According to the Splunk Core Consultant study guide, the correct mapping for the deployment of a new environment for a customer is Option D. This is because it follows the PS best practices for mapping, which include the use of the org_cluster_search_base, org_cluster_indexer_base, and org_all_indexes indexes. Additionally, Option D also includes the use of the etc/apps and etc/master-apps directories, which are recommended for the deployment of a new environment.  References :

Splunk Core Consultant study guide

Splunk Core Consultant test blueprint

 The Search Job Inspector can be used to debug searches if the search has not expired. This means that the search artifact still exists on the search head and can be inspected for performance and error information. The Search Job Inspector can be accessed from the Job menu in Splunk Web, or by using the btool command with the job_inspector option. The search does not need to be running or queued to use the Search Job Inspector, as long as it has not expired. Therefore, the correct answer is A, if the search has not expired.  References  :=

View search job properties

Use btool to troubleshoot configurations

 The customer can resolve the issue by modifying the blacklisted lookup definition stanza to specify setting allow_caching=true. This option allows the lookup to be cached on the search head and used for searches, without being included in the search bundle that is distributed to the indexers. This way, the customer can reduce the bundle size and avoid the error messages. Therefore, the correct answer is B, the blacklisted lookup definition stanza needs to be modified to specify setting allow_caching=true.  References  :=

Configure distributed search

Use lookups in distributed search

The most efficient search is the one that retrieves the least amount of data from the indexes and performs the least amount of processing on the search head. Among the four options, the most efficient search is D, (index=www) OR (index=sales) | search (index=www status=200 uri=/cart/checkout) OR (index=sales) | stats count, sum(revenue) as total_revenue by session_id | table total_revenue session_id. This is because:

It uses a base search to limit the data to only two indexes, www and sales, which are relevant for the query.

It uses a subsearch to further filter the data by status and uri for the www index, and by index for the sales index.

It uses a stats command to aggregate the data by session_id and calculate the count and total revenue.

It uses a table command to display only the required fields.

The other options are less efficient for various reasons:

Option A uses an append command, which is expensive and can cause memory issues. It also does not filter the data by status and uri for the www index, which can retrieve more data than needed.

Option B uses a boolean OR operator, which can be slower than a subsearch. It also does not filter the data by status and uri for the www index, which can retrieve more data than needed.

Option C does not use a base search to limit the data to specific indexes, which can retrieve more data than needed. It also uses an append command, which is expensive and can cause memory issues.

Therefore, the correct answer is D, (index=www) OR (index=sales) | search (index=www status=200 uri=/cart/checkout) OR (index=sales) | stats count, sum(revenue) as total_revenue by session_id | table total_revenue session_id.  References  :=

Quick tips for optimization

About search optimization

The Secret to a Great Splunk Search

How to make efficient and fast searches

The search can be rewritten to maximize efficiency by using the index option. The index option is used to specify the index to search. This option is useful when you have multiple indexes and want to search only one of them. The index option is also useful when you want to search a specific index that is not the default index. The index option can reduce the search time and resource consumption by limiting the scope of the search. Therefore, the correct answer is C. Option C, which uses the index option to search only the main index for the sourcetype web_access.  References :

Splunk Core Certified Consultant Test Blueprint

Splunk Documentation: Specify indexes in your search

Splunk Documentation: Use the index option

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.  References :

Splunk Core Consultant knowledge source documents or study guide: https://www.splunk.com/en_us/resources/splunk-certification-exam-study-guide.html

Splunk Test Blueprint Consultant: https://www.splunk.com/en_us/pdfs/training/splunk-test-blueprint-consultant.pdf

Plan a tiered deployment server topology 1

The data retention controls that must be configured to ensure that at least one year of logs are retained for both Windows and Firewall events are maxTotalDataSizeMB and frozenTimePeriodInSecs. These settings are defined in the indexes.conf file, which specifies the index settings and data retention policies for Splunk. The maxTotalDataSizeMB setting determines the maximum size of an index, in megabytes. When the index reaches this size, the oldest data is frozen (deleted or archived). The frozenTimePeriodInSecs setting determines the maximum age of the data in an index, in seconds. When the data exceeds this age, it is frozen. Therefore, by setting these values appropriately for the Windows and Firewall indexes, the customer can ensure that at least one year of logs are retained.  References :

Splunk Core Certified Consultant Test Blueprint

Splunk Documentation: Set up multiple indexes

Splunk Documentation: Configure index size and data retention

The Monitoring Console (MC) is a Splunk app that provides a comprehensive view of the health and performance of a Splunk environment. The MC can be configured to monitor a single instance or a distributed deployment. To monitor a distributed deployment, the MC instance needs to be configured as a search head that can run distributed searches across the other instances in the environment. Therefore, the MC instance needs to have the other search heads, the deployment server, the license master, and the cluster master/master node as distributed search peers. The MC instance does not need to have the indexers as distributed search peers, because the cluster master/master node already provides access to the indexed data in the cluster. Therefore, the correct answer is C. Search heads, deployment server, license master, cluster master/master node.  References :

Splunk Core Certified Consultant Test Blueprint

Splunk Documentation: About the Monitoring Console

Splunk Documentation: Configure a Monitoring Console instance

Splunk Documentation: Add search peers