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Splunk SPLK-4001 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Metrics Concepts	15%	- Core Metrics Data Model 1. Splunk IM data model, metrics, MTS, datapoints 2. Data resolution and rollups 3. Components of a datapoint 4. Types of metadata
Topic 2: Finding Insights Using Analytics	15%	- Metrics Analytics 1. Moving and calendar window analytics 2. Combining plots in charts 3. Ratios and percentage trends 4. Subset analysis of MTS signals 5. Aggregation across sources 6. Time-based comparisons
Topic 3: Detectors for Common Use Cases	15%	- Advanced Detector Scenarios 1. Non-flapping detectors 2. Ephemeral infrastructure monitoring 3. Large-scale monitoring 4. Population monitoring 5. Cyclic pattern monitoring 6. Troubleshoot detectors 7. Detect common issues
Topic 4: Get Metrics In with OpenTelemetry	10%	- OpenTelemetry Collector Deployment 1. Deploy the OTel Collector on Linux 2. Configure the OTel Collector 3. General OpenTelemetry concepts 4. Edit configuration files 5. Troubleshooting common errors
Topic 5: Introduction to Visualizing Metrics	15%	- Metrics Visualization 1. Create charts and dashboards 2. Visualization types 3. Apply rollups and analytics functions 4. Search and visualize metrics 5. Dashboard groups
Topic 6: Create Efficient Dashboards and Alerts	10%	- Dashboard Optimization 1. Single-instance dashboards 2. Alert customization 3. Event overlays 4. Dashboard instructions 5. Troubleshooting charts and alerts 6. Data links configuration
Topic 7: Monitor Using Built-in Content	10%	- Observability Navigation & Monitoring 1. Interpret charts using rollups and analytics functions 2. Cluster Analyzer troubleshooting 3. Use alerts and detectors 4. Interact with built-in dashboards and content 5. Kubernetes Navigator usage
Topic 8: 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

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最新的 Splunk O11y Cloud Certified SPLK-4001 免費考試真題 (Q33-Q38):

問題 #33
An SRE creates a new detector to receive an alert when server latency is higher than 260 milliseconds. Latency below 260 milliseconds is healthy for their service. The SRE creates a New Detector with a Custom Metrics Alert Rule for latency and sets a Static Threshold alert condition at 260ms. How can the number of alerts be reduced?

A. Choose another signal.
B. Adjust the Trigger sensitivity. Duration set to 1 minute.
C. Adjust the notification sensitivity. Duration set to 1 minute.
D. Adjust the threshold.

答案：B

解題說明：
According to the Splunk O11y Cloud Certified Metrics User Track document, trigger sensitivity is a setting that determines how long a signal must remain above or below a threshold before an alert is triggered. By default, trigger sensitivity is set to Immediate, which means that an alert is triggered as soon as the signal crosses the threshold. This can result in a lot of alerts, especially if the signal fluctuates frequently around the threshold value. To reduce the number of alerts, you can adjust the trigger sensitivity to a longer duration, such as 1 minute, 5 minutes, or 15 minutes.
This means that an alert is only triggered if the signal stays above or below the threshold for the specified duration. This can help filter out noise and focus on more persistent issues.

問題 #34
A DevOps engineer wants to determine if the latency their application experiences is growing fester after a new software release a week ago. They have already created two plot lines, A and B, that represent the current latency and the latency a week ago, respectively. How can the engineer use these two plot lines to determine the rate of change in latency?

A. Create a temporary plot by clicking the Change% button in the upper-right corner of the plot showing lines A and B.
B. Create a plot C using the formula (A-B) and add a scale:percent function to express the rate of change as a percentage.
C. Create a temporary plot by dragging items A and B into the Analytics Explorer window.
D. Create a plot C using the formula (A/B-l) and add a scale: 100 function to express the rate of change as a percentage.

答案：D

解題說明：
The correct answer is C. Create a plot C using the formula (A/B-l) and add a scale: 100 function to express the rate of change as a percentage.
To calculate the rate of change in latency, you need to compare the current latency (plot A) with the latency a week ago (plot B). One way to do this is to use the formula (A/B-l), which gives you the ratio of the current latency to the previous latency minus one. This ratio represents how much the current latency has increased or decreased relative to the previous latency. For example, if the current latency is 200 ms and the previous latency is 100 ms, then the ratio is (200/100-l) = 1, which means the current latency is 100% higher than the previous latency1 To express the rate of change as a percentage, you need to multiply the ratio by 100. You can do this by adding a scale: 100 function to the formula. This function scales the values of the plot by a factor of 100. For example, if the ratio is 1, then the scaled value is 100%2 To create a plot C using the formula (A/B-l) and add a scale: 100 function, you need to follow these steps:
Select plot A and plot B from the Metric Finder.
Click on Add Analytics and choose Formula from the list of functions.
In the Formula window, enter (A/B-l) as the formula and click Apply.
Click on Add Analytics again and choose Scale from the list of functions.
In the Scale window, enter 100 as the factor and click Apply.
You should see a new plot C that shows the rate of change in latency as a percentage.
To learn more about how to use formulas and scale functions in Splunk Observability Cloud, you can refer to these documentations34.
1: https://www.mathsisfun.com/numbers/percentage-change.html 2: https://docs.splunk.com/Observability/gdi/metrics/analytics.html#Scale 3: https://docs.splunk.com/Observability/gdi/metrics/analytics.html#Formula 4: https://docs.splunk.com/Observability/gdi/metrics/analytics.html#Scale

問題 #35
In the Splunk distribution of the OpenTelemetry Collector, what is the difference between the agent_config.yaml and the splunk-otel-collector.conf files?

A. splunk-otel-collector.conf defines the OpenTelemetry pipeline, and agent_config.yaml sets endpoint URLs and access tokens.
B. agent_config.yaml defines the OpenTelemetry pipeline, and splunk-otel-collector.conf sets endpoint URLs and access tokens.
C. agent_config.yaml configures the gateway's address and splunk-otel-collector.conf sets the memory limits for the collector.
D. splunk-otel-collector.conf configures processors and agent_config.yaml sets the memory limits for the collector.

答案：A

問題 #36
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. Select the Sharded option when creating the plot.
C. When creating the plot, add a discriminator.
D. Add a restricted scope adjustment to the plot.

答案：A

解題說明：
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

問題 #37
What are the best practices for creating detectors? (select all that apply)

A. Have a consistent type of measurement.
B. Have a consistent value.
C. View data at highest resolution.
D. View detector in a chart.

答案：A,B,C,D

解題說明：
Explanation
The best practices for creating detectors are:
View data at highest resolution. This helps to avoid missing important signals or patterns in the data that could indicate anomalies or issues1 Have a consistent value. This means that the metric or dimension used for detection should have a clear and stable meaning across different sources, contexts, and time periods. For example, avoid using metrics that are affected by changes in configuration, sampling, or aggregation2 View detector in a chart. This helps to visualize the data and the detector logic, as well as to identify any false positives or negatives. It also allows to adjust the detector parameters and thresholds based on the data distribution and behavior3 Have a consistent type of measurement. This means that the metric or dimension used for detection should have the same unit and scale across different sources, contexts, and time periods. For example, avoid mixing bytes and bits, or seconds and milliseconds.
1: https://docs.splunk.com/Observability/gdi/metrics/detectors.html#Best-practices-for-detectors 2:
https://docs.splunk.com/Observability/gdi/metrics/detectors.html#Best-practices-for-detectors 3:
https://docs.splunk.com/Observability/gdi/metrics/detectors.html#View-detector-in-a-chart :
https://docs.splunk.com/Observability/gdi/metrics/detectors.html#Best-practices-for-detectors

問題 #38
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