Splunk O11y Cloud Certified Metrics User Exam SPLK-4001 Exam Questions in PDF

Free Splunk SPLK-4001 Dumps Questions (page: 2)

To refine a search for a metric a customer types host: test-*.
What does this filter return?

  1. Only metrics with a dimension of host and a value beginning with test-.
  2. Error
  3. Every metric except those with a dimension of host and a value equal to test.
  4. Only metrics with a value of test- beginning with host.

Answer(s): A

Explanation:

The correct answer is A. Only metrics with a dimension of host and a value beginning with test-. This filter returns the metrics that have a host dimension that matches the pattern test-. For example, test-01, test-abc, test-xyz, etc. The asterisk () is a wildcard character that can match any string of characters.
To learn more about how to filter metrics in Splunk Observability Cloud, you can refer to this documentation.
1: https://docs.splunk.com/Observability/gdi/metrics/search.html#Filter-metrics
2: https://docs.splunk.com/Observability/gdi/metrics/search.html



A customer operates a caching web proxy. They want to calculate the cache hit rate for their service.
What is the best way to achieve this?

  1. Percentages and ratios
  2. Timeshift and Bottom N
  3. Timeshift and Top N
  4. Chart Options and metadata

Answer(s): A

Explanation:

According to the Splunk O11y Cloud Certified Metrics User Track document., percentages and ratios are useful for calculating the proportion of one metric to another, such as cache hits to cache misses, or successful requests to failed requests. You can use the percentage() or ratio() functions in SignalFlow to compute these values and display them in charts. For example, to calculate the cache hit rate for a service, you can use the following SignalFlow code:
percentage(counters("cache.hits"), counters("cache.misses")) This will return the percentage of cache hits out of the total number of cache attempts. You can also use the ratio() function to get the same result, but as a decimal value instead of a percentage. ratio(counters("cache.hits"), counters("cache.misses"))



Which of the following are correct ports for the specified components in the OpenTelemetry Collector?

  1. gRPC (4000), SignalFx (9943), Fluentd (6060)
  2. gRPC (6831), SignalFx (4317), Fluentd (9080)
  3. gRPC (4459), SignalFx (9166), Fluentd (8956)
  4. gRPC (4317), SignalFx (9080), Fluentd (8006)

Answer(s): D

Explanation:

The correct answer is D. gRPC (4317), SignalFx (9080), Fluentd (8006). According to the web search results, these are the default ports for the corresponding components in the OpenTelemetry Collector. You can verify this by looking at the table of exposed ports and endpoints in the first result. You can also see the agent and gateway configuration files in the same result for more details.
1: https://docs.splunk.com/observability/gdi/opentelemetry/exposed-endpoints.html



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?

  1. Select the Sharded option when creating the plot.
  2. Add a filter to narrow the scope of the measurement.
  3. Add a restricted scope adjustment to the plot.
  4. When creating the plot, add a discriminator.

Answer(s): B

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 it. 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 Support.
To learn more about how to use filters in Splunk Observability Cloud, you can refer to this documentation.
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



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?

  1. Adjust the threshold.
  2. Adjust the Trigger sensitivity. Duration set to 1 minute.
  3. Adjust the notification sensitivity. Duration set to 1 minute.
  4. Choose another signal.

Answer(s): B

Explanation:

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.



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9/5/2022 10:54:00 PM

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9/7/2023 6:51:00 AM

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1/19/2024 8:15:00 AM

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5/30/2023 9:37:00 PM

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9/28/2023 8:25:00 PM

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9/18/2023 2:40:00 PM

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