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| Section | Weight | Objectives |
|---|---|---|
| Forwarder & Deployment Best Practices | 6% | - Data collection and forwarding optimization - Deployment server and configuration management - Forwarder tier design and configuration |
| Large-Scale Deployment Design | 5% | - High availability and scalability - Enterprise architecture patterns - Security and compliance design |
| Search Head Cluster | 8% | - Scaling and member lifecycle management - Architecture and deployment - Deployer and captaincy management |
| Multisite Indexer Cluster | 8% | - Disaster recovery and high availability - Configuration and cross-site operations - Geographic deployment planning |
| Indexer Cluster Administration & Operations | 7% | - App bundle distribution and management - Storage management and monitoring - Peer node maintenance and decommission |
| Troubleshooting Methodology & Tools | 14% | - Resolve configuration, search, and deployment issues - Log analysis and internal indexes - Cluster and forwarding problem resolution - Diagnostic tools and Splunk support model |
| Infrastructure Planning | 12% | - Resource sizing: CPU, memory, storage, network - Topology design for ES, ITSI, and security - Index design, retention, and data management |
| Deployment Planning & Requirements Definition | 7% | - Identify relevant applications and solutions - Collect and analyze project and environment requirements - Define deployment methodology and process |
| Performance Monitoring & Tuning | 5% | - Search performance optimization - Configuration tuning: limits.conf, indexes.conf, props.conf - System and indexer performance monitoring |
| Clustering Concepts & Overview | 5% | - Search head cluster fundamentals - Indexer cluster fundamentals - Storage and replication requirements |
| Single-site Indexer Cluster | 8% | - Upgrade and migration considerations - Configuration and deployment - Replication factor, search factor, and management |
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NEW QUESTION # 96
When should a dedicated deployment server be used?
Answer: C
Explanation:
A dedicated deployment server is a Splunk instance that manages the distribution of configuration updates and apps to a set of deployment clients, such as forwarders, indexers, or search heads. A dedicated deployment server should be used when there are more than 50 deployment clients, because this number exceeds the recommended limit for a non-dedicated deployment server. A non-dedicated deployment server is a Splunk instance that also performs other roles, such as indexing or searching. Using a dedicated deployment server can improve the performance, scalability, and reliability of the deployment process. Option C is the correct answer. Option A is incorrect because the number of search peers does not affect the need for a dedicated deployment server. Search peers are indexers that participate in a distributed search. Option B is incorrect because the number of apps to deploy does not affect the need for a dedicated deployment server. Apps are packages of configurations and assets that provide specific functionality or views in Splunk. Option D is incorrect because the number of server classes does not affect the need for a dedicated deployment server. Server classes are logical groups of deployment clients that share the same configuration updates and apps12
1: https://docs.splunk.com/Documentation/Splunk/9.1.2/Updating/Aboutdeploymentserver 2:
https://docs.splunk.com/Documentation/Splunk/9.1.2/Updating/Whentousedeploymentserver
NEW QUESTION # 97
Why should intermediate forwarders be avoided when possible?
Answer: B
Explanation:
Intermediate forwarders are forwarders that receive data from other forwarders and then send that data to indexers. They can be useful in some scenarios, such as when network bandwidth or security constraints prevent direct forwarding to indexers, or when data needs to be routed, cloned, or modified in transit.
However, intermediate forwarders also introduce additional complexity and overhead to the data pipeline, which can affect the performance and reliability of data ingestion. Therefore, intermediate forwarders should be avoided when possible, and used only when there is a clear benefit or requirement for them. Some of the drawbacks of intermediate forwarders are:
* They increase the number of hops and connections in the data flow, which can introduce latency and increase the risk of data loss or corruption.
* They consume more resources on the hosts where they run, such as CPU, memory, disk, and network bandwidth, which can affect the performance of other applications or processes on those hosts.
* They require additional configuration and maintenance, such as setting up inputs, outputs, load balancing, security, monitoring, and troubleshooting.
* They can create data duplication or inconsistency if they are not configured properly, such as when using cloning or routing rules.
Some of the references that support this answer are:
* Configure an intermediate forwarder, which states: "Intermediate forwarding is where a forwarder receives data from one or more forwarders and then sends that data on to another indexer. This kind of setup is useful when, for example, you have many hosts in different geographical regions and you want to send data from those forwarders to a central host in that region before forwarding the data to an indexer. All forwarder types can act as an intermediate forwarder. However, this adds complexity to your deployment and can affect performance, so use it only when necessary."
* Intermediate data routing using universal and heavy forwarders, which states: "This document outlines a variety of Splunk options for routing data that address both technical and business requirements.
Overall benefits Using splunkd intermediate data routing offers the following overall benefits: ... The routing strategies described in this document enable flexibility for reliably processing data at scale.
Intermediate routing enables better security in event-level data as well as in transit. The following is a list of use cases and enablers for splunkd intermediate data routing: ... Limitations splunkd intermediate data routing has the following limitations: ... Increased complexity and resource consumption. splunkd intermediate data routing adds complexity to the data pipeline and consumes resources on the hosts where it runs. This can affect the performance and reliability of data ingestion and other applications or processes on those hosts. Therefore, intermediate routing should be avoided when possible, and used only when there is a clear benefit or requirement for it."
* Use forwarders to get data into Splunk Enterprise, which states: "The forwarders take the Apache data and send it to your Splunk Enterprise deployment for indexing, which consolidates, stores, and makes the data available for searching. Because of their reduced resource footprint, forwarders have a minimal performance impact on the Apache servers. ... Note: You can also configure a forwarder to send data to another forwarder, which then sends the data to the indexer. This is called intermediate forwarding.
However, this adds complexity to your deployment and can affect performance, so use it only when necessary."
NEW QUESTION # 98
metrics. log is stored in which index?
Answer: C
Explanation:
According to the Splunk documentation1, metrics.log is a file that contains various metrics data for reviewing product behavior, such as pipeline, queue, thruput, and tcpout_connections. Metrics.log is stored in the
_internal index by default2, which is a special index that contains internal logs and metrics for Splunk Enterprise. The other options are false because:
* main is the default index for user data, not internal data3.
* _telemetry is an index that contains data collected by the Splunk Telemetry feature, which sends anonymous usage and performance data to Splunk4.
* _introspection is an index that contains data collected by the Splunk Monitoring Console, which monitors the health and performance of Splunk components.
NEW QUESTION # 99
Which of the following is an indexer clustering requirement?
Answer: B
Explanation:
Explanation
An indexer clustering requirement is that the cluster members must share the same license pool and license master. A license pool is a group of licenses that are assigned to a set of Splunk instances. A license master is a Splunk instance that manages the distribution and enforcement of licenses in a pool. In an indexer cluster, all cluster members must belong to the same license pool and report to the same license master, to ensure that the cluster does not exceed the license limit and that the license violations are handled consistently. An indexer cluster does not require shared storage, because each cluster member has its own local storage for the index data. An indexer cluster does not have to reside on a dedicated rack, because the cluster members can be located on different physical or virtual machines, as long as they can communicate with each other. An indexer cluster does not have to have at least three members, because a cluster can have as few as two members, although this is not recommended for high availability
NEW QUESTION # 100
How does the average run time of all searches relate to the available CPU cores on the indexers?
Answer: C
Explanation:
The average run time of all searches increases as the number of CPU cores on the indexers decreases. The CPU cores are the processing units that execute the instructions and calculations for the data. The number of CPU cores on the indexers affects the search performance, because the indexers are responsible for retrieving and filtering the data from the indexes. The more CPU cores the indexers have, the faster they can process the data and return the results. The less CPU cores the indexers have, the slower they can process the data and return the results. Therefore, the average run time of all searches is inversely proportional to the number of CPU cores on the indexers. The average run time of all searches is not independent of the number of CPU cores on the indexers, because the CPU cores are an important factor for the search performance. The average run time of all searches does not decrease as the number of CPU cores on the indexers decreases, because this would imply that the search performance improves with less CPU cores, which is not true. The average run time of all searches does not increase as the number of CPU cores on the indexers increases, because this would imply that the search performance worsens with more CPU cores, which is not true
NEW QUESTION # 101
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