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Splunk SPLK-4001 Exam Sample Questions

Question # 1

For a high-resolution metric, what is the highest possible native resolution of the metric?

A. 2 seconds

B. 15 seconds

C. 1 second

D. 5 seconds

Answer

C. 1 second

Explanation:

The correct answer is C. 1 second.

According to the Splunk Test Blueprint - O11y Cloud Metrics User document1, one of the metrics concepts that is covered in the exam is data resolution and rollups. Data resolution refers to the granularity of the metric data points, and rollups are the process of aggregating data points over time to reduce the amount of data stored.

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 Data Resolution and Rollups, which explains that Splunk Observability Cloud collects high-resolution metrics at 1-second intervals by default, and then applies rollups to reduce the data volume over time. The document also provides a table that shows the different rollup intervals and retention periods for different resolutions.

Therefore, based on these documents, we can conclude that for a high-resolution metric, the highest possible native resolution of the metric is 1 second.

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Question # 2

Which of the following statements about adding properties to MTS are true? (select all that apply)

A. Properties can be set via the API.

B. Properties are sent in with datapoints.

C. Properties are applied to dimension key:value pairs and propagated to all MTS with that dimension

D. Properties can be set in the UI under Metric Metadata.

Answer

A. Properties can be set via the API.

D. Properties can be set in the UI under Metric Metadata.

Explanation:

According to the web search results, properties are key-value pairs that you can assign to dimensions of existing metric time series (MTS) in Splunk Observability Cloud1. Properties provide additional context and information about the metrics, such as the environment, role, or owner of the dimension. For example, you can add the property use: QA to the host dimension of your metrics to indicate that the host that is sending the data is used for QA.

To add properties to MTS, you can use either the API or the UI. The API allows you to programmatically create, update, delete, and list properties for dimensions using HTTP requests2. The UI allows you to interactively create, edit, and delete properties for dimensions using the Metric Metadata page under Settings3. Therefore, option A and D are correct.

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Question # 3

What information is needed to create a detector?

A. Alert Status, Alert Criteria, Alert Settings, Alert Message, Alert Recipients

B. Alert Signal, Alert Criteria, Alert Settings, Alert Message, Alert Recipients

C. Alert Signal, Alert Condition, Alert Settings, Alert Message, Alert Recipients

D. Alert Status, Alert Condition, Alert Settings, Alert Meaning, Alert Recipients

Answer

C. Alert Signal, Alert Condition, Alert Settings, Alert Message, Alert Recipients

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.

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Question # 4

A customer is experiencing an issue where their detector is not sending email notifications but is generating alerts within the Splunk Observability UI. Which of the below is the root cause?

A. The detector has an incorrect alert rule.

B. The detector has an incorrect signal,

C. The detector is disabled.

D. The detector has a muting rule.

Answer

D. The detector has a muting rule.

Explanation:

The most likely root cause of the issue is D. The detector has a muting rule. A muting rule is a way to temporarily stop a detector from sending notifications for certain alerts, without disabling the detector or changing its alert conditions. A muting rule can be useful when you want to avoid alert noise during planned maintenance, testing, or other situations where you expect the metrics to deviate from normal1

When a detector has a muting rule, it will still generate alerts within the Splunk Observability UI, but it will not send email notifications or any other types of notifications that you have configured for the detector. You can see if a detector has a muting rule by looking at the Muting Rules tab on the detector page. You can also create, edit, or delete muting rules from there1

To learn more about how to use muting rules in Splunk Observability Cloud, you can refer to this documentation1.

---

Question # 5

When creating a standalone detector, individual rules in it are labeled according to severity. Which of the choices below represents the possible severity levels that can be selected?

A. Info, Warning, Minor, Major, and Emergency.

B. Debug, Warning, Minor, Major, and Critical.

C. Info, Warning, Minor, Major, and Critical.

D. Info, Warning, Minor, Severe, and Critical.

Answer

C. Info, Warning, Minor, Major, and Critical.

Explanation:

The correct answer is C. Info, Warning, Minor, Major, and Critical.

When creating a standalone detector, you can define one or more rules that specify the alert conditions and the severity level for each rule. The severity level indicates how urgent or important the alert is, and it can also affect the notification settings and the escalation policy for the alert1 Splunk Observability Cloud provides five predefined severity levels that you can choose from when creating a rule: Info, Warning, Minor, Major, and Critical. Each severity level has a different color and icon to help you identify the alert status at a glance. You can also customize the severity levels by changing their names, colors, or icons2

To learn more about how to create standalone detectors and use severity levels in Splunk Observability Cloud, you can refer to these documentations12.

1: https://docs.splunk.com/Observability/alerts-detectors-notifications/detectors.html#Create-a-standalone-detector 2: https://docs.splunk.com/Observability/alerts-detectors-notifications/detector-options.html#Severity-levels

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