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| Section | Weight | Objectives |
|---|---|---|
| License Management | 5% | - License types and enforcement
|
| Data Inputs and Indexing | 10% | - Data ingestion and indexing
|
| Users, Roles, and Security | - Authentication and authorization
| |
| Splunk Admin Basics | 5% | - Splunk architecture fundamentals
|
| Search and Knowledge Objects | - Knowledge object management
| |
| Splunk Configuration Files | 5% | - Configuration management
|
| Monitoring and Maintenance | - Operational administration
|
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NEW QUESTION # 45
A security team needs to ingest a static file for a specific incident. The log file has not been collected previously and future updates to the file must not be indexed.
Which command would meet these needs?
Answer: D
Explanation:
Explanation
The correct answer is A. splunk add one shot / opt/ incident [data . log -index incident According to the Splunk documentation1, the splunk add one shot command adds a single file or directory to the Splunk index and then stops monitoring it. This is useful for ingesting static files that do not change or update. The command takes the following syntax:
splunk add one shot <file> -index <index_name>
The file parameter specifies the path to the file or directory to be indexed. The index parameter specifies the name of the index where the data will be stored. If the index does not exist, Splunk will create it automatically.
Option B is incorrect because the splunk edit monitor command modifies an existing monitor input, which is used for ingesting files or directories that change or update over time. This command does not create a new monitor input, nor does it stop monitoring after indexing.
Option C is incorrect because the splunk add monitor command creates a new monitor input, which is also used for ingesting files or directories that change or update over time. This command does not stop monitoring after indexing.
Option D is incorrect because the splunk edit oneshot command does not exist. There is no such command in the Splunk CLI.
References:1:Monitor files and directories with inputs.conf - Splunk Documentation
NEW QUESTION # 46
How is a remote monitor input distributed to forwarders?
Answer: D
Explanation:
https://docs.splunk.com/Documentation/Splunk/8.0.5/Data/Usingforwardingagents Scroll down to the section Titled, How to configure forwarder inputs, and subsection Here are the main ways that you can configure data inputs on a forwarder Install the app or add-on that contains the inputs you wants
NEW QUESTION # 47
A Splunk index has the following configuration:
Assume hot buckets only roll based on size. What is the correct bucket life cycle for the data?
Answer: C
Explanation:
Based on the configuration in the buttercupstanza, the lifecycle of the buckets follows this path:
1. Hot: New data is written to hot buckets. These are the active buckets where data is being indexed.
2. Warm: Once the hot bucket reaches its size limit (maxDataSize = 10000), it rolls over into a warm bucket. The warm bucket is where data is still searchable but no longer being actively written to.
3. Cold: Once the warm bucket reaches the maxWarmDBCount = 100, it rolls into cold storage, as specified in the configuration with the coldPathsetting.
4. Delete: When the cold bucket exceeds the total allowed data size (maxTotalDataSizeMB =
60000), older data is deleted according to the bucket lifecycle management settings.
NEW QUESTION # 48
Which data pipeline phase is the last opportunity for defining event boundaries?
Answer: D
Explanation:
Reference https://docs.splunk.com/Documentation/Splunk/8.2.3/Admin/Configurationparametersandthedatapipeline
NEW QUESTION # 49
Which Splunk component would one use to perform line breaking prior to indexing?
Answer: C
Explanation:
Explanation
According to the Splunk documentation1, a heavy forwarder is a Splunk Enterprise instance that can parse and filter data before forwarding it to an indexer. A heavy forwarder can perform line breaking, which is the process of splitting incoming data into individual events based on a set of rules2. A heavy forwarder can also apply other transformations to the data, such as field extractions, event type matching, or masking sensitive data3.
NEW QUESTION # 50
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