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The Splunk O11y Cloud Certified Metrics User certification exam is available online and can be taken from anywhere in the world. SPLK-4001 Exam consists of 60 multiple-choice questions and candidates have two hours to complete the exam. Candidates who pass the exam will receive the Splunk O11y Cloud Certified Metrics User certification, which is valid for two years.
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Splunk SPLK-4001 certification exam is designed for IT professionals who want to demonstrate their expertise in using Splunk to monitor, analyze, and troubleshoot cloud-based applications and infrastructure. SPLK-4001 Exam is part of the Splunk O11y (Observability) Cloud Certification program, which is a series of exams that validate different aspects of Splunk’s cloud-based monitoring and analytics capabilities.
NEW QUESTION # 123
Which of the following is optional, but highly recommended to include in a datapoint?
Answer: A
Explanation:
A metric type is an optional, but highly recommended field that specifies the kind of measurement that a datapoint represents. For example, a metric type can be gauge, counter, cumulative counter, or histogram. A metric type helps Splunk Observability Cloud to interpret and display the data correctly.
NEW QUESTION # 124
A customer wants to find the total number of transmission errors that occurred over a discrete period of time. Assuming that the metric type is Cumulative Counter, which of the following combinations of rollup and analytic function could be used to accomplish this?
Answer: D
Explanation:
For a cumulative counter, the Delta rollup calculates the change in the counter value over each interval. Applying the Sum Transformation analytic function then adds those deltas together to get the total number of transmission errors over the selected time period.
NEW QUESTION # 125
For which types of charts can individual plot visualization be set?
Answer: A
Explanation:
Explanation
The correct answer is C. Line, Area, Column.
For line, area, and column charts, you can set the individual plot visualization to change the appearance of each plot in the chart. For example, you can change the color, shape, size, or style of the lines, areas, or columns. You can also change the rollup function, data resolution, or y-axis scale for each plot1 To set the individual plot visualization for line, area, and column charts, you need to select the chart from the Metric Finder, then click on Plot Chart Options and choose Individual Plot Visualization from the list of options. You can then customize each plot according to your preferences2 To learn more about how to use individual plot visualization in Splunk Observability Cloud, you can refer to this documentation2.
1: https://docs.splunk.com/Observability/gdi/metrics/charts.html#Individual-plot-visualization 2:
https://docs.splunk.com/Observability/gdi/metrics/charts.html#Set-individual-plot-visualization
NEW QUESTION # 126
Which component of the OpenTelemetry Collector allows for the modification of metadata?
Answer: B
Explanation:
The component of the OpenTelemetry Collector that allows for the modification of metadata is A. Processors.
Processors are components that can modify the telemetry data before sending it to exporters or other components. Processors can perform various transformations on metrics, traces, and logs, such as filtering, adding, deleting, or updating attributes, labels, or resources. Processors can also enrich the telemetry data with additional metadata from various sources, such as Kubernetes, environment variables, or system information1 For example, one of the processors that can modify metadata is the attributes processor. This processor can update, insert, delete, or replace existing attributes on metrics or traces. Attributes are key-value pairs that provide additional information about the telemetry data, such as the service name, the host name, or the span kind2 Another example is the resource processor. This processor can modify resource attributes on metrics or traces. Resource attributes are key-value pairs that describe the entity that produced the telemetry data, such as the cloud provider, the region, or the instance type3 To learn more about how to use processors in the OpenTelemetry Collector, you can refer to this documentation1.
1: https://opentelemetry.io/docs/collector/configuration/#processors 2: https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/processor/attributesprocessor 3: https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/processor/resourceprocessor
NEW QUESTION # 127
A customer is experiencing issues getting metrics from a new receiver they have configured in the OpenTelemetry Collector. How would the customer go about troubleshooting further with the logging exporter?
Answer: C
Explanation:
The logging exporter is a component that allows the OpenTelemetry Collector to send traces, metrics, and logs directly to the console. It can be used to diagnose and troubleshoot issues with telemetry received and processed by the Collector, or to obtain samples for other purposes. To activate the logging exporter, you need to add it to the pipeline that you want to diagnose. In this case, since you are experiencing issues with a new receiver for metrics, you need to add the logging exporter to the metrics receiver pipeline. This will create a new plot that shows the metrics received by the Collector and any errors or warnings that might occur. The image that you have sent with your question shows how to add the logging exporter to the metrics receiver pipeline. You can see that the exporters section of the metrics pipeline includes logging as one of the options. This means that the metrics received by any of the receivers listed in the receivers section will be sent to the logging exporter as well as to any other exporters listed.
NEW QUESTION # 128
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