Splunk SPLK-2002 Dumps - Pass Splunk Enterprise Certified Architect Exam in First Attempt 2026

As per Splunk Enterprise Search Performance documentation, the most significant factor affecting search performance when querying across a large number of buckets is disk I/O throughput. A search that spans ''All Time'' forces Splunk to inspect all historical buckets (hot, warm, cold, and potentially frozen if thawed), even if only a few events match the query. This dramatically increases the amount of data read from disk, making the search bound by I/O performance rather than CPU or memory.

Increasing the number of indexing pipelines (Option B) only benefits data ingestion, not search performance. Changing to a real-time search (Option D) does not help because real-time searches are optimized for streaming new data, not historical queries. The indexed_realtime_use_by_default setting (Option C) applies only to streaming indexed real-time searches, not historical ''All Time'' searches.

To improve performance for such searches, Splunk documentation recommends enhancing disk I/O capability --- typically through SSD storage, increased disk bandwidth, or optimized storage tiers. Additionally, creating summary indexes or accelerated data models may help for repeated ''All Time'' queries, but the most direct improvement comes from faster disk performance since Splunk must scan large numbers of buckets for even small result sets.

Reference (Splunk Enterprise Documentation):

* Search Performance Tuning and Optimization

* Understanding Bucket Search Mechanics and Disk I/O Impact

* limits.conf Parameters for Search Performance

* Storage and Hardware Sizing Guidelines for Indexers and Search Heads

Data retention is optional in the data source assessment because it is not directly related to the ingestion process. Data retention is determined by the index configuration and the storage capacity of the Splunk platform. Data format, data location, and data volume are all essential information for planning how to collect, parse, and index the data source.

Drive more value through data source and use case optimization - Splunk, page 9

Data source planning for Splunk Enterprise Security

Splunk documentation states that in an indexer-clustered environment, the Monitoring Console should be deployed on the Cluster Manager. This placement ensures direct access to cluster-wide metrics, replication status, bucket health, and indexer performance data.

The Cluster Manager already communicates with all peer indexers and maintains authoritative cluster state information. Hosting the Monitoring Console on this instance allows it to automatically collect and display cluster health dashboards without requiring additional configuration.

While the Monitoring Console can technically run on other instances, Splunk explicitly recommends colocating it with the Cluster Manager in clustered deployments to ensure full visibility and accuracy.

Deploying it on each instance or on unrelated servers is not recommended and does not align with Splunk best practices.

Therefore, the correct answer is D: On the Cluster Manager.

Splunk Monitoring Console Manual; Indexer Cluster Management Guide; Cluster Health Monitoring Best Practices.

The index=_internal component=DC* host=<uf> search will show all deployment client messages from the universal forwarder. The component field indicates the type of Splunk component that generated the message, and the host field indicates the host name of the machine that sent the message. The index=_audit component=DC* host=<uf> search will not return any results, because the deployment client messages are not stored in the _audit index. The index=_internal component=DS* host=<ds> search will show the deployment server messages from the deployment server, not the client.The index=_audit component=DS* host=<ds> search will also not return any results, for the same reason as above

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.