Pass the Splunk Core Certified Consultant SPLK-3003 Questions and answers with ExamsMirror

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. References:

Splunk Core Certified Consultant Test Blueprint

Splunk Documentation: How Splunk Enterprise indexes data

Splunk Documentation: About default fields

 A [script://] input sends data to a Splunk forwarder using the standard output (STDOUT) and standard error (STDERR) streams of the script. A [script://] input is a type of scripted input that runs an executable script on a Splunk forwarder and indexes the data that the script outputs to STDOUT or STDERR. The script can be written in any scripting language, such as Python, Perl, or shell, and it can perform various tasks, such as querying APIs, databases, or remote data interfaces, and formatting the data for indexing. The Splunk forwarder launches the script at a specified interval and reads the data from its STDOUT or STDERR streams.

The other options are incorrect because they are not the methods that a [script://] input uses to send data to a Splunk forwarder. Option A is incorrect because UDP stream is not a method that a [script://] input uses, but rather a method that a network input uses to receive data from UDP ports. Option B is incorrect because TCP stream is not a method that a [script://] input uses, but rather a method that a network input uses to receive data from TCP ports. Option C is incorrect because temporary file is not a method that a [script://] input uses, but rather a method that a monitor input uses to read data from files or directories. 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

Get data from APIs and other remote data interfaces through scripted inputs1

Configure scripted inputs2

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 inputs.conf stanzas in the image are attempting to monitor the files secure and messages in the /var/log directory. However, the whitelist attribute is set to “messages” and “secure” respectively, which means that only those files will be actively monitored. Therefore, the correct answer is D. /var/log/secure, /var/log/messages. References:

Splunk Core Certified Consultant Test Blueprint

Splunk Documentation: Monitor files and directories with inputs.conf

Splunk Documentation: Use whitelist and blacklist to filter inputs

The default push mode for a search head cluster deployer app configuration bundle is full. This means that the deployer pushes the entire app configuration bundle to the search head cluster members, overwriting any existing app configurations on the members. The full push mode ensures that the app configurations are consistent and synchronized across the cluster. The other push modes are merge_to_default, default_only, and local_only, which have different effects on how the app configurations are merged or overwritten on the cluster members. Therefore, the correct answer is A. full. References:

Splunk Core Certified Consultant Test Blueprint

Splunk Documentation: Deploy apps to a search head cluster

Splunk Documentation: Push configuration bundle

 The difference in the Splunk2Splunk payload traffic sent between a universal forwarder (UF) and indexer compared to the payload sent between a heavy forwarder (HF) and the indexer layer is that the UF sends a stream of data containing one set of metadata fields to represent the entire stream, whereas the HF sends individual events, each with their own metadata fields attached, resulting in a larger payload. This is because the UF does not parse or index the data before forwarding it, but rather sends it as raw data in 64K TCP chunks. The metadata fields, such as host, source, sourcetype, etc., are applied to the entire stream based on the inputs.conf configuration. The HF, on the other hand, parses and indexes the data before forwarding it, which means that it breaks the data into individual events and assigns metadata fields to each event based on props.conf and transforms.conf configuration. This results in a larger payload size, but also allows for more granular control over event processing and routing. References:

[Splunk Certification Exam Study Guide], page 14

[Splunk Documentation: How Splunk Enterprise processes incoming data]

[Splunk Documentation: Forwarding parsed data]

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

 Network latency is the time it takes for data to travel from one point to another, and storage IOPS is the number of input/output operations per second. These factors can affect the performance of the migration and should be taken into account when planning and executing the migration.

The CLI commands that you have shown in the image are used to adjust the maximum load that a peer node can handle during bucket replication and rebuilding. These settings can affect the performance and efficiency of an index cluster migration to new hardware. Therefore, some of the factors that you should consider when running these commands are:

Data ingestion rate: The higher the data ingestion rate, the more buckets will be created and need to be replicated or rebuilt across the cluster. This will increase the load on the peer nodes and the network bandwidth. You might want to lower the max_peer_build_load and max_peer_rep_load settings to avoid overloading the cluster during migration.

Network latency and storage IOPS: The network latency and storage IOPS are measures of how fast the data can be transferred and stored between the peer nodes. The lower these values are, the longer it will take for the cluster to replicate or rebuild buckets. You might want to increase the max_peer_build_load and max_peer_rep_load settings to speed up the migration process, but not too high that it causes errors or timeouts.

Distance and location: The distance and location of the peer nodes can also affect the network latency and bandwidth. If the peer nodes are located in different geographic regions or data centers, the data transfer might be slower and more expensive than if they are in the same location. You might want to consider using site replication factor and site search factor settings to optimize the cluster for multisite deployment.

SSL data encryption: If you enable SSL data encryption for your cluster, it will add an extra layer of security for your data, but it will also consume more CPU resources and network bandwidth. This might slow down the data transfer and increase the load on the peer nodes. You might want to balance the trade-off between security and performance when using SSL data encryption.

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

 The primary driver behind implementing indexer clustering in a customer’s environment is to provide higher availability for buckets of data. Indexer clustering is a feature of Splunk Enterprise that allows a group of indexers to replicate each other’s data, so that the system keeps multiple copies of all data. This process is known as index replication. By maintaining multiple, identical copies of Splunk Enterprise data, clusters prevent data loss while promoting data availability for searching. Indexer clustering also provides load balancing and failover capabilities for search and indexing operations.

The other options are incorrect because they are not the main reasons for using indexer clustering. Option A is incorrect because indexer clustering does not improve resiliency as the search load increases, but rather as the indexer load increases. Resiliency refers to the ability of the cluster to maintain search and indexing performance under stress or failure conditions. Option B is incorrect because indexer clustering does not reduce indexing latency, but rather increases it slightly due to the overhead of replication. Indexing latency refers to the time it takes for data to be indexed and searchable after ingestion. Option D is incorrect because indexer clustering does not scale out a Splunk environment to offer higher performance capability, but rather scales up a Splunk environment to offer higher availability and resiliency. Scaling out refers to adding more nodes to a distributed system to increase its capacity and throughput, while scaling up refers to adding more resources to existing nodes to increase their performance and reliability. 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

About indexer clusters and index replication1

Indexer cluster architecture overview2