Splunk Updated SPLK-2002 Exam Questions and Answers by kate

A lookup table is a file that contains a list of values that can be used to enrich or modify the data during search time1. Lookup tables can be stored in CSV files or in the KV Store1. Troubleshooting lookup tables involves identifying and resolving issues that prevent the lookup tables from being accessed, updated, or applied correctly by the Splunk searches. Some of the tools and methods that can help with troubleshooting lookup tables are:

web_access.log: This is a file that contains information about the HTTP requests and responses that occur between the Splunk web server and the clients2. This file can help troubleshoot issues related to lookup table permissions, availability, and errors, such as 404 Not Found, 403 Forbidden, or 500 Internal Server Error34.

btool output: This is a command-line tool that displays the effective configuration settings for a given Splunk component, such as inputs, outputs, indexes, props, and so on5. This tool can help troubleshoot issues related to lookup table definitions, locations, and precedence, as well as identify the source of a configuration setting6.

search.log: This is a file that contains detailed information about the execution of a search, such as the search pipeline, the search commands, the search results, the search errors, and the search performance. This file can help troubleshoot issues related to lookup table commands, arguments, fields, and outputs, such as lookup, inputlookup, outputlookup, lookup_editor, and so on .

Option B is the correct answer because web_access.log is the best place to start troubleshooting lookup table issues, as it can provide the most relevant and immediate information about the lookup table access and status. Option A is incorrect because btool output is not a log file, but a command-line tool. Option C is incorrect because health.log is a file that contains information about the health of the Splunk components, such as the indexer cluster, the search head cluster, the license master, and the deployment server. This file can help troubleshoot issues related to Splunk deployment health, but not necessarily related to lookup tables. Option D is incorrect because configuration_change.log is a file that contains information about the changes made to the Splunk configuration files, such as the user, the time, the file, and the action. This file can help troubleshoot issues related to Splunk configuration changes, but not necessarily related to lookup tables.

According to the Splunk documentation1, in a search head cluster, the KV Store Primary is the same node as the search head cluster captain. The KV Store Primary is responsible for coordinating the replication of KV Store data across the cluster members. When any node receives a write request, the KV Store delegates the write to the KV Store Primary. The KV Store keeps the reads local, however. This ensures that the KV Store data is consistent and available across the cluster.

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

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.