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| Section | Weight | Objectives |
|---|---|---|
| Metrics Concepts | 15% | - Data resolution, rollups - Define components of the Splunk IM Data Model, Metrics, MTS, datapoints - List the components of a datapoint - Discriminate between types of metadata |
| Get Metrics In with OpenTelemetry | 10% | - General OpenTelemetry Concepts - Troubleshooting common errors - Edit the configuration - Deploy the OTel Collector on Linux - Configure the OTel Collector |
| Intro to Alerting on Metrics using Detectors | 10% | - Clone an existing detector - Make a muting rule - Make a solo detector - Make the detector from a chart |
| Monitor Using Built-in Content | 10% | - Use the Cluster Analyzer to pinpoint the root of some problems - Use the Kubernetes Navigator to investigate problems with nodes, pods, and containers - Correctly interpret data in charts based on rollups, analytic functions, and chart resolution - Interact with data using built-in content - Subscribe to alerts |
| Introduction to Metric Visualization | 15% | - Use rollups and analytical tools correctly - Differentiate between several chart visualization types - Create charts and dashboards - Analyze data in charts - Create widgets and showcase groups - Visualize a measure in a chart - Look for metrics |
| Create Efficient Dashboards and Alerts | 10% | - Create single-instance dashboard panels - Configure personal information linkages - Include instructions on interfaces - View dashboard happenings |
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NEW QUESTION # 114
When applying analytic functions to a subset of multiple time series (MTS) in a signal, what is the resulting data structure?
Answer: C
NEW QUESTION # 115
What is the finest resolution that Calendar Window Transformation datapoints can be calculated and displayed?
Answer: D
Explanation:
Calendar Window Transformation datapoints are calculated and displayed at the native resolution of the input time series, ensuring that the aggregation respects the original granularity of the metric data.
NEW QUESTION # 116
Which chart type in Splunk Observability Cloud is best suited for visualizing the proportion of time a resource spends in different states?
Answer: D
Explanation:
A Heatmap is well-suited for visualizing many time series at once and showing how values (such as states or utilization levels) are distributed across a large number of instances over time.
NEW QUESTION # 117
The Sum Aggregation option for analytic functions does which of the following?
Answer: B
Explanation:
Explanation
According to the Splunk Test Blueprint - O11y Cloud Metrics User document1, one of the metrics concepts that is covered in the exam is analytic functions. Analytic functions are mathematical operations that can be applied to metrics to transform, aggregate, or analyze them.
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 Analytic Functions, which explains that analytic functions can be used to perform calculations on metrics, such as sum, average, min, max, count, etc. The document also provides examples of how to use analytic functions in charts and dashboards.
One of the analytic functions that can be used is Sum Aggregation, which calculates the sum of values present in the input time series across the entire environment or per group. The document gives an example of how to use Sum Aggregation to calculate the total CPU usage across all hosts in a group by using the following syntax:
sum(cpu.utilization) by hostgroup
NEW QUESTION # 118
For a high-resolution metric, what is the highest possible native resolution of the metric?
Answer: D
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.
NEW QUESTION # 119
......
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