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Download DemoVendor: Splunk
Certifications: Splunk Certifications
Exam Code: SPLK-4001
Exam Name: Splunk O11y Cloud Certified Metrics User
Updated: Jan 02, 2025
Q&As: 54
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What happens when the limit of allowed dimensions is exceeded for an MTS?
A. The additional dimensions are dropped.
B. The datapoint is averaged.
C. The datapoint is updated.
D. The datapoint is dropped.
Correct Answer: A
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.
Which of the following aggregate analytic functions will allow a user to see the highest or lowest n values of a metric?
A. Maximum / Minimum
B. Best/Worst
C. Exclude / Include
D. Top / Bottom
Correct Answer: D
The correct answer is D. Top / Bottom. Top and bottom are aggregate analytic functions that allow a user to see the highest or lowest n values of a metric. They can be used to select a subset of the time series in the plot by count or by percent. For example, top (5) will show the five time series with the highest values in each time period, while bottom (10%) will show the 10% of time series with the lowest values in each time period To learn more about how to use top and bottom functions in Splunk Observability Cloud, you can refer to this documentation.
A customer has a large population of servers. They want to identify the servers where utilization has increased the most since last week. Which analytics function is needed to achieve this?
A. Rate
B. Sum transformation
C. Tlmeshift
D. Standard deviation
Correct Answer: C
The correct answer is C. Timeshift.
According to the Splunk Observability Cloud documentation1, timeshift is an analytic function that allows you to compare the current value of a metric with its value at a previous time interval, such as an hour ago or a week ago. You can use
the timeshift function to measure the change in a metric over time and identify trends, anomalies, or patterns. For example, to identify the servers where utilization has increased the most since last week, you can use the following SignalFlow
code:
timeshift(1w, counters("server.utilization"))
This will return the value of the server.utilization counter metric for each server one week ago. You can then subtract this value from the current value of the same metric to get the difference in utilization. You can also use a chart to visualize
the results and sort them by the highest difference in utilization.
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