SPLK-3003 Exam Dumps

Explanation: These are the indexes.conf settings that can be leveraged to meet the requirements of the customer, given the following assumptions and calculations:
The customer has a single indexer with a single storage device for all data. The customer wants to keep 30 days of data searchable, which means 30 x 50GB = 1500GB of data in total.

The customer wants to optimize search performance for hourly scheduled searches that process a week’s worth of data, which means 7 x 50GB = 350GB of data per search.

The indexes.conf settings that can be used to achieve these goals are:
maxDataSize: This setting determines the maximum size of a bucket before it rolls from hot to warm. By setting this to auto_high_volume, Splunk software will create buckets that are approximately 10GB in size, which is suitable for high-volume data sources. This will result in about 5 hot buckets and 145 warm buckets per index, which will reduce the number of buckets that need to be searched and improve search performance.

frozenTimePeriodInSecs: This setting determines how long Splunk software keeps the data in an index before freezing or deleting it. By setting this to 2592000 seconds (30 days), Splunk software will ensure that the data is searchable for at least 30 days, and then move it to the frozen state or delete it according to the coldToFrozenDir or coldToFrozenScript settings.

maxVolumeDataSizeMB: This setting determines the maximum size of a volume before Splunk software stops writing data to it. By setting this to 1536000 MB (1500 GB), Splunk software will ensure that the volume can store exactly 30 days of data, and then roll the oldest buckets to frozen or delete them according to the frozenTimePeriodInSecs setting.

The other options are incorrect because they either do not meet the requirements of the customer or they contain invalid or unnecessary settings. Option A is incorrect because frozenTimePeriodInSecs and maxVolumeDataSizeMB are redundant settings, as they both control the retention policy of the index. Also, maxHotBuckets is not relevant for search performance, as it only affects how many hot buckets can exist per index.

Option B is incorrect because maxTotalDataSizeMB and maxGlobalDataSizeMB are not valid settings in indexes.conf, as they are only used in server.conf to control the total size of all indexes and all volumes respectively. Also, maxHotBuckets is not relevant for search performance, as it only affects how many hot buckets can exist per index.

Option D is incorrect because homePath.maxDataSizeMB and maxHotSpanSecs are not valid settings in indexes.conf, as they are only used in volumes.conf to control the size and time span of hot buckets within a volume respectively. Also, maxWarmDBCount is not relevant for search performance, as it only affects how many warm buckets can exist per index.

Explanation: When Splunk indexes events, it extracts metadata fields such as host, source, and source type from the raw data. These fields are used to identify and categorize the events, and to enable efficient searching and filtering. Splunk also assigns a unique identifier (_cd) and a timestamp (_time) to each event. Splunk does not extract the top 10 fields, perform parsing, merging, and typing processes on universal forwarders, or create report acceleration summaries during indexing. These are separate processes that occur either before or after indexing. Therefore, the correct answer is B. Extracts metadata fields such as host, source, source type.

Explanation: To set up the HTTP Event Collector (HEC), each HEC input entry must contain a valid token. A token is a string of alphanumeric characters that acts as an identifier and an authentication code for the HEC input. You can generate a token when you create a new HEC input or use an existing token for multiple inputs. A token is required for sending data to HEC and for managing the HEC input settings.

Explanation: The SHC will function as expected as the minimum required number of nodes for a SHC is 3. This is because the SHC uses a quorum-based algorithm to determine the cluster state and elect the captain. A quorum is a majority of cluster members that can communicate with each other. As long as a quorum exists, the cluster can continue to operate normally and serve search requests. If a network outage occurs between the two data centers, each data center will have three SHC members, but only one of them will have a quorum. The data center with the quorum will elect a new captain if the previous one was in the other data center, and the other data center will lose its cluster status and stop serving searches until the network communication is restored.
The other options are incorrect because they do not reflect what happens when a network outage occurs between two data centers with a SHC. Option A is incorrect because the SHC deployer will not become the new captain, as it is not part of the SHC and does not participate in cluster activities. Option B is incorrect because the SHC will not stop all scheduled search activity, as it will still run scheduled searches on the data center with the quorum. Option D is incorrect because the SHC captain will not fall back to previous active captain in the remaining site, as it will be elected by the quorum based on several factors, such as load, availability, and priority.

Explanation: Splunk does not support overlapping usernames between internal Splunk authentication and LDAP. If a username exists in both $SPLUNK_HOME/etc/passwd and LDAP, Splunk will try to use the internal Splunk authentication first, as explained in the previous question. However, if the user tries to change their password or edit their account settings, Splunk will error with a message like "Cannot edit user: User exists in multiple realms". This is because Splunk cannot determine which authentication scheme to use for these actions. Therefore, it is recommended to avoid overlapping usernames between internal Splunk authentication and LDAP.

Explanation: In a single indexer cluster, the best practice is to install the Monitoring Console (MC) on the cluster master node. This is because the cluster master node has access to all the information about the cluster state, such as the bucket status, the peer status, the search head status, and the replication and search factors. The MC can use this information to monitor the health and performance of the cluster and alert on any issues or anomalies. The MC can also run distributed searches across all the peer nodes and collect metrics and logs from them.
The other options are incorrect because they are not recommended locations for installing the MC in a single indexer cluster. Option A is incorrect because the deployer should not share with the master cluster, as this can cause conflicts and errors in applying configuration bundles to the cluster. Option B is incorrect because the license master is not a good candidate for hosting the MC, as it does not have direct access to the cluster information and it might have a high load from managing license usage for many clients.
Option D is incorrect because the production search head is not a good candidate for hosting the MC, as it might have a high load from serving user searches and dashboards, and it might not be able to run distributed searches across all the peer nodes if it is not part of the cluster.