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Splunk SPLK-4001 Exam is designed to test the knowledge and competency of professionals in using Splunk's O11y Cloud platform for metrics and data analytics. SPLK-4001 exam is intended for individuals who work with Splunk's cloud-based monitoring and observability tools and need to demonstrate their expertise in using these tools to collect and analyze data. SPLK-4001 exam covers topics such as data collection, data visualization, alerting, and troubleshooting.
Splunk SPLK-4001 (Splunk O11y Cloud Certified Metrics User) Exam is an industry-recognized certification program that helps to validate an individual’s knowledge and expertise in the area of cloud monitoring and analytics. Splunk O11y Cloud Certified Metrics User certification exam is specifically designed for Splunk Cloud administrators who are responsible for monitoring cloud-based infrastructure and applications. Through this certification program, candidates will gain technical expertise and knowledge required to implement and manage cloud monitoring strategies using Splunk Metrics.
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NEW QUESTION # 79
Which of the following is true about the native resolution of a metric?
Answer: C
Explanation:
The native resolution of a metric is determined by the reporting interval of the source sending the data; charts and detectors may aggregate data using rollups when viewing over longer time ranges than the native resolution.
NEW QUESTION # 80
A customer deals with a holiday rush of traffic during November each year, but does not want to be flooded with alerts when this happens. The increase in traffic is expected and consistent each year. Which detector condition should be used when creating a detector for this data?
Answer: A
Explanation:
historical anomaly is a detector condition that allows you to trigger an alert when a signal deviates from its historical pattern1. Historical anomaly uses machine learning to learn the normal behavior of a signal based on its past data, and then compares the current value of the signal with the expected value based on the learned pattern1. You can use historical anomaly to detect unusual changes in a signal that are not explained by seasonality, trends, or cycles1.
Historical anomaly is suitable for creating a detector for the customer's data, because it can account for the expected and consistent increase in traffic during November each year. Historical anomaly can learn that the traffic pattern has a seasonal component that peaks in November, and then adjust the expected value of the traffic accordingly1. This way, historical anomaly can avoid triggering alerts when the traffic increases in November, as this is not an anomaly, but rather a normal variation. However, historical anomaly can still trigger alerts when the traffic deviates from the historical pattern in other ways, such as if it drops significantly or spikes unexpectedly1.
NEW QUESTION # 81
A customer deals with a holiday rush of traffic during November each year, but does not want to be flooded with alerts when this happens. The increase in traffic is expected and consistent each year. Which detector condition should be used when creating a detector for this data?
Answer: A
Explanation:
historical anomaly is a detector condition that allows you to trigger an alert when a signal deviates from its historical pattern. Historical anomaly uses machine learning to learn the normal behavior of a signal based on its past data, and then compares the current value of the signal with the expected value based on the learned pattern. You can use historical anomaly to detect unusual changes in a signal that are not explained by seasonality, trends, or cycles. Historical anomaly is suitable for creating a detector for the customer's data, because it can account for the expected and consistent increase in traffic during November each year. Historical anomaly can learn that the traffic pattern has a seasonal component that peaks in November, and then adjust the expected value of the traffic accordingly. This way, historical anomaly can avoid triggering alerts when the traffic increases in November, as this is not an anomaly, but rather a normal variation.
However, historical anomaly can still trigger alerts when the traffic deviates from the historical pattern in other ways, such as if it drops significantly or spikes unexpectedly.
NEW QUESTION # 82
Which feature allows users to receive an alert notification via Slack, email, or PagerDuty when a detector triggers?
Answer: D
Explanation:
Notification integrations allow detectors to send alerts to external systems such as Slack, email, PagerDuty, and others, ensuring the right teams are notified when an alert condition is triggered.
NEW QUESTION # 83
A customer has created a chart that tracks cpu.utilization of a set of production servers. The customer wants to show which of their servers are under 5% utilization to track underutilization of resources. What is the best analytic function to achieve this?
Answer: C
Explanation:
The Bottom analytic function identifies the metrics with the lowest values, allowing the customer to highlight servers with CPU utilization under 5% and track underutilized resources effectively.
NEW QUESTION # 84
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