Splunk SPLK-2002 - Splunk Enterprise Certified Architect

According to the Splunk documentation1, the Search Job Inspector is a tool that you can use to troubleshoot search performance and understand the behavior of knowledge objects, such as event types, tags, lookups, and so on, within the search. You can inspect search jobs that are currently running or that have finished recently. The Search Job Inspector can help you investigate error messages that appear underneath the search bar in Splunk Web, as it can show you the details of the search job, such as the search string, the search mode, the search timeline, the search log, the search profile, and the search properties. You can use this information to identify the cause of the error and fix it2. The other options are false because:

Dashboard panels showing “Waiting for queued job to start” on page load is not a problem that can be investigated using the Search Job Inspector, as it indicates that the search job has not started yet. This could be due to the search scheduler being busy or the search priority being low. You can use the Jobs page or the Monitoring Console to monitor the status of the search jobs and adjust the priority or concurrency settings if needed3.

Different users seeing different extracted fields from the same search is not a problem that can be investigated using the Search Job Inspector, as it is related to the user permissions and the knowledge object sharing settings. You can use the Access Controls page or the Knowledge Manager to manage the user roles and the knowledge object visibility4.

Events not being sorted in reverse chronological order is not a problem that can be investigated using the Search Job Inspector, as it is related to the search syntax and the sort command. You can use the Search Manual or the Search Reference to learn how to use the sort command and its options to sort the events by any field or criteria.

According to the Splunk documentation1, the CHARSET setting in props.conf specifies the character set encoding of the source data. This setting has the least impact on indexing performance, as it only affects how Splunk interprets the bytes of the data, not how it processes or transforms the data. The other options are false because:

The SHOULD_LINEMERGE setting in props.conf determines whether Splunk breaks events based on timestamps or newlines. This setting has a significant impact on indexing performance, as it affects how Splunk parses the data and identifies the boundaries of the events2.

The TRUNCATE setting in props.conf specifies the maximum number of characters that Splunk indexes from a single line of a file. This setting has a moderate impact on indexing performance, as it affects how much data Splunk reads and writes to the index3.

The TIME_PREFIX setting in props.conf specifies the prefix that directly precedes the timestamp in the event data. This setting has a moderate impact on indexing performance, as it affects how Splunk extracts the timestamp and assigns it to the event

 The following statements are true regarding Splunk Enterprise performance:

Adding search peers increases the search throughput as search load increases. This is because adding more search peers distributes the search workload across more indexers, which reduces the load on each indexer and improves the search speed and concurrency.

Adding search heads provides additional CPU cores to run more concurrent searches. This is because adding more search heads increases the number of search processes that can run in parallel, which improves the search performance and scalability. The following statements are false regarding Splunk Enterprise performance:

Adding search peers does not increase the maximum size of search results. The maximum size of search results is determined by the maxresultrows setting in the limits.conf file, which is independent of the number of search peers.

Adding RAM to an existing search head does not provide additional search capacity. The search capacity of a search head is determined by the number of CPU cores, not the amount of RAM. Adding RAM to a search head may improve the search performance, but not the search capacity. For more information, see Splunk Enterprise performance in the Splunk documentation.

When adding or decommissioning a member from a Search Head Cluster (SHC), the proper order of operations is:

Delete Splunk Enterprise, if it exists.

Install and initialize the instance.

Join the SHC.

This order of operations ensures that the member has a clean and consistent Splunk installation before joining the SHC. Deleting Splunk Enterprise removes any existing configurations and data from the instance. Installing and initializing the instance sets up the Splunk software and the required roles and settings for the SHC. Joining the SHC adds the instance to the cluster and synchronizes the configurations and apps with the other members. The other order of operations are not correct, because they either skip a step or perform the steps in the wrong order.

 The splunk diag --exclude command is a way to exclude search artifacts when creating a diag. A diag is a diagnostic snapshot of a Splunk instance that contains various logs, configurations, and other information. Search artifacts are temporary files that are generated by search jobs and stored in the dispatch directory. Search artifacts can be excluded from the diag by using the --exclude option and specifying the dispatch directory. The splunk diag --debug --refresh command is a way to create a diag with debug logging enabled and refresh the diag if it already exists. The splunk diag --disable=dispatch command is not a valid command, because the --disable option does not exist. The splunk diag --filter-searchstrings command is a way to filter out sensitive information from the search strings in the diag

A single-site indexer cluster is a group of Splunk Enterprise instances that index and replicate data across the cluster1. A bucket is a directory that contains indexed data, along with metadata and other information2. A replication factor is the number of copies of each bucket that the cluster maintains1. A search factor is the number of searchable copies of each bucket that the cluster maintains1. A searchable copy is a copy that contains both the raw data and the index files3. A search head is a Splunk Enterprise instance that coordinates the search activities across the peer nodes1.

Option D is the correct answer because it reflects the definitions of replication factor and search factor. The cluster will ensure that there are at least three copies of each bucket, one on each peer node, to satisfy the replication factor of 3. The cluster will also ensure that there are at least two searchable copies of each bucket, one primary and one searchable, to satisfy the search factor of 2. The primary copy is the one that the search head uses to run searches, and the searchable copy is the one that can be promoted to primary if the original primary copy becomes unavailable3.

Option A is incorrect because it confuses the replication factor and the search factor. The cluster will ensure there are at least three copies of each bucket, not two, to meet the replication factor of 3. The cluster will ensure there are at least two copies of searchable metadata, not three, to meet the search factor of 2.

Option B is incorrect because it uses the wrong terms. The cluster will ensure there are at least, not at most, three copies of each bucket, to meet the replication factor of 3. The cluster will ensure there are at least, not at most, two copies of searchable metadata, to meet the search factor of 2.

Option C is incorrect because it has nothing to do with the replication factor or the search factor. The cluster does not limit the number of search heads that can access the bucket at the same time. The search head can search across multiple clusters, and the cluster can serve multiple search heads1.

1: The basics of indexer cluster architecture - Splunk Documentation 2: About buckets - Splunk Documentation 3: Search factor - Splunk Documentation

Comprehensive and Detailed Explanation (From Splunk Enterprise Documentation)Splunk’s official planning guidance explains that the deployment cycle begins with defining the system architecture, capacity planning, platform design, and topologies. Splunk states that before any component is installed, administrators must complete “infrastructure planning and buildout,” which includes determining indexer capacity, search head roles, clustering strategy, storage layout, and performance requirements. This foundational step ensures that all Splunk components have the proper hardware, network design, and scaling expectations.

After the environment is built, Splunk documentation states that the next stage is “deployment and data onboarding,” which includes configuring indexers, forwarders, parsing rules, event processing pipelines, data source validation, and enrichment steps such as field extractions, tagging, event types, and CIM alignment. Splunk describes this as the phase where you bring in data and confirm correctness, completeness, and normalization.

Only after the system is stable and populated with data does Splunk recommend “user planning and rollout”, which includes developing dashboards, roles, knowledge objects, search best practices, and enabling user access. Splunk emphasizes that user onboarding should occur last, once infrastructure and data pipelines are fully validated.

Splunk provides various methods to change the internal logging levels in a Splunk environment to troubleshoot an issue. All of the options are valid ways to do so. Option A is correct because the Monitoring Console (MC) allows the administrator to view and modify the logging levels of various Splunk components through a graphical interface. Option B is correct because the Splunk command line provides the splunk set log-level command to change the logging levels of specific components or categories. Option C is correct because the Splunk Web provides the Settings > Server settings > Server logging page to change the logging levels of various components through a web interface. Option D is correct because the log-local.cfg file allows the administrator to manually edit the logging levels of various components by overriding the default settings in the log.cfg file123

1: https://docs.splunk.com/Documentation/Splunk/9.1.2/Troubleshooting/Enabledebuglogging 2: https://docs.splunk.com/Documentation/Splunk/9.1.2/Admin/Serverlogging 3: https://docs.splunk.com/Documentation/Splunk/9.1.2/Admin/Loglocalcfg

 The Splunk Universal Forwarder is the only Splunk Enterprise offering that has its own license. The Splunk Universal Forwarder license allows the forwarder to send data to any Splunk Enterprise or Splunk Cloud instance without consuming any license quota. The Splunk Heavy Forwarder does not have its own license, but rather consumes the license quota of the Splunk Enterprise or Splunk Cloud instance that it sends data to. The Splunk Cloud Forwarder and the Splunk Forwarder Management are not separate Splunk Enterprise offerings, but rather features of the Splunk Cloud service. For more information, see [About forwarder licensing] in the Splunk documentation.

The curl https://serverhost:8089/services/admin/inputstatus/TailingProcessor:FileStatus command is used to check the status of the tailed files when troubleshooting monitor inputs. Monitor inputs are inputs that monitor files or directories for new data and send the data to Splunk for indexing. The TailingProcessor:FileStatus endpoint returns information about the files that are being monitored by the Tailing Processor, such as the file name, path, size, position, and status. The splunk cmd btool inputs list | tail command is used to list the inputs configurations from the inputs.conf file and pipe the output to the tail command. The splunk cmd btool check inputs layer command is used to check the inputs configurations for syntax errors and layering. The curl https://serverhost:8089/services/admin/inputstatus/TailingProcessor:Tailstatus command does not exist, and it is not a valid endpoint.