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Splunk SPLK-4001 Exam Syllabus Topics:

Section Weight Objectives
Alerting with Detectors 15% - Threshold, anomaly, and multi-condition detectors
- Common use cases: latency, saturation, errors
- Notification rules and incident response
Analytics & Insights 10% - Aggregation, filtering, and transformation functions
- Correlation and pattern detection
Dashboards & Operational Efficiency 10% - Designing clear, performant dashboards
- Reducing alert fatigue and optimizing monitoring
Metrics Concepts 20% - Dimensions, time-series data, and cardinality
- Data retention and resolution settings
- Metric types: Gauges, Counters, Histograms, Summaries
Data Collection & Ingestion 15% - Integration with Kubernetes and cloud environments
- OpenTelemetry configuration and deployment
- Signal flow and data processing pipeline
Built-in Monitoring Content 10% - Using pre-built dashboards and navigators
- Content packs and quick-start monitoring
Visualizing Metrics 20% - Creating and configuring charts, graphs, and time-series
- Visualization best practices and effective communication
- Using SignalFlow for custom queries

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最新的 Splunk O11y Cloud Certified SPLK-4001 免費考試真題 (Q56-Q61):

問題 #56
When applying analytic functions to a subset of multiple time series (MTS) in a signal, what is the resulting data structure?

  • A. A single time series with aggregated values
  • B. Individual time series with separate calculations
  • C. A scatter plot showing the relationships between MTS
  • D. A combined time series with separate timestamps

答案：B


問題 #57
Which of the following rollups will display the time delta between a datapoint being sent and a datapoint being received?

  • A. Jitter
  • B. Delay
  • C. Lag
  • D. Latency

答案：C

解題說明：
According to the Splunk Observability Cloud documentation, lag is a rollup function that returns the difference between the most recent and the previous data point values seen in the metric time series reporting interval. This can be used to measure the time delta between a data point being sent and a data point being received, as long as the data points have timestamps that reflect their send and receive times. For example, if a data point is sent at 10:00:00 and received at 10:00:05, the lag value for that data point is 5 seconds.


問題 #58
Which of the following statements is true of detectors created from a chart on a custom dashboard?

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

答案：B

解題說明：
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


問題 #59
Which of the following are true about organization metrics? (select all that apply)

  • A. Organization metrics are included for free.
  • B. Organization metrics give insights into system usage, system limits, data ingested and token quotas.
  • C. A user can plot and alert on them like metrics they send to Splunk Observability Cloud.
  • D. Organization metrics count towards custom MTS limits.

答案：A,B,C

解題說明：
The correct answer is A, C, and D. Organization metrics give insights into system usage, system limits, data ingested and token quotas. Organization metrics are included for free. A user can plot and alert on them like metrics they send to Splunk Observability Cloud.
Organization metrics are a set of metrics that Splunk Observability Cloud provides to help you measure your organization's usage of the platform. They include metrics such as:
Ingest metrics: Measure the data you're sending to Infrastructure Monitoring, such as the number of data points you've sent.
App usage metrics: Measure your use of application features, such as the number of dashboards in your organization.
Integration metrics: Measure your use of cloud services integrated with your organization, such as the number of calls to the AWS CloudWatch API.
Resource metrics: Measure your use of resources that you can specify limits for, such as the number of custom metric time series (MTS) you've created1 Organization metrics are not charged and do not count against any system limits. You can view them in built-in charts on the Organization Overview page or in custom charts using the Metric Finder. You can also create alerts based on organization metrics to monitor your usage and performance1 To learn more about how to use organization metrics in Splunk Observability Cloud, you can refer to this documentation1.
1: https://docs.splunk.com/observability/admin/org-metrics.html


問題 #60
Which of the following aggregate analytic functions will allow a user to see the highest or lowest n values of a metric?

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

答案：C

解題說明：
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.


問題 #61
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