SPLK-2002 Exam Dumps - Splunk Enterprise Certified Architect

According to the Splunk SmartStore Architecture Guide, the primary benefit of SmartStore is the separation of storage from compute resources within an indexer cluster. SmartStore enables Splunk to decouple indexer storage (data at rest) from the compute layer (indexers that perform searches and indexing).

With SmartStore, active (hot/warm) data remains on local disk for fast access, while older, less frequently searched (remote) data is stored in an external object storage system such as Amazon S3, Google Cloud Storage, or on-premises S3-compatible storage. This separation reduces the storage footprint on indexers, allowing organizations to scale compute and storage independently.

This architecture improves cost efficiency and scalability by:

Lowering on-premises storage costs using object storage for retention.

Enabling dynamic scaling of indexers without impacting total data availability.

Reducing replication overhead since SmartStore manages data objects efficiently.

SmartStore does not affect replication or search factors (Option A), does not handle Knowledge Object replication (Option C), and the Cluster Manager is still required (Option D) to coordinate cluster activities.

References (Splunk Enterprise Documentation):

• SmartStore Overview and Architecture Guide

• SmartStore Deployment and Configuration Manual

• Managing Storage and Compute Independence in Indexer Clusters

• Splunk Enterprise Capacity Planning – SmartStore Sizing Guidelines

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.

The following logs are included in the _introspection index, which contains data that the Splunk Enterprise deployment logs for platform instrumentation:

disk_objects.log. This log contains information about the disk objects that Splunk creates and manages, such as buckets, indexes, and files. This log can help monitor the disk space usage and the bucket lifecycle.

resource_usage.log. This log contains information about the resource usage of Splunk processes, such as CPU, memory, disk, and network. This log can help monitor the Splunk performance and identify any resource bottlenecks. The following logs are not included in the _introspection index, but rather in the _internal index, which contains data that Splunk generates for internal logging:

audit.log. This log contains information about the audit events that Splunk records, such as user actions, configuration changes, and search activity. This log can help audit the Splunk operations and security.

metrics.log. This log contains information about the performance metrics that Splunk collects, such as data throughput, data latency, search concurrency, and search duration. This log can help measure the Splunk performance and efficiency. For more information, see About Splunk Enterprise logging and [About the _introspection index] in the Splunk documentation.

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.