QUESTION: 13

Which of the following is optional, but highly recommended to include in a datapoint?

Metric name
Timestamp
Value
Metric type

Answer(s): D

Explanation:

The correct answer is D. Metric type.
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.
To learn more about how to send metrics to Splunk Observability Cloud, you can refer to this documentation.
1: https://docs.splunk.com/Observability/gdi/metrics/metrics.html#Metric-types
2: https://docs.splunk.com/Observability/gdi/metrics/metrics.html

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QUESTION: 14

Which analytic function can be used to discover peak page visits for a site over the last day?

Maximum: Transformation (24h)
Maximum: Aggregation (Id)
Lag: (24h)
Count: (Id)

Answer(s): A

Explanation:

According to the Splunk Observability Cloud documentation., 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.

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QUESTION: 15

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?

Adding debug into the metrics receiver pipeline:
Adding logging into the metrics receiver pipeline:
Adding logging into the metrics exporter pipeline:
Adding debug into the metrics exporter pipeline:

Answer(s): 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 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. To learn more about how to use the logging exporter in Splunk Observability Cloud, you can refer to this documentation.
1: https://docs.splunk.com/Observability/gdi/opentelemetry/components/logging-exporter.html
2: https://docs.splunk.com/Observability/gdi/opentelemetry/exposed-endpoints.html

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QUESTION: 16

What information is needed to create a detector?

Alert Status, Alert Criteria, Alert Settings, Alert Message, Alert Recipients
Alert Signal, Alert Criteria, Alert Settings, Alert Message, Alert Recipients
Alert Signal, Alert Condition, Alert Settings, Alert Message, Alert Recipients
Alert Status, Alert Condition, Alert Settings, Alert Meaning, Alert Recipients

Answer(s): C

Explanation:

According to the Splunk Observability Cloud documentation., 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.

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Free SPLK-4001 Exam Braindumps (page: 4)

QUESTION: 13

Explanation:

QUESTION: 14

Explanation:

QUESTION: 15

Explanation:

QUESTION: 16

Explanation: