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Splunk SPLK-4001 Exam Syllabus Topics:

Section	Weight	Objectives
Intro to Alerting on Metrics using Detectors	10%	- Make a solo detector - Clone an existing detector - Make the detector from a chart - Make a muting rule
Introduction to Metric Visualization	15%	- Use rollups and analytical tools correctly - Create charts and dashboards - Differentiate between several chart visualization types - Create widgets and showcase groups - Visualize a measure in a chart - Look for metrics - Analyze data in charts
Create Efficient Dashboards and Alerts	10%	- Create single-instance dashboard panels - View dashboard happenings - Include instructions on interfaces - Configure personal information linkages
Monitor Using Built-in Content	10%	- Interact with data using built-in content - Correctly interpret data in charts based on rollups, analytic functions, and chart resolution - Subscribe to alerts - Use the Kubernetes Navigator to investigate problems with nodes, pods, and containers - Use the Cluster Analyzer to pinpoint the root of some problems
Metrics Concepts	15%	- Data resolution, rollups - Discriminate between types of metadata - List the components of a datapoint - Define components of the Splunk IM Data Model, Metrics, MTS, datapoints
Get Metrics In with OpenTelemetry	10%	- Troubleshooting common errors - Edit the configuration - Deploy the OTel Collector on Linux - General OpenTelemetry Concepts - Configure the OTel Collector

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Splunk O11y Cloud Certified Metrics User Sample Questions (Q30-Q35):

NEW QUESTION # 30
What kind of metadata is sent with a datapoint

A. Tags
B. Properties
C. Sources
D. Dimensions

Answer: D

Explanation:
Dimensions are the metadata sent with a datapoint. They describe the context of the metric, such as the source, host, environment, or other identifying attributes used to filter and group metric data.

NEW QUESTION # 31
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?

A. Add a filter to narrow the scope of the measurement.
B. Add a restricted scope adjustment to the plot.
C. Select the Sharded option when creating the plot.
D. When creating the plot, add a discriminator.

Answer: A

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 # 32
A user wants to compare current CPU usage to the same time yesterday on the same chart.
Which analytic function should they use?

A. Dense
B. Timeshift
C. Bottom
D. Rate

Answer: B

Explanation:
The Timeshift function shifts a signal by a specified time interval, allowing users to overlay and compare current data against historical data, such as the same period the previous day.

NEW QUESTION # 33
A customer wants to build a chart that shows the top 5 hosts by memory usage. Which analytic function should they apply?

A. Integrate
B. Top
C. Delta
D. Sum

Answer: B

Explanation:
The Top analytic function ranks time series based on their values and returns the specified number of highest-ranking series, making it ideal for identifying the top N hosts by a given metric.

NEW QUESTION # 34
What is the finest resolution that Calendar Window Transformation datapoints can be calculated and displayed?

A. 1 hour resolution
B. The coarsest resolution of any signal on the chart
C. 1 second resolution
D. The native resolution of the input time series

Answer: D

Explanation:
Calendar Window Transformation datapoints are calculated and displayed at the native resolution of the input time series, ensuring that the aggregation respects the original granularity of the metric data.

NEW QUESTION # 35
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