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The SPLK-4001 exam is an excellent way for individuals to demonstrate their expertise in Splunk's metrics and logging capabilities. By passing the exam, individuals can differentiate themselves in the job market and demonstrate their ability to monitor and troubleshoot complex systems in real-time.

The SPLK-4001 exam covers a range of topics, including data collection, metric analysis, alerting, and visualization. Candidates are required to demonstrate their knowledge of Splunk Observability Cloud's architecture, its various components and how they work together to provide a comprehensive monitoring solution. Additionally, the exam evaluates the candidate's ability to interpret metrics and identify potential issues, as well as their skills in creating custom dashboards and alerts.

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 O11y Cloud Certified Metrics User Sample Questions (Q56-Q61):

NEW QUESTION # 56
Where does the Splunk distribution of the OpenTelemetry Collector store the configuration files on Linux machines by default?

A. /etc/opentelemetry/
B. /etc/otel/collector/
C. /opt/splunk/
D. /etc/system/default/

Answer: B

Explanation:
The correct answer is B. /etc/otel/collector/
According to the web search results, the Splunk distribution of the OpenTelemetry Collector stores the configuration files on Linux machines in the /etc/otel/collector/ directory by default. You can verify this by looking at the first result1, which explains how to install the Collector for Linux manually. It also provides the locations of the default configuration file, the agent configuration file, and the gateway configuration file.
To learn more about how to install and configure the Splunk distribution of the OpenTelemetry Collector, you can refer to this documentation2.
1: https://docs.splunk.com/Observability/gdi/opentelemetry/install-linux-manual.html 2: https://docs.splunk.com/Observability/gdi/opentelemetry.html

NEW QUESTION # 57
Given that the metric demo. trans. count is being sent at a 10 second native resolution, which of the following is an accurate description of the data markers displayed in the chart below?

A. Each data marker represents the sum of API calls in the hour leading up to the data marker.
B. Each data marker represents the 10 second delta between counter values.
C. Each data marker represents the average of the sum of datapoints over the last minute, averaged over the hour.
D. Each data marker represents the average hourly rate of API calls.

Answer: A

Explanation:
Explanation
The correct answer is D. Each data marker represents the sum of API calls in the hour leading up to the data marker.
The metric demo.trans.count is a cumulative counter metric, which means that it represents the total number of API calls since the start of the measurement. A cumulative counter metric can be used to measure the rate of change or the sum of events over a time period1 The chart below shows the metric demo.trans.count with a one-hour rollup and a line chart type. A rollup is a way to aggregate data points over a specified time interval, such as one hour, to reduce the number of data points displayed on a chart. A line chart type connects the data points with a line to show the trend of the metric over time2 Each data marker on the chart represents the sum of API calls in the hour leading up to the data marker. This is because the rollup function for cumulative counter metrics is sum by default, which means that it adds up all the data points in each time interval. For example, the data marker at 10:00 AM shows the sum of API calls from 9:00 AM to 10:00 AM3 To learn more about how to use metrics and charts in Splunk Observability Cloud, you can refer to these documentations123.
1: https://docs.splunk.com/Observability/gdi/metrics/metrics.html#Metric-types 2:
https://docs.splunk.com/Observability/gdi/metrics/charts.html#Data-resolution-and-rollups-in-charts 3:
https://docs.splunk.com/Observability/gdi/metrics/charts.html#Rollup-functions-for-metric-types

NEW QUESTION # 58
The Sum Aggregation option for analytic functions does which of the following?

A. Calculates the number of MTS present in the plot.
B. Calculates 1/2 of the values present in the input time series.
C. Calculates the sum of values present in the input time series across the entire environment or per group.
D. Calculates the sum of values per time series across a period of time.

Answer: C

Explanation:
Explanation
According to the Splunk Test Blueprint - O11y Cloud Metrics User document1, one of the metrics concepts that is covered in the exam is analytic functions. Analytic functions are mathematical operations that can be applied to metrics to transform, aggregate, or analyze them.
The Splunk O11y Cloud Certified Metrics User Track document2 states that one of the recommended courses for preparing for the exam is Introduction to Splunk Infrastructure Monitoring, which covers the basics of metrics monitoring and visualization.
In the Introduction to Splunk Infrastructure Monitoring course, there is a section on Analytic Functions, which explains that analytic functions can be used to perform calculations on metrics, such as sum, average, min, max, count, etc. The document also provides examples of how to use analytic functions in charts and dashboards.
One of the analytic functions that can be used is Sum Aggregation, which calculates the sum of values present in the input time series across the entire environment or per group. The document gives an example of how to use Sum Aggregation to calculate the total CPU usage across all hosts in a group by using the following syntax:
sum(cpu.utilization) by hostgroup

NEW QUESTION # 59
What information is needed to create a detector?

A. Alert Signal, Alert Condition, Alert Settings, Alert Message, Alert Recipients
B. Alert Status, Alert Condition, Alert Settings, Alert Meaning, Alert Recipients
C. Alert Status, Alert Criteria, Alert Settings, Alert Message, Alert Recipients
D. Alert Signal, Alert Criteria, Alert Settings, Alert Message, Alert Recipients

Answer: A

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.

NEW QUESTION # 60
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?

A. Adding debug into the metrics exporter pipeline:
B. Adding logging into the metrics receiver pipeline:
C. Adding logging into the metrics exporter pipeline:
D. Adding debug into the metrics receiver pipeline:

Answer: B

Explanation:
The correct answer is B. Adding logging into the metrics receiver pipeline.
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 purposes1 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 occur1 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 listed2 To learn more about how to use the logging exporter in Splunk Observability Cloud, you can refer to this documentation1.
1: https://docs.splunk.com/Observability/gdi/opentelemetry/components/logging-exporter.html 2: https://docs.splunk.com/Observability/gdi/opentelemetry/exposed-endpoints.html

NEW QUESTION # 61
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