects KV Store resiliency is the network latency between search heads, which can impact the speed and reliability of data replication2.

Decreasing latency between search heads can improve KV Store resiliency by reducing the chances of data loss, inconsistency, or corruption2.

The other options are not directly related to KV Store resiliency. Faster storage, indexer CPU and memory, and Operations Log size may affect other aspects of Splunk performance, but not KV Store345.

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.

The following statements describe a search head cluster captain:

Is the job scheduler for the entire search head cluster. The captain is responsible for scheduling and dispatching the searches that run on the search head cluster, as well as coordinating the search results from the search peers. The captain also ensures that the scheduled searches are balanced across the search head cluster members and that the search concurrency limits are enforced.

Replicates the search head cluster’s knowledge bundle to the search peers. The captain is responsible for creating and distributing the knowledge bundle to the search peers, which contains the knowledge objects that are required for the searches. The captain also ensures that the knowledge bundle is consistent and up-to-date across the search head cluster and the search peers. The following statements do not describe a search head cluster captain:

Manages alert action suppressions (throttling). Alert action suppressions are the settings that prevent an alert from triggering too frequently or too many times. These settings are managed by the search head that runs the alert, not by the captain. The captain does not have any special role in managing alert action suppressions.

Synchronizes the member list with the KV store primary. The member list is the list of search head cluster members that are active and available. The KV store primary is the search head cluster member that is responsible for replicating the KV store data to the other members. These roles are not related to the captain, and the captain does not synchronize them. The member list and the KV store primary are determined by the RAFT consensus algorithm, which is independent of the captain election. For more information, see [About the captain and the captain election] and [About KV store and search head clusters] in the Splunk documentation.

Increasing the number of parallel ingestion pipelines in server.conf is most likely to improve indexing performance when indexing is slow and real-time search results are delayed in a Splunk environment with two indexers and one search head. The parallel ingestion pipelines allow Splunk to process multiple data streams simultaneously, which increases the indexing throughput and reduces the indexing latency. Increasing the maximum number of hot buckets in indexes.conf will not improve indexing performance, but rather increase the disk space consumption and the bucket rolling time. Decreasing the maximum size of the search pipelines in limits.conf will not improve indexing performance, but rather reduce the search performance and the search concurrency. Decreasing the maximum concurrent scheduled searches in limits.conf will not improve indexing performance, but rather reduce the search capacity and the search availability. For more information, see Configure parallel ingestion pipelines in the Splunk documentation.

Index files (. tsidx files) are the main components of an index that store the raw data and the inverted index of terms. They take the most space in an index, especially if the raw data has many unique terms that increase the size of the inverted index. Bloom filters, source metadata, and sourcetype metadata are much smaller in comparison and do not depend on the number of unique terms in the raw data.

According to Splunk’s Deployment Planning and Implementation Guidelines, one of the most critical elements of a Splunk deployment plan is a comprehensive data source inventory and current logging details. This information defines the scope of data ingestion and directly influences sizing, architecture design, and licensing.

A proper deployment plan should identify:

All data sources (such as syslogs, application logs, network devices, OS logs, databases, etc.)

Expected daily ingest volume per source

Log formats and sourcetypes

Retention requirements and compliance constraints

This data forms the foundation for index sizing, forwarder configuration, and storage planning. Without a well-defined data inventory, Splunk architects cannot accurately determine hardware capacity, indexing load, or network throughput requirements.

While stakeholder mapping, topology diagrams, and continuity plans (Options A, B, D) are valuable in a broader IT project, Splunk’s official guidance emphasizes logging details and source inventory as mandatory for a deployment plan. It ensures that the Splunk environment is properly sized, licensed, and aligned with business data visibility goals.

References (Splunk Enterprise Documentation):

• Splunk Enterprise Deployment Planning Manual – Data Source Inventory Requirements

• Capacity Planning for Indexer and Search Head Sizing

• Planning Data Onboarding and Ingestion Strategies

• Splunk Architecture and Implementation Best Practices

 The following is a good practice for a search head cluster deployer: The deployer must be used to distribute non-replicable configurations to search head cluster members. Non-replicable configurations are the configurations that are not replicated by the search factor, such as the apps and the server.conf settings. The deployer is the Splunk server role that distributes these configurations to the search head cluster members, ensuring that they have the same configuration. The deployer does not only distribute configurations to search head cluster members when they “phone home”, as this would cause configuration inconsistencies and delays. The deployer does not distribute configurations to search head cluster members to be valid configurations, as this implies that the configurations are invalid without the deployer. The deployer does not only distribute configurations to search head cluster members with splunk apply shcluster-bundle, as this would require manual intervention by the administrator. For more information, see Use the deployer to distribute apps and configuration updates in the Splunk documentation.

 To reduce the captain’s work load in a search head cluster, the setting that will prevent scheduled searches from running on the captain is captain_is_adhoc_searchhead = true (on the current captain). This setting will designate the current captain as an ad hoc search head, which means that it will not run any scheduled searches, but only ad hoc searches initiated by users. This will reduce the captain’s work load and improve the search head cluster performance. The adhoc_searchhead = true (on all members) setting will designate all search head cluster members as ad hoc search heads, which means that none of them will run any scheduled searches, which is not desirable. The adhoc_searchhead = true (on the current captain) setting will have no effect, as this setting is ignored by the captain. The captain_is_adhoc_searchhead = true (on all members) setting will have no effect, as this setting is only applied to the current captain. For more information, see Configure the captain as an ad hoc search head in the Splunk documentation.