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[Hardware] Professional SPLK-4001 Most Reliable Questions - Pass SPLK-4001 Exam

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【Hardware】 Professional SPLK-4001 Most Reliable Questions - Pass SPLK-4001 Exam

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The Splunk SPLK-4001 exam covers a range of topics, including understanding metrics, configuring and using cloud monitoring tools, designing dashboards and visualizations, and troubleshooting performance issues. SPLK-4001 Exam is intended to assess your ability to work with Splunk in a cloud environment and to demonstrate your proficiency in using the tool to identify and resolve performance issues.
Splunk O11y Cloud Certified Metrics User Sample Questions (Q42-Q47):NEW QUESTION # 42
What are the best practices for creating detectors? (select all that apply)
  • A. Have a consistent type of measurement.
  • B. View data at highest resolution.
  • C. Have a consistent value.
  • D. View detector in a chart.
Answer: A,B,C,D
Explanation:
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/Observab ... tices-for-detectors 2:
https://docs.splunk.com/Observab ... tices-for-detectors 3:
https://docs.splunk.com/Observab ... detector-in-a-chart :
https://docs.splunk.com/Observab ... tices-for-detectors

NEW QUESTION # 43
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 restricted scope adjustment to the plot.
  • B. When creating the plot, add a discriminator.
  • C. Add a filter to narrow the scope of the measurement.
  • D. Select the Sharded option when creating the plot.
Answer: C
Explanation:
Explanation
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/Observab ... html#Filter-metrics 2:
https://docs.splunk.com/Observab ... ctors.html#Plot-cap 3:
https://docs.splunk.com/Observability/gdi/metrics/search.html

NEW QUESTION # 44
Which of the following statements is true of detectors created from a chart on a custom dashboard?
  • A. The alerts will show up in the team landing page.
  • B. Changes made to the chart affect the detector.
  • C. Changes made to the detector affect the chart.
  • D. The detector is automatically linked to the chart.
Answer: D
Explanation:
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/observab ... tors-to-charts.html 2:
https://docs.splunk.com/observab ... -manage-alerts.html

NEW QUESTION # 45
Which analytic function can be used to discover peak page visits for a site over the last day?
  • A. Lag: (24h)
  • B. Count: (Id)
  • C. Maximum: Aggregation (Id)
  • D. Maximum: Transformation (24h)
Answer: D
Explanation:
According to the Splunk Observability Cloud documentation1, the maximum function is an analytic function that returns the highest value of a metric or a dimension over a specified time interval. The maximum function can be used as a transformation or an aggregation. A transformation applies the function to each metric time series (MTS) individually, while an aggregation applies the function to all MTS and returns a single value. For example, to discover the peak page visits for a site over the last day, you can use the following SignalFlow code:
maximum(24h, counters("page.visits"))
This will return the highest value of the page.visits counter metric for each MTS over the last 24 hours. You can then use a chart to visualize the results and identify the peak page visits for each MTS.

NEW QUESTION # 46
A Software Engineer is troubleshooting an issue with memory utilization in their application. They released a new canary version to production and now want to determine if the average memory usage is lower for requests with the 'canary' version dimension. They've already opened the graph of memory utilization for their service.
How does the engineer see if the new release lowered average memory utilization?
  • A. On the chart for plot A, select Add Analytics, then select MeanrTransformation. In the window that appears, select 'version' from the Group By field.
  • B. On the chart for plot A, scroll to the end and click Enter Function, then enter 'A/B-l'.
  • C. On the chart for plot A, click the Compare Means button. In the window that appears, type 'version1.
  • D. On the chart for plot A, select Add Analytics, then select Mean:Aggregation. In the window that appears, select 'version' from the Group By field.
Answer: D
Explanation:
The correct answer is C. On the chart for plot A, select Add Analytics, then select Mean:Aggregation. In the window that appears, select 'version' from the Group By field.
This will create a new plot B that shows the average memory utilization for each version of the application. The engineer can then compare the values of plot B for the 'canary' and 'stable' versions to see if there is a significant difference.
To learn more about how to use analytics functions in Splunk Observability Cloud, you can refer to this documentation1.
1: https://docs.splunk.com/Observability/gdi/metrics/analytics.html

NEW QUESTION # 47
......
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