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| Section | Weight | Objectives |
|---|---|---|
| Alerting on Metrics with Detectors | 10% | - Detectors and Alerting
|
| Detectors for Common Use Cases | 15% | - Advanced Detector Scenarios
|
| Introduction to Visualizing Metrics | 15% | - Metrics Visualization
|
| Finding Insights Using Analytics | 15% | - Metrics Analytics
|
| Metrics Concepts | 15% | - Core Metrics Data Model
|
| Get Metrics In with OpenTelemetry | 10% | - OpenTelemetry Collector Deployment
|
| Monitor Using Built-in Content | 10% | - Observability Navigation & Monitoring
|
| Create Efficient Dashboards and Alerts | 10% | - Dashboard Optimization
|
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NEW QUESTION # 108
Given that the metric demo. trans. count is being sent at a 10 second native resolution, which of the following is an accurate description of the data markers displayed in the chart below?
Answer: C
Explanation:
Explanation
The correct answer is D. Each data marker represents the sum of API calls in the hour leading up to the data marker.
The metric demo.trans.count is a cumulative counter metric, which means that it represents the total number of API calls since the start of the measurement. A cumulative counter metric can be used to measure the rate of change or the sum of events over a time period1 The chart below shows the metric demo.trans.count with a one-hour rollup and a line chart type. A rollup is a way to aggregate data points over a specified time interval, such as one hour, to reduce the number of data points displayed on a chart. A line chart type connects the data points with a line to show the trend of the metric over time2 Each data marker on the chart represents the sum of API calls in the hour leading up to the data marker. This is because the rollup function for cumulative counter metrics is sum by default, which means that it adds up all the data points in each time interval. For example, the data marker at 10:00 AM shows the sum of API calls from 9:00 AM to 10:00 AM3 To learn more about how to use metrics and charts in Splunk Observability Cloud, you can refer to these documentations123.
1: https://docs.splunk.com/Observability/gdi/metrics/metrics.html#Metric-types 2:
https://docs.splunk.com/Observability/gdi/metrics/charts.html#Data-resolution-and-rollups-in-charts 3:
https://docs.splunk.com/Observability/gdi/metrics/charts.html#Rollup-functions-for-metric-types
NEW QUESTION # 109
What tool provides the ability to search metrics and their associated metadata within Splunk Observability Cloud?
Answer: A
Explanation:
Metric Finder is used to search for metrics and view their associated metadata in Splunk Observability Cloud, making it the appropriate tool for locating available metrics and understanding their related dimensions or properties.
NEW QUESTION # 110
Which of the following statements about adding properties to MTS are true? (select all that apply)
Answer: A,C
Explanation:
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.
NEW QUESTION # 111
Which of the following are supported rollup functions in Splunk Observability Cloud?
Answer: C
Explanation:
Explanation
According to the Splunk O11y Cloud Certified Metrics User Track document1, Observability Cloud has the following rollup functions: Sum: (default for counter metrics): Returns the sum of all data points in the MTS reporting interval. Average (default for gauge metrics): Returns the average value of all data points in the MTS reporting interval. Min: Returns the minimum data point value seen in the MTS reporting interval. Max:
Returns the maximum data point value seen in the MTS reporting interval. Latest: Returns the most recent data point value seen in the MTS reporting interval. Lag: Returns the difference between the most recent and the previous data point values seen in the MTS reporting interval. Rate: Returns the rate of change of data points in the MTS reporting interval. Therefore, option A is correct.
NEW QUESTION # 112
When configuring a new receiver to send data to Splunk Observability Cloud, which sections must the new receiver be added to in the OpenTelemetry Collector configuration file? (Choose all that apply.)
Answer: B,C,D
Explanation:
In the OpenTelemetry Collector configuration, a new receiver must be defined under receivers, referenced in a pipeline, and paired with an appropriate exporter to send data to Splunk Observability Cloud.
NEW QUESTION # 113
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