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| Section | Objectives |
|---|---|
| Security and Authentication | - Encryption and data protection - Authentication mechanisms - Role-based access control (RBAC) |
| Search Head Architecture | - Search head clustering - Search performance optimization - Knowledge object distribution |
| Data Management and Indexing | - Index configuration and management - Data retention and lifecycle management - Parsing and indexing process |
| Indexer Clustering | - Failure recovery and resilience - Cluster master configuration - Replication and search factor management |
| Splunk Architecture Fundamentals | - Distributed architecture concepts - Data flow and pipeline architecture - Forwarder and indexer roles |
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NEW QUESTION # 125
Which of the following statements describe a Search Head Cluster (SHC) captain? (Select all that apply.)
Answer: B,C
Explanation:
Explanation
The following statements describe a search head cluster captain:
* Is the job scheduler for the entire search head cluster. The captain is responsible for scheduling and dispatching the searches that run on the search head cluster, as well as coordinating the search results from the search peers. The captain also ensures that the scheduled searches are balanced across the search head cluster members and that the search concurrency limits are enforced.
* Replicates the search head cluster's knowledge bundle to the search peers. The captain is responsible for creating and distributing the knowledge bundle to the search peers, which contains the knowledge objects that are required for the searches. The captain also ensures that the knowledge bundle is consistent and up-to-date across the search head cluster and the search peers. The following statements do not describe a search head cluster captain:
* Manages alert action suppressions (throttling). Alert action suppressions are the settings that prevent an alert from triggering too frequently or too many times. These settings are managed by the search head
* that runs the alert, not by the captain. The captain does not have any special role in managing alert action suppressions.
* Synchronizes the member list with the KV store primary. The member list is the list of search head cluster members that are active and available. The KV store primary is the search head cluster member that is responsible for replicating the KV store data to the other members. These roles are not related to the captain, and the captain does not synchronize them. The member list and the KV store primary are determined by the RAFT consensus algorithm, which is independent of the captain election. For more information, see [About the captain and the captain election] and [About KV store and search head clusters] in the Splunk documentation.
NEW QUESTION # 126
(The performance of a specific search is performing poorly. The search must run over All Time and is expected to have very few results. Analysis shows that the search accesses a very large number of buckets in a large index. What step would most significantly improve the performance of this search?)
Answer: C
Explanation:
As per Splunk Enterprise Search Performance documentation, the most significant factor affecting search performance when querying across a large number of buckets is disk I/O throughput. A search that spans "All Time" forces Splunk to inspect all historical buckets (hot, warm, cold, and potentially frozen if thawed), even if only a few events match the query. This dramatically increases the amount of data read from disk, making the search bound by I/O performance rather than CPU or memory.
Increasing the number of indexing pipelines (Option B) only benefits data ingestion, not search performance.
Changing to a real-time search (Option D) does not help because real-time searches are optimized for streaming new data, not historical queries. The indexed_realtime_use_by_default setting (Option C) applies only to streaming indexed real-time searches, not historical "All Time" searches.
To improve performance for such searches, Splunk documentation recommends enhancing disk I/O capability
- typically through SSD storage, increased disk bandwidth, or optimized storage tiers. Additionally, creating summary indexes or accelerated data models may help for repeated "All Time" queries, but the most direct improvement comes from faster disk performance since Splunk must scan large numbers of buckets for even small result sets.
References (Splunk Enterprise Documentation):
* Search Performance Tuning and Optimization
* Understanding Bucket Search Mechanics and Disk I/O Impact
* limits.conf Parameters for Search Performance
* Storage and Hardware Sizing Guidelines for Indexers and Search Heads
NEW QUESTION # 127
Splunk Enterprise platform instrumentation refers to data that the Splunk Enterprise deployment logs in the
_introspection index. Which of the following logs are included in this index? (Select all that apply.)
Answer: A,B
Explanation:
Explanation
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.
NEW QUESTION # 128
Which of the following statements about integrating with third-party systems is true? (Select all that apply.)
Answer: A,C
Explanation:
The following statements about integrating with third-party systems are true: You can use Splunk alerts to provision actions on a third-party system, and you can forward data from Splunk forwarder to a third-party system without indexing it first. Splunk alerts are triggered events that can execute custom actions, such as sending an email, running a script, or calling a webhook. Splunk alerts can be used to integrate with third-party systems, such as ticketing systems, notification services, or automation platforms. For example, you can use Splunk alerts to create a ticket in ServiceNow, send a message to Slack, or trigger a workflow in Ansible. Splunk forwarders are Splunk instances that collect and forward data to other Splunk instances, such as indexers or heavy forwarders. Splunk forwarders can also forward data to third-party systems, such as Hadoop, Kafka, or AWS Kinesis, without indexing it first. This can be useful for sending data to other data processing or storage systems, or for integrating with other analytics or monitoring tools. A Hadoop application cannot search data in Splunk, because Splunk does not provide a native interface for Hadoop applications to access Splunk data. Splunk can search data in the Hadoop File System (HDFS), but only by using the Hadoop Connect app, which is a Splunk app that enables Splunk to index and search data stored in HDFS
NEW QUESTION # 129
Which of the following statements describe licensing in a clustered Splunk deployment? (Select all that apply.)
Answer: A,C
Explanation:
Explanation/Reference: https://docs.splunk.com/Documentation/Splunk/7.3.2/Admin/Distdeploylicenses
NEW QUESTION # 130
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