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Splunk SPLK-4001 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Intro to Alerting on Metrics using Detectors10%- Make a solo detector
- Make a muting rule
- Clone an existing detector
- Make the detector from a chart
Topic 2: Monitor Using Built-in Content10%- Interact with data using built-in content
- Correctly interpret data in charts based on rollups, analytic functions, and chart resolution
- Use the Kubernetes Navigator to investigate problems with nodes, pods, and containers
- Use the Cluster Analyzer to pinpoint the root of some problems
- Subscribe to alerts
Topic 3: Create Efficient Dashboards and Alerts10%- Include instructions on interfaces
- Configure personal information linkages
- Create single-instance dashboard panels
- View dashboard happenings
Topic 4: Get Metrics In with OpenTelemetry10%- Deploy the OTel Collector on Linux
- General OpenTelemetry Concepts
- Troubleshooting common errors
- Edit the configuration
- Configure the OTel Collector
Topic 5: Introduction to Metric Visualization15%- Use rollups and analytical tools correctly
- Create charts and dashboards
- Differentiate between several chart visualization types
- Look for metrics
- Visualize a measure in a chart
- Create widgets and showcase groups
- Analyze data in charts
Topic 6: Metrics Concepts15%- Data resolution, rollups
- Define components of the Splunk IM Data Model, Metrics, MTS, datapoints
- List the components of a datapoint
- Discriminate between types of metadata

>> SPLK-4001更新 <<

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最新的 Splunk O11y Cloud Certified SPLK-4001 免費考試真題 (Q20-Q25):

問題 #20
What information is needed to create a detector?

答案:B

解題說明:
According to the Splunk Observability Cloud documentation, to create a detector, you need the following information:
Alert Signal: This is the metric or dimension that you want to monitor and alert on. You can select a signal from a chart or a dashboard, or enter a SignalFlow query to define the signal.
Alert Condition: This is the criteria that determines when an alert is triggered or cleared. You can choose from various built-in alert conditions, such as static threshold, dynamic threshold, outlier, missing data, and so on. You can also specify the severity level and the trigger sensitivity for each alert condition.
Alert Settings: This is the configuration that determines how the detector behaves and interacts with other detectors. You can set the detector name, description, resolution, run lag, max delay, and detector rules. You can also enable or disable the detector, and mute or unmute the alerts.
Alert Message: This is the text that appears in the alert notification and event feed. You can customize the alert message with variables, such as signal name, value, condition, severity, and so on. You can also use markdown formatting to enhance the message appearance.
Alert Recipients: This is the list of destinations where you want to send the alert notifications. You can choose from various channels, such as email, Slack, PagerDuty, webhook, and so on. You can also specify the notification frequency and suppression settings.


問題 #21
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?

答案:A

解題說明:
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 latency, 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%. 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.


問題 #22
Which of the following are supported rollup functions in Splunk Observability Cloud?

答案:D

解題說明:
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.


問題 #23
What constitutes a single metrics time series (MTS)?

答案:C

解題說明:
A metric time series (MTS) is a collection of data points that have the same metric and the same set of dimensions. For example, the following sets of data points are in three separate MTS:
MTS1: Gauge metric cpu.utilization, dimension "hostname": "host1"
MTS2: Gauge metric cpu.utilization, dimension "hostname": "host2"
MTS3: Gauge metric memory.usage, dimension "hostname": "host1"
A metric is a numerical measurement that varies over time, such as CPU utilization or memory usage. A dimension is a key-value pair that provides additional information about the metric, such as the hostname or the location. A data point is a combination of a metric, a dimension, a value, and a timestamp.


問題 #24
What information is needed to create a detector?

答案:B

解題說明:
Explanation
According to the Splunk Observability Cloud documentation1, to create a detector, you need the following information:
Alert Signal: This is the metric or dimension that you want to monitor and alert on. You can select a signal from a chart or a dashboard, or enter a SignalFlow query to define the signal.
Alert Condition: This is the criteria that determines when an alert is triggered or cleared. You can choose from various built-in alert conditions, such as static threshold, dynamic threshold, outlier, missing data, and so on. You can also specify the severity level and the trigger sensitivity for each alert condition.
Alert Settings: This is the configuration that determines how the detector behaves and interacts with other detectors. You can set the detector name, description, resolution, run lag, max delay, and detector rules. You can also enable or disable the detector, and mute or unmute the alerts.
Alert Message: This is the text that appears in the alert notification and event feed. You can customize the alert message with variables, such as signal name, value, condition, severity, and so on. You can also use markdown formatting to enhance the message appearance.
Alert Recipients: This is the list of destinations where you want to send the alert notifications. You can choose from various channels, such as email, Slack, PagerDuty, webhook, and so on. You can also specify the notification frequency and suppression settings.


問題 #25
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