SPLK-3003 Exam Dumps

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: A default behavior of a search head cluster captain is that it is a cluster member who performs normal search activities. This means that the captain can run searches, display dashboards, access knowledge objects, and perform other functions that any other search head can do. The captain also has additional responsibilities, such as coordinating artifact replication, managing search affinity, handling search head failures, and electing a new captain if needed.

Explanation: A subsearch is a search that runs within another search, and provides input to the outer search. A subsearch is useful when the input to the outer search is not known in advance, but depends on the results of another search. A subsearch is also useful when the input to the outer search is too large to be specified manually, but can be generated by another search. Therefore, a subsearch is the most appropriate in the scenario when dynamically filtering hosts. For example, if we want to filter the hosts that have a certain value of a field, we can use a subsearch to find those hosts and pass them to the outer search. For example:

This search will return the events from the main index that have a host value that matches the subsearch. The subsearch will find the hosts that have more than 100 events with status 404 in the access_combined sourcetype, and pass them to the outer search as a list of values. This way, we can dynamically filter the hosts based on another search criterion.

The other scenarios are not as suitable for using a subsearch. When joining results from multiple indexes, we can use the join command or append command instead of a subsearch. When filtering indexed fields, we can use the where command or the search command instead of a subsearch. When joining multiple large datasets, we can use the map command or the multisearch command instead of a subsearch.

Explanation:
Carefully design smaller apps with specific configuration that can be reused. This is the Splunk PS recommendation when using the deployment server and building deployment apps, because it allows for more flexibility, modularity, and efficiency in managing and deploying updates to Splunk Enterprise instances. Smaller apps with specific configuration can be easily reused across different server classes, environments, and use cases, without causing conflicts or redundancies. They can also reduce the size of the deployment bundle and the network bandwidth consumption.
The other options are incorrect because they are not the Splunk PS recommendation when using the deployment server and building deployment apps. Option B is incorrect because deploying only Splunk PS base configurations via the deployment server limits the functionality and customization of the deployment server, as it does not allow for deploying other types of apps, such as add-ons, dashboards, or custom configurations. Option C is incorrect because using $SPLUNK_HOME/etc/system/local configurations on forwarders and only deploying TAs via the deployment server is not a good practice, as it makes the forwarder configuration harder to manage and troubleshoot, and it does not leverage the full potential of the deployment server. Option D is incorrect because carefully designing bigger apps containing multiple configs is not a good practice, as it makes the deployment apps more complex, less reusable, and more prone to errors and conflicts.

Explanation: The recommended solution to reduce the number of connection failures to the deployment server (DS) is to create a tiered deployment server topology. A tiered deployment server topology is a way of organizing the deployment server and its clients into multiple levels or tiers, where each tier has a different phone home interval and a different set of apps to deploy.
This way, the deployment server can handle more clients without being overwhelmed by frequent connections and large app deployments. A tiered deployment server topology can also improve the performance and scalability of the deployment server, as well as reduce the network bandwidth consumption and latency. The other options are incorrect because they either do not solve the problem or they make it worse.
Option B is incorrect because reducing the phone home interval to 6 seconds will increase the number of connection failures to the DS, as it will make the clients connect more often and put more load on the DS.
Option C is incorrect because leaving the phone home interval at 60 seconds will not reduce the number of connection failures to the DS, as it will not change the current situation.
Option D is incorrect because increasing the phone home interval to 600 seconds will reduce the number of connection failures to the DS, but it will also reduce the responsiveness and reliability of the deployment server, as it will make the clients connect less often and delay the app deployments.

Explanation: The correct process and procedure for migrating a Splunk index cluster to new hardware is as follows:
Install new indexers. This step involves installing the Splunk Enterprise software on the new machines and configuring them with the same network settings, OS settings, and hardware specifications as the original indexers.
Configure indexers into the cluster as peers; ensure they receive the cluster bundle and the same configuration as original peers. This step involves joining the new indexers to the existing cluster as peer nodes, using the same cluster master and replication factor. The new indexers should also receive the same configuration files as the original peers, either by copying them manually or by using a deployment server. The cluster bundle contains the indexes.conf file and other files that define the index settings and data retention policies for the cluster.
Decommission old peers one at a time. This step involves removing the old indexers from the cluster gracefully, using the splunk offline command or the REST API endpoint /services/cluster/master/control/control/decommission. This ensures that the cluster master redistributes the primary buckets from the old peers to the new peers, and that no data is lost during the migration process.
Remove old peers from the CM’s list. This step involves deleting the old indexers from the list of peer nodes maintained by the cluster master, using the splunk remove server command or the REST API endpoint /services/cluster/master/peers. This ensures that the cluster master does not try to communicate with the old peers or assign them any search or replication tasks.
Update forwarders to forward to the new peers. This step involves updating the outputs.conf file on the forwarders that send data to the cluster, so that they point to the new indexers instead of the old ones. This ensures that the data ingestion process is not disrupted by the migration.