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| Section | Weight | Objectives |
|---|---|---|
| Monitor Using Built-in Content | 10% | - Observability Navigation & Monitoring
|
| Introduction to Visualizing Metrics | 15% | - Metrics Visualization
|
| Create Efficient Dashboards and Alerts | 10% | - Dashboard Optimization
|
| Alerting on Metrics with Detectors | 10% | - Detectors and Alerting
|
| Finding Insights Using Analytics | 15% | - Metrics Analytics
|
| Get Metrics In with OpenTelemetry | 10% | - OpenTelemetry Collector Deployment
|
| Metrics Concepts | 15% | - Core Metrics Data Model
|
| Detectors for Common Use Cases | 15% | - Advanced Detector Scenarios
|
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NEW QUESTION # 91
An executive team wants a chart to show the number of transactions processed so far today.
What analytics function will achieve this?
Answer: A
Explanation:
Sum Transformation with a Calendar Window calculates the accumulated total within a fixed calendar period, such as today. This produces a chart showing the number of transactions processed so far during the current day.
NEW QUESTION # 92
Which of the following statements is true of detectors created from a chart on a custom dashboard?
Answer: B
Explanation:
When you create a detector from a chart on a custom dashboard, the detector is automatically linked to the chart. This means that you can see the detector status and alerts on the chart, and you can access the detector settings from the chart menu. You can also unlink the detector from the chart if you want to.
Changes made to the chart do not affect the detector, and changes made to the detector do not affect the chart. The detector and the chart are independent entities that have their own settings and parameters. However, if you change the metric or dimension of the chart, you might lose the link to the detector.
The alerts generated by the detector will show up in the Alerts page, where you can view, manage, and acknowledge them. You can also see them on the team landing page if you assign the detector to a team.
NEW QUESTION # 93
Which of the following rollups will display the time delta between a datapoint being sent and a datapoint being received?
Answer: B
Explanation:
According to the Splunk Observability Cloud documentation, lag is a rollup function that returns the difference between the most recent and the previous data point values seen in the metric time series reporting interval. This can be used to measure the time delta between a data point being sent and a data point being received, as long as the data points have timestamps that reflect their send and receive times. For example, if a data point is sent at 10:00:00 and received at 10:00:05, the lag value for that data point is 5 seconds.
NEW QUESTION # 94
What Pod conditions does the Analyzer panel in Kubernetes Navigator monitor? (select all that apply)
Answer: A,B,C,D
Explanation:
The Pod conditions that the Analyzer panel in Kubernetes Navigator monitors are:
Not Scheduled: This condition indicates that the Pod has not been assigned to a Node yet. This could be due to insufficient resources, node affinity, or other scheduling constraints1 Unknown: This condition indicates that the Pod status could not be obtained or is not known by the system. This could be due to communication errors, node failures, or other unexpected situations1 Failed: This condition indicates that the Pod has terminated in a failure state. This could be due to errors in the application code, container configuration, or external factors1 Pending: This condition indicates that the Pod has been accepted by the system, but one or more of its containers has not been created or started yet. This could be due to image pulling, volume mounting, or network issues1 Therefore, the correct answer is A, B, C, and D.
To learn more about how to use the Analyzer panel in Kubernetes Navigator, you can refer to this documentation2.
1: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#pod-phase 2: https://docs.splunk.com/observability/infrastructure/monitor/k8s-nav.html#Analyzer-panel
NEW QUESTION # 95
Which of the following is optional, but highly recommended to include in a datapoint?
Answer: A
Explanation:
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 correctly1 To learn more about how to send metrics to Splunk Observability Cloud, you can refer to this documentation2.
1: https://docs.splunk.com/Observability/gdi/metrics/metrics.html#Metric-types 2:
https://docs.splunk.com/Observability/gdi/metrics/metrics.html
NEW QUESTION # 96
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