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

The __introspection log file contains data about the impact of the Splunk software on the host system, such as CPU, memory, disk, and network usage, as well as KV store performance1.This log file is monitored by default and the contents are sent to the _introspection index1. The other options are not related to the __introspection log file.File monitor input configurations are stored in inputs.conf2.File monitor checkpoint offset is stored in fishbucket3.User activities and knowledge objects are stored in the _audit and _internal indexes respectively4.

Splunk Enterprise documentation clearly states that the best method to secure log traffic between Universal Forwarders (UFs) and Indexers is to implement Transport Layer Security (TLS) using signed SSL certificates. When Universal Forwarders send data to Indexers, this communication can be encrypted using SSL/TLS to prevent eavesdropping, data tampering, or interception while in transit.

Splunk provides default self-signed certificates out of the box, but these are only for testing or lab environments and should not be used in production. Production-grade security requires custom, signed SSL certificates --- either from an internal Certificate Authority (CA) or a trusted public CA. These certificates validate both the sender (forwarder) and receiver (indexer), ensuring data integrity and authenticity.

In practice, this involves:

Generating or obtaining CA-signed certificates.

Configuring the forwarder's outputs.conf to use SSL encryption (sslCertPath, sslPassword, and sslRootCAPath).

Configuring the indexer's inputs.conf and server.conf to require and validate client certificates.

This configuration ensures end-to-end encryption for all log data transmitted from forwarders to indexers.

Routing traffic through a WAF (Option C) does not provide end-to-end encryption for Splunk's internal communication, and securing search head--to--indexer communication (Option D) is unrelated to forwarder data flow.

Reference (Splunk Enterprise Documentation):

* Securing Splunk Enterprise: Encrypting Data in Transit Using SSL/TLS

* Configure Forwarder-to-Indexer Encryption

* Server and Forwarder Authentication with Signed Certificates

* Best Practices for Forwarder Management and Security Configuration

To ensure that high-velocity sources will not have forwarding delays to the indexers, the default limit for maxKBps in limits.conf should be increased. This parameter controls the maximum bandwidth that a forwarder can use to send data to the indexers. By default, it is set to 256 KBps, which may not be sufficient for high-volume data sources. Increasing this limit can reduce the forwarding latency and improve the performance of the forwarders. However, this should be done with caution, as it may affect the network bandwidth and the indexer load. Option B is the correct answer. Option A is incorrect because the sessionTimeout parameter in server.conf controls the duration of a TCP connection between a forwarder and an indexer, not the bandwidth limit. Option C is incorrect because the forceTimebasedAutoLB parameter in outputs.conf controls the frequency of load balancing among the indexers, not the bandwidth limit.Option D is incorrect because the phoneHomelntervallnSecs parameter in deploymentclient.conf controls the interval at which a forwarder contacts the deployment server, not the bandwidth limit12

1: https://docs.splunk.com/Documentation/Splunk/9.1.2/Admin/Limitsconf#limits.conf.spec2: https://docs.splunk.com/Documentation/Splunk/9.1.2/Forwarding/Routeandfilterdatad#Set_the_maximum_bandwidth_usage_for_a_forwarder

Intermediate forwarders are forwarders that receive data from other forwarders and then send that data to indexers. They can be useful in some scenarios, such as when network bandwidth or security constraints prevent direct forwarding to indexers, or when data needs to be routed, cloned, or modified in transit. However, intermediate forwarders also introduce additional complexity and overhead to the data pipeline, which can affect the performance and reliability of data ingestion. Therefore, intermediate forwarders should be avoided when possible, and used only when there is a clear benefit or requirement for them. Some of the drawbacks of intermediate forwarders are:

They increase the number of hops and connections in the data flow, which can introduce latency and increase the risk of data loss or corruption.

They consume more resources on the hosts where they run, such as CPU, memory, disk, and network bandwidth, which can affect the performance of other applications or processes on those hosts.

They require additional configuration and maintenance, such as setting up inputs, outputs, load balancing, security, monitoring, and troubleshooting.

They can create data duplication or inconsistency if they are not configured properly, such as when using cloning or routing rules.

Some of the references that support this answer are:

Configure an intermediate forwarder, which states: ''Intermediate forwarding is where a forwarder receives data from one or more forwarders and then sends that data on to another indexer. This kind of setup is useful when, for example, you have many hosts in different geographical regions and you want to send data from those forwarders to a central host in that region before forwarding the data to an indexer. All forwarder types can act as an intermediate forwarder. However, this adds complexity to your deployment and can affect performance, so use it only when necessary.''

Intermediate data routing using universal and heavy forwarders, which states: ''This document outlines a variety of Splunk options for routing data that address both technical and business requirements. Overall benefits Using splunkd intermediate data routing offers the following overall benefits: ... The routing strategies described in this document enable flexibility for reliably processing data at scale. Intermediate routing enables better security in event-level data as well as in transit. The following is a list of use cases and enablers for splunkd intermediate data routing: ... Limitations splunkd intermediate data routing has the following limitations: ... Increased complexity and resource consumption. splunkd intermediate data routing adds complexity to the data pipeline and consumes resources on the hosts where it runs. This can affect the performance and reliability of data ingestion and other applications or processes on those hosts. Therefore, intermediate routing should be avoided when possible, and used only when there is a clear benefit or requirement for it.''

Use forwarders to get data into Splunk Enterprise, which states: ''The forwarders take the Apache data and send it to your Splunk Enterprise deployment for indexing, which consolidates, stores, and makes the data available for searching. Because of their reduced resource footprint, forwarders have a minimal performance impact on the Apache servers. ... Note: You can also configure a forwarder to send data to another forwarder, which then sends the data to the indexer. This is called intermediate forwarding. However, this adds complexity to your deployment and can affect performance, so use it only when necessary.''

The following may explain the problem of why a colleague cannot see the src_ip field in their search results: The field was extracted as a private knowledge object, and the colleague did not explicitly use the field in the search and the search was set to Fast Mode. A knowledge object is a Splunk entity that applies some knowledge or intelligence to the data, such as a field extraction, a lookup, or a macro. A knowledge object can have different permissions, such as private, app, or global. A private knowledge object is only visible to the user who created it, and it cannot be shared with other users. A field extraction is a type of knowledge object that extracts fields from the raw data at index time or search time. If a field extraction is created as a private knowledge object, then only the user who created it can see the extracted field in their search results. A search mode is a setting that determines how Splunk processes and displays the search results, such as Fast, Smart, or Verbose. Fast mode is the fastest and most efficient search mode, but it also limits the number of fields and events that are displayed. Fast mode only shows the default fields, such as _time, host, source, sourcetype, and _raw, and any fields that are explicitly used in the search. If a field is not used in the search and it is not a default field, then it will not be shown in Fast mode. The events are tagged as communicate, but are missing the network tag, and the Typing Queue, which does regular expression replacements, is blocked, are not valid explanations for the problem. Tags are labels that can be applied to fields or field values to make them easier to search. Tags do not affect the visibility of fields, unless they are used as filters in the search. The Typing Queue is a component of the Splunk data pipeline that performs regular expression replacements on the data, such as replacing IP addresses with host names.The Typing Queue does not affect the field extraction process, unless it is configured to do so