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Splunk SPLK-4001 Exam Syllabus Topics:

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

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Splunk O11y Cloud Certified Metrics User Sample Questions (Q54-Q59):

NEW QUESTION # 54
Which of the following statements is true of detectors created from a chart on a custom dashboard?

A. The detector is automatically linked to the chart.
B. Changes made to the chart affect the detector.
C. Changes made to the detector affect the chart.
D. The alerts will show up in the team landing page.

Answer: A

Explanation:
The correct answer is D. The detector is automatically linked to the chart.
When you create a detector from a chart on a custom dashboard, the detector is automatically linked to the chart. This means that you can see the detector status and alerts on the chart, and you can access the detector settings from the chart menu. You can also unlink the detector from the chart if you want to1 Changes made to the chart do not affect the detector, and changes made to the detector do not affect the chart. The detector and the chart are independent entities that have their own settings and parameters. However, if you change the metric or dimension of the chart, you might lose the link to the detector1 The alerts generated by the detector will show up in the Alerts page, where you can view, manage, and acknowledge them. You can also see them on the team landing page if you assign the detector to a team2 To learn more about how to create and link detectors from charts on custom dashboards, you can refer to this documentation1.
1: https://docs.splunk.com/observability/alerts-detectors-notifications/link-detectors-to-charts.html 2: https://docs.splunk.com/observability/alerts-detectors-notifications/view-manage-alerts.html

NEW QUESTION # 55
What is the recommended approach to monitor a large number of metric time series (MTS)?

A. Use dimensions to filter and break down MTS into smaller groups.
B. Use an MTS policy to group MTS.
C. Use one of the aggregation functions over time window to group MTS.
D. Use one of the aggregation functions to group MTS.

Answer: A

Explanation:
Using dimensions to filter and break down metric time series allows you to organize and manage large numbers of MTS efficiently. Dimensions provide context and enable grouping, filtering, and targeted analysis without overwhelming dashboards or alerts.

NEW QUESTION # 56
Which of the following are accurate reasons to clone a detector? (select all that apply)

A. To explore how a detector was created without risk of changing it.
B. To reduce the amount of billed TAPM for the detector.
C. To modify the rules without affecting the existing detector.
D. To add an additional recipient to the detector's alerts.

Answer: A,C

Explanation:
The correct answers are A and D.
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. B and C are not valid reasons because:
Cloning a detector does not reduce the amount of billed TAPM for the detector. TAPM stands for Tracked Active Problem Metric, which is a metric that has been alerted on by a detector. Cloning a detector does not change the number of TAPM that are generated by the original detector or the clone.
Cloning a detector does not add an additional recipient to the detector's alerts. Cloning a detector copies the alert recipients from the original detector, but it does not add any new ones. To add an additional recipient to a detector's alerts, you need to edit the alert settings of the detector.

NEW QUESTION # 57
To smooth a very spiky cpu.utilization metric, what is the correct analytic function to better see if the cpu. utilization for servers is trending up over time?

A. Rate/Sec
B. Mean (Transformation)
C. Median
D. Mean (by host)

Answer: B

Explanation:
According to the web search results, a mean transformation is an analytic function that returns the average value of a metric or a dimension over a specified time interval. A mean transformation can be used to smooth a very spiky metric, such as cpu.utilization, by reducing the impact of outliers and noise. A mean transformation can also help to see if the metric is trending up or down over time, by showing the general direction of the average value. For example, to smooth the cpu.utilization metric and see if it is trending up over time, you can use the following SignalFlow code:
mean(1h, counters("cpu.utilization"))
This will return the average value of the cpu.utilization counter metric for each metric time series (MTS) over the last hour. You can then use a chart to visualize the results and compare the mean values across different MTS.

NEW QUESTION # 58
A customer wants to create a chart that adds two metrics together to give a total. What is the best method to achieve this?

A. Edit the existing metrics under Metric Metadata in the UI.
B. Use a formula in another plot that adds them both together.
C. Input both metrics into the same plot signal.
D. Create a new metric that adds them both together.

Answer: B

Explanation:
A formula plot is the best way to combine existing metric plots mathematically. By creating another plot that adds the two metric signals together, the chart can display their combined total without changing the original metrics.

NEW QUESTION # 59
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