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Splunk SPLK-4001 certification exam is designed for individuals who have expertise in using Splunk to monitor and analyze metrics in cloud environments. Splunk O11y Cloud Certified Metrics User certification is ideal for professionals who are interested in validating their knowledge of Splunk's metrics monitoring capabilities and their ability to leverage them to improve operational efficiency and performance. SPLK-4001 Exam requires candidates to demonstrate their ability to configure and manage Splunk's metrics collection and analysis tools, as well as their knowledge of best practices for utilizing these tools in a cloud environment.
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2025 SPLK-4001: Professional Splunk O11y Cloud Certified Metrics User Real Exam Answers
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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.
Splunk SPLK-4001, also known as the Splunk O11y Cloud Certified Metrics User Certification Exam, is a certification program designed for professionals who want to demonstrate their expertise in using Splunk's O11y Cloud platform to monitor and analyze metrics. SPLK-4001 Exam is designed to test the candidate's knowledge and skillset in using Splunk's O11y Cloud platform to collect, analyze, and visualize metrics from various sources. Splunk O11y Cloud Certified Metrics User certification program is ideal for IT professionals, system administrators, network engineers, and security analysts who want to validate their skills in using Splunk to monitor their infrastructure and applications.
Splunk O11y Cloud Certified Metrics User Sample Questions (Q56-Q61):
NEW QUESTION # 56
What is one reason a user of Splunk Observability Cloud would want to subscribe to an alert?
- A. To perform transformations on the data used by the detector.
- B. To determine the root cause of the Issue triggering the detector.
- C. To be able to modify the alert parameters.
- D. To receive an email notification when a detector is triggered.
Answer: D
Explanation:
Explanation
One reason a user of Splunk Observability Cloud would want to subscribe to an alert is C. To receive an email notification when a detector is triggered.
A detector is a component of Splunk Observability Cloud that monitors metrics or events and triggers alerts when certain conditions are met. A user can create and configure detectors to suit their monitoring needs and goals1 A subscription is a way for a user to receive notifications when a detector triggers an alert. A user can subscribe to a detector by entering their email address in the Subscription tab of the detector page. A user can also unsubscribe from a detector at any time2 When a user subscribes to an alert, they will receive an email notification that contains information about the alert, such as the detector name, the alert status, the alert severity, the alert time, and the alert message. The email notification also includes links to view the detector, acknowledge the alert, or unsubscribe from the detector2 To learn more about how to use detectors and subscriptions in Splunk Observability Cloud, you can refer to these documentations12.
1: https://docs.splunk.com/Observability/alerts-detectors-notifications/detectors.html 2:
https://docs.splunk.com/Observability/alerts-detectors-notifications/subscribe-to-detectors.html
NEW QUESTION # 57
Which analytic function can be used to discover peak page visits for a site over the last day?
- A. Maximum: Aggregation (Id)
- B. Maximum: Transformation (24h)
- C. Count: (Id)
- D. Lag: (24h)
Answer: B
Explanation:
According to the Splunk Observability Cloud documentation1, 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.
NEW QUESTION # 58
What are the best practices for creating detectors? (select all that apply)
- A. View data at highest resolution.
- B. Have a consistent value.
- C. View detector in a chart.
- D. Have a consistent type of measurement.
Answer: A,B,C,D
Explanation:
The best practices for creating detectors are:
View data at highest resolution. This helps to avoid missing important signals or patterns in the data that could indicate anomalies or issues1 Have a consistent value. This means that the metric or dimension used for detection should have a clear and stable meaning across different sources, contexts, and time periods. For example, avoid using metrics that are affected by changes in configuration, sampling, or aggregation2 View detector in a chart. This helps to visualize the data and the detector logic, as well as to identify any false positives or negatives. It also allows to adjust the detector parameters and thresholds based on the data distribution and behavior3 Have a consistent type of measurement. This means that the metric or dimension used for detection should have the same unit and scale across different sources, contexts, and time periods. For example, avoid mixing bytes and bits, or seconds and milliseconds.
1: https://docs.splunk.com/Observability/gdi/metrics/detectors.html#Best-practices-for-detectors
2: https://docs.splunk.com/Observability/gdi/metrics/detectors.html#Best-practices-for-detectors
3: https://docs.splunk.com/Observability/gdi/metrics/detectors.html#View-detector-in-a-chart
4: https://docs.splunk.com/Observability/gdi/metrics/detectors.html#Best-practices-for-detectors
NEW QUESTION # 59
What information is needed to create a detector?
- A. Alert Signal, Alert Condition, Alert Settings, Alert Message, Alert Recipients
- B. Alert Signal, Alert Criteria, Alert Settings, Alert Message, Alert Recipients
- C. Alert Status, Alert Criteria, Alert Settings, Alert Message, Alert Recipients
- D. Alert Status, Alert Condition, Alert Settings, Alert Meaning, 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
What happens when the limit of allowed dimensions is exceeded for an MTS?
- A. The datapoint is updated.
- B. The additional dimensions are dropped.
- C. The datapoint is averaged.
- D. The datapoint is dropped.
Answer: B
Explanation:
Explanation
According to the web search results, dimensions are metadata in the form of key-value pairs that monitoring software sends in along with the metrics. The set of metric time series (MTS) dimensions sent during ingest is used, along with the metric name, to uniquely identify an MTS1. Splunk Observability Cloud has a limit of 36 unique dimensions per MTS2. If the limit of allowed dimensions is exceeded for an MTS, the additional dimensions are dropped and not stored or indexed by Observability Cloud2. This means that the data point is still ingested, but without the extra dimensions. Therefore, option A is correct.
NEW QUESTION # 61
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