SPLK-2002 Exam Dumps

Explanation:
According to the Splunk blog1, the Universal Forwarder is ideal for collecting data from high-velocity data sources, such as a syslog server, due to its smaller footprint and faster performance. The Universal Forwarder performs minimal processing and sends raw or unparsed data to the indexers, reducing the network traffic and the load on the forwarders.
The other options are false because:

• When most of the data requires masking, a Heavy Forwarder is needed, as it can perform advanced filtering and data transformation before forwarding the data2.
• When data comes directly from a database server, a Heavy Forwarder is needed, as it can run modular inputs such as DB Connect to collect data from various databases2.
• When a modular input is needed, a Heavy Forwarder is needed, as the Universal Forwarder does not include a bundled version of Python, which is required for most modular inputs2.

Explanation: A monitored log file is changing on the forwarder, but Splunk searches are not finding any new data that has been added. This could be caused by two possible reasons: B. An admin has removed the Splunk fishbucket on the forwarder. C. The last 256 bytes of the monitored file are not changing. Option B is correct because the Splunk fishbucket is a directory that stores information about the files that have been monitored by Splunk, such as the file name, size, modification time, and CRC checksum. If an admin removes the fishbucket, Splunk will lose track of the files that have been previously indexed and will not index any new data from those files. Option C is correct because Splunk uses the CRC checksum of the last 256 bytes of a monitored file to determine if the file has changed since the last time it was read. If the last 256 bytes of the file are not changing, Splunk will assume that the file is unchanged and will not index any new data from it. Option A is incorrect because running the splunk clean eventdata -index command on the indexer will delete all the data from the specified index, but it will not affect the forwarder’s ability to send new data to the indexer. Option D is incorrect because Splunk does not use the first 256 bytes of a monitored file to determine if the file has changed.

Explanation:
Number of concurrent users: This is an important factor because it affects the search performance and resource utilization of the Splunk environment. More users mean more concurrent searches, which require more CPU, memory, and disk I/O. The number of concurrent users also determines the search head capacity and the search head clustering configuration12.
Volume of incoming data: This is another crucial factor because it affects the indexing performance and storage requirements of the Splunk environment. More data means more indexing throughput, which requires more CPU, memory, and disk I/O. The volume of incoming data also determines the indexer capacity and the indexer clustering configuration13.
Existence of premium apps: This is a relevant factor because some premium apps, such as Splunk Enterprise Security and Splunk IT Service Intelligence, have additional requirements and recommendations for the Splunk environment. For example, Splunk Enterprise Security requires a dedicated search head cluster and a minimum of 12 CPU cores per search head. Splunk IT Service Intelligence requires a minimum of 16 CPU cores and 64 GB of RAM per search head45.

Explanation: 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.

Explanation: 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.

Explanation:

• 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.

Explanation: 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.