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| Section | Weight | Objectives |
|---|---|---|
| Troubleshooting Methodology & Tools | 14% | - Cluster and forwarding problem resolution - Diagnostic tools and Splunk support model - Log analysis and internal indexes - Resolve configuration, search, and deployment issues |
| Forwarder & Deployment Best Practices | 6% | - Deployment server and configuration management - Forwarder tier design and configuration - Data collection and forwarding optimization |
| Search Head Cluster | 8% | - Deployer and captaincy management - Scaling and member lifecycle management - Architecture and deployment |
| Infrastructure Planning | 12% | - Resource sizing: CPU, memory, storage, network - Index design, retention, and data management - Topology design for ES, ITSI, and security |
| Indexer Cluster Administration & Operations | 7% | - App bundle distribution and management - Peer node maintenance and decommission - Storage management and monitoring |
| Performance Monitoring & Tuning | 5% | - Configuration tuning: limits.conf, indexes.conf, props.conf - System and indexer performance monitoring - Search performance optimization |
| Single-site Indexer Cluster | 8% | - Upgrade and migration considerations - Replication factor, search factor, and management - Configuration and deployment |
| Multisite Indexer Cluster | 8% | - Disaster recovery and high availability - Geographic deployment planning - Configuration and cross-site operations |
| Deployment Planning & Requirements Definition | 7% | - Collect and analyze project and environment requirements - Identify relevant applications and solutions - Define deployment methodology and process |
| Large-Scale Deployment Design | 5% | - High availability and scalability - Security and compliance design - Enterprise architecture patterns |
| Clustering Concepts & Overview | 5% | - Storage and replication requirements - Indexer cluster fundamentals - Search head cluster fundamentals |
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NEW QUESTION # 12
An indexer cluster is being designed with the following characteristics:
* 10 search peers
* Replication Factor (RF): 4
* Search Factor (SF): 3
* No SmartStore usage
How many search peers can fail before data becomes unsearchable?
Answer: B
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.
1: Configure the search factor
NEW QUESTION # 13
Which of the following are client filters available in serverclass.conf? (Select all that apply.)
Answer: B,D
Explanation:
Explanation/Reference: https://docs.splunk.com/Documentation/Splunk/7.3.1/Updating/ Filterclients#Define_filters_through_serverclass.conf
NEW QUESTION # 14
When converting from a single-site to a multi-site cluster, what happens to existing single-site clustered buckets?
Answer: C
Explanation:
Explanation/Reference: https://docs.splunk.com/Documentation/Splunk/7.3.2/Indexer/Migratetomultisite
NEW QUESTION # 15
Which of the following statements describe a Search Head Cluster (SHC) captain? (Select all that apply.)
Answer: A,B
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 # 16
A three-node search head cluster is skipping a large number of searches across time. What should be done to increase scheduled search capacity on the search head cluster?
Answer: B
Explanation:
Explanation
Changing the limits.conf value for max_searches_per_cpu to a higher value is the best option to increase scheduled search capacity on the search head cluster when a large number of searches are skipped across time.
This value determines how many concurrent scheduled searches can run on each CPU core of the search head.
Increasing this value will allow more scheduled searches to run at the same time, which will reduce the number of skipped searches. Creating a job server on the cluster, running the server.conf captain_is_adhoc_searchhead = true command, or adding another search head to the cluster are not the best options to increase scheduled search capacity on the search head cluster. For more information, see [Configure limits.conf] in the Splunk documentation.
NEW QUESTION # 17
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