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Splunk SPLK-4001 Exam Syllabus Topics:

Section	Weight	Objectives
Finding Insights Using Analytics	15%	- Metrics Analytics 1. Ratios and percentage trends 2. Subset analysis of MTS signals 3. Combining plots in charts 4. Time-based comparisons 5. Moving and calendar window analytics 6. Aggregation across sources
Get Metrics In with OpenTelemetry	10%	- OpenTelemetry Collector Deployment 1. Configure the OTel Collector 2. Edit configuration files 3. General OpenTelemetry concepts 4. Deploy the OTel Collector on Linux 5. Troubleshooting common errors
Introduction to Visualizing Metrics	15%	- Metrics Visualization 1. Create charts and dashboards 2. Search and visualize metrics 3. Dashboard groups 4. Apply rollups and analytics functions 5. Visualization types
Alerting on Metrics with Detectors	10%	- Detectors and Alerting 1. Standalone detectors 2. Create detectors from charts 3. Muting rules 4. Clone and manage detectors
Monitor Using Built-in Content	10%	- Observability Navigation & Monitoring 1. Interpret charts using rollups and analytics functions 2. Use alerts and detectors 3. Kubernetes Navigator usage 4. Interact with built-in dashboards and content 5. Cluster Analyzer troubleshooting
Create Efficient Dashboards and Alerts	10%	- Dashboard Optimization 1. Event overlays 2. Data links configuration 3. Single-instance dashboards 4. Alert customization 5. Dashboard instructions 6. Troubleshooting charts and alerts
Detectors for Common Use Cases	15%	- Advanced Detector Scenarios 1. Cyclic pattern monitoring 2. Large-scale monitoring 3. Population monitoring 4. Ephemeral infrastructure monitoring 5. Troubleshoot detectors 6. Non-flapping detectors 7. Detect common issues
Metrics Concepts	15%	- Core Metrics Data Model 1. Types of metadata 2. Data resolution and rollups 3. Splunk IM data model, metrics, MTS, datapoints 4. Components of a datapoint

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Splunk O11y Cloud Certified Metrics User Sample Questions (Q70-Q75):

NEW QUESTION # 70
Which of the following aggregate analytic functions will allow a user to see the highest or lowest n values of a metric?

A. Best/Worst
B. Maximum / Minimum
C. Exclude / Include
D. Top / Bottom

Answer: D

Explanation:
Explanation
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 period1 To learn more about how to use top and bottom functions in Splunk Observability Cloud, you can refer to this documentation1.

NEW QUESTION # 71
A customer is sending in datapoints regarding the number of API calls made to a particular service. The datapoints are being sent every 10 seconds, and represent the number of API calls seen in the last 10 seconds. What metric type is this?

A. Cumulative Counter
B. Numeric
C. Gauge
D. Counter

Answer: C

Explanation:
A gauge metric represents a value measured at a specific point in time or over a defined interval.
In this scenario, the datapoints indicate the number of API calls observed in each 10-second interval, which aligns with the characteristics of a gauge metric.

NEW QUESTION # 72
What Pod conditions does the Analyzer panel in Kubernetes Navigator monitor? (select all that apply)

A. Unknown
B. Not Scheduled
C. Failed
D. Pending

Answer: A,B,C,D

Explanation:
The Pod conditions that the Analyzer panel in Kubernetes Navigator monitors are:
Not Scheduled: This condition indicates that the Pod has not been assigned to a Node yet. This could be due to insufficient resources, node affinity, or other scheduling constraints. Unknown:
This condition indicates that the Pod status could not be obtained or is not known by the system.
This could be due to communication errors, node failures, or other unexpected situations. Failed:
This condition indicates that the Pod has terminated in a failure state. This could be due to errors in the application code, container configuration, or external factors. Pending: This condition indicates that the Pod has been accepted by the system, but one or more of its containers has not been created or started yet. This could be due to image pulling, volume mounting, or network issues.

NEW QUESTION # 73
A customer wants the ability to drill down from a property in one dashboard to another dashboard so they can correlate content. What is the best way to achieve this?

A. Property Data Links
B. Dashboard Data Links
C. Local Data Links
D. Global Data Links

Answer: C

Explanation:
Local Data Links allow users to drill down from a property on one dashboard to another dashboard, enabling correlation of related content while maintaining context from the originating dashboard.

NEW QUESTION # 74
Which of the following are supported rollup functions in Splunk Observability Cloud?

A. sigma, epsilon, pi, omega, beta, tau
B. std_dev, mean, median, mode, min, max
C. 1min, 5min, 10min, 15min, 30min
D. average, latest, lag, min, max, sum, rate

Answer: D

Explanation:
Explanation
According to the Splunk O11y Cloud Certified Metrics User Track document1, Observability Cloud has the following rollup functions: Sum: (default for counter metrics): Returns the sum of all data points in the MTS reporting interval. Average (default for gauge metrics): Returns the average value of all data points in the MTS reporting interval. Min: Returns the minimum data point value seen in the MTS reporting interval. Max:
Returns the maximum data point value seen in the MTS reporting interval. Latest: Returns the most recent data point value seen in the MTS reporting interval. Lag: Returns the difference between the most recent and the previous data point values seen in the MTS reporting interval. Rate: Returns the rate of change of data points in the MTS reporting interval. Therefore, option A is correct.

NEW QUESTION # 75
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