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Splunk SPLK-4001 Exam Overview:

Certification Vendor:Splunk
Exam Name:Splunk O11y Cloud Certified Metrics User Exam
Exam Number:SPLK-4001
Exam Format:Multiple Choice
Real Exam Qty:54
Exam Duration:60 minutes
Exam Price:$130 USD
Available Languages:English
Recommended Training:OpenTelemetry Fundamentals
Splunk Observability Cloud Training
Exam Registration:Splunk Certification Track (Official)
Pearson VUE Registration (via Splunk portal)
Sample Questions:Splunk SPLK-4001 Sample Questions
Exam Way:Online or onsite proctored exam via Pearson VUE
Pre Condition:None
Official Syllabus URL:https://www.splunk.com/en_us/training/certification-track/splunk-o11y-cloud-certified-metrics-user.html

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The Splunk SPLK-4001 Exam consists of 65 questions that are to be completed in 90 minutes. The questions are in a multiple-choice format with a passing score of 70% or higher. Splunk O11y Cloud Certified Metrics User certification is valid for two years and must be renewed after the expiration date. There is a registration fee to take the exam, and the exam can be taken at any Pearson VUE test center or online through remote proctoring. Splunk O11y Cloud Certified Metrics User certification exam requires thorough preparation, including self-study, practice tests, and attending Splunk training courses.

Splunk O11y Cloud Certified Metrics User Sample Questions (Q11-Q16):

NEW QUESTION # 11
A Software Engineer is troubleshooting an issue with memory utilization in their application. They released a new canary version to production and now want to determine if the average memory usage is lower for requests with the 'canary' version dimension. They've already opened the graph of memory utilization for their service.
How does the engineer see if the new release lowered average memory utilization?

Answer: D

Explanation:
Explanation
The correct answer is C. On the chart for plot A, select Add Analytics, then select Mean:Aggregation. In the window that appears, select 'version' from the Group By field.
This will create a new plot B that shows the average memory utilization for each version of the application.
The engineer can then compare the values of plot B for the 'canary' and 'stable' versions to see if there is a significant difference.
To learn more about how to use analytics functions in Splunk Observability Cloud, you can refer to this documentation1.
1: https://docs.splunk.com/Observability/gdi/metrics/analytics.html


NEW QUESTION # 12
Which of the following are accurate reasons to clone a detector? (select all that apply)

Answer: A,C

Explanation:
According to the Splunk Test Blueprint - O11y Cloud Metrics User document1, one of the alerting concepts that is covered in the exam is detectors and alerts. Detectors are the objects that define the conditions for generating alerts, and alerts are the notifications that are sent when those conditions are met.
The Splunk O11y Cloud Certified Metrics User Track document2 states that one of the recommended courses for preparing for the exam is Alerting with Detectors, which covers how to create, modify, and manage detectors and alerts.
In the Alerting with Detectors course, there is a section on Cloning Detectors, which explains that cloning a detector creates a copy of the detector with all its settings, rules, and alert recipients.
The document also provides some reasons why you might want to clone a detector, such as:
To modify the rules without affecting the existing detector. This can be useful if you want to test different thresholds or conditions before applying them to the original detector. To explore how a detector was created without risk of changing it. This can be helpful if you want to learn from an existing detector or use it as a template for creating a new one. Therefore, based on these documents, we can conclude that A and D are accurate reasons to clone a detector.


NEW QUESTION # 13
What happens when the limit of allowed dimensions is exceeded for an MTS?

Answer: D

Explanation:
According to the web search results, dimensions are metadata in the form of key-value pairs that monitoring software sends in along with the metrics. The set of metric time series (MTS) dimensions sent during ingest is used, along with the metric name, to uniquely identify an MTS.
Splunk Observability Cloud has a limit of 36 unique dimensions per MTS. If the limit of allowed dimensions is exceeded for an MTS, the additional dimensions are dropped and not stored or indexed by Observability Cloud. This means that the data point is still ingested, but without the extra dimensions. Therefore, option A is correct.


NEW QUESTION # 14
Changes to which type of metadata result in a new metric time series?

Answer: B

Explanation:
The correct answer is A. Dimensions.
Dimensions are metadata in the form of key-value pairs that are sent along with the metrics at the time of ingest. They provide additional information about the metric, such as the name of the host that sent the metric, or the location of the server. Along with the metric name, they uniquely identify a metric time series (MTS)1 Changes to dimensions result in a new MTS, because they create a different combination of metric name and dimensions. For example, if you change the hostname dimension from host1 to host2, you will create a new MTS for the same metric name1 Properties, sources, and tags are other types of metadata that can be applied to existing MTSes after ingest. They do not contribute to uniquely identify an MTS, and they do not create a new MTS when changed2 To learn more about how to use metadata in Splunk Observability Cloud, you can refer to this documentation2.
1: https://docs.splunk.com/Observability/metrics-and-metadata/metrics.html#Dimensions 2: https://docs.splunk.com/Observability/metrics-and-metadata/metrics-dimensions-mts.html


NEW QUESTION # 15
When writing a detector with a large number of MTS, such as memory. free in a deployment with 30,000 hosts, it is possible to exceed the cap of MTS that can be contained in a single plot. Which of the choices below would most likely reduce the number of MTS below the plot cap?

Answer: D

Explanation:
The correct answer is B. Add a filter to narrow the scope of the measurement.
A filter is a way to reduce the number of metric time series (MTS) that are displayed on a chart or used in a detector. A filter specifies one or more dimensions and values that the MTS must have in order to be included. For example, if you want to monitor the memory.free metric only for hosts that belong to a certain cluster, you can add a filter like cluster:my-cluster to the plot or detector. This will exclude any MTS that do not have the cluster dimension or have a different value for it1 Adding a filter can help you avoid exceeding the plot cap, which is the maximum number of MTS that can be contained in a single plot. The plot cap is 100,000 by default, but it can be changed by contacting Splunk Support2 To learn more about how to use filters in Splunk Observability Cloud, you can refer to this documentation3.
1: https://docs.splunk.com/Observability/gdi/metrics/search.html#Filter-metrics 2: https://docs.splunk.com/Observability/gdi/metrics/detectors.html#Plot-cap 3: https://docs.splunk.com/Observability/gdi/metrics/search.html


NEW QUESTION # 16
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