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| Section | Weight | Objectives |
|---|---|---|
| Create Efficient Dashboards and Alerts | 10% | - Include instructions on interfaces - Create single-instance dashboard panels - Configure personal information linkages - View dashboard happenings |
| Monitor Using Built-in Content | 10% | - Use the Cluster Analyzer to pinpoint the root of some problems - Interact with data using built-in content - Subscribe to alerts - Correctly interpret data in charts based on rollups, analytic functions, and chart resolution - Use the Kubernetes Navigator to investigate problems with nodes, pods, and containers |
| Get Metrics In with OpenTelemetry | 10% | - Deploy the OTel Collector on Linux - Configure the OTel Collector - Troubleshooting common errors - Edit the configuration - General OpenTelemetry Concepts |
| Intro to Alerting on Metrics using Detectors | 10% | - Make a muting rule - Make the detector from a chart - Clone an existing detector - Make a solo detector |
| Introduction to Metric Visualization | 15% | - Look for metrics - Create widgets and showcase groups - Visualize a measure in a chart - Create charts and dashboards - Analyze data in charts - Use rollups and analytical tools correctly - Differentiate between several chart visualization types |
| Metrics Concepts | 15% | - List the components of a datapoint - Data resolution, rollups - Discriminate between types of metadata - Define components of the Splunk IM Data Model, Metrics, MTS, datapoints |
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NEW QUESTION # 10
Which of the following rollups will display the time delta between a datapoint being sent and a datapoint being received?
Answer: D
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 # 11
When you add instructions to dashboards, what is their primary purpose?
Answer: D
NEW QUESTION # 12
Which of the following statements about adding properties to MTS are true? (select all that apply)
Answer: B,D
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 Cloud. 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 requests. The UI allows you to interactively create, edit, and delete properties for dimensions using the Metric Metadata page under Settings.
NEW QUESTION # 13
A Software Engineer is troubleshooting an issue with memory utilization in their application. They released a new canary version to production and now want to determine if the average memory usage is lower for requests with the 'canary' version dimension. They've already opened the graph of memory utilization for their service.
How does the engineer see if the new release lowered average memory utilization?
Answer: C
Explanation:
Explanation
The correct answer is C. On the chart for plot A, select Add Analytics, then select Mean:Aggregation. In the window that appears, select 'version' from the Group By field.
This will create a new plot B that shows the average memory utilization for each version of the application.
The engineer can then compare the values of plot B for the 'canary' and 'stable' versions to see if there is a significant difference.
To learn more about how to use analytics functions in Splunk Observability Cloud, you can refer to this documentation1.
1: https://docs.splunk.com/Observability/gdi/metrics/analytics.html
NEW QUESTION # 14
What happens when the limit of allowed dimensions is exceeded for an MTS?
Answer: D
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 MTS.
Splunk Observability Cloud has a limit of 36 unique dimensions per MTS. If the limit of allowed dimensions is exceeded for an MTS, the additional dimensions are dropped and not stored or indexed by Observability Cloud. This means that the data point is still ingested, but without the extra dimensions. Therefore, option A is correct.
NEW QUESTION # 15
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