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| Section | Weight | Objectives |
|---|---|---|
| Monitor Using Built-in Content | 10% | - Interact with data using built-in content - 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 - Subscribe to alerts - Use the Cluster Analyzer to pinpoint the root of some problems |
| 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 |
| Intro to Alerting on Metrics using Detectors | 10% | - Make a solo detector - Make a muting rule - Clone an existing detector - Make the detector from a chart |
| Introduction to Metric Visualization | 15% | - Create widgets and showcase groups - Analyze data in charts - Use rollups and analytical tools correctly - Create charts and dashboards - Look for metrics - Visualize a measure in a chart - Differentiate between several chart visualization types |
| Get Metrics In with OpenTelemetry | 10% | - Troubleshooting common errors - Edit the configuration - Configure the OTel Collector - Deploy the OTel Collector on Linux - General OpenTelemetry Concepts |
| Create Efficient Dashboards and Alerts | 10% | - View dashboard happenings - Create single-instance dashboard panels - Include instructions on interfaces - Configure personal information linkages |
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NEW QUESTION # 54
What are the best practices for creating detectors? (select all that apply)
Answer: A,B,C,D
Explanation:
The best practices for creating detectors are:
View data at highest resolution. This helps to avoid missing important signals or patterns in the data that could indicate anomalies or issues1 Have a consistent value. This means that the metric or dimension used for detection should have a clear and stable meaning across different sources, contexts, and time periods. For example, avoid using metrics that are affected by changes in configuration, sampling, or aggregation2 View detector in a chart. This helps to visualize the data and the detector logic, as well as to identify any false positives or negatives. It also allows to adjust the detector parameters and thresholds based on the data distribution and behavior3 Have a consistent type of measurement. This means that the metric or dimension used for detection should have the same unit and scale across different sources, contexts, and time periods. For example, avoid mixing bytes and bits, or seconds and milliseconds.
1: https://docs.splunk.com/Observability/gdi/metrics/detectors.html#Best-practices-for-detectors
2: https://docs.splunk.com/Observability/gdi/metrics/detectors.html#Best-practices-for-detectors
3: https://docs.splunk.com/Observability/gdi/metrics/detectors.html#View-detector-in-a-chart
4: https://docs.splunk.com/Observability/gdi/metrics/detectors.html#Best-practices-for-detectors
NEW QUESTION # 55
What approach can be used to effectively monitor cyclic metrics with unpredictable periods?
Answer: B
NEW QUESTION # 56
A user wants to compare current CPU usage to the same time yesterday on the same chart.
Which analytic function should they use?
Answer: C
Explanation:
The Timeshift function shifts a signal by a specified time interval, allowing users to overlay and compare current data against historical data, such as the same period the previous day.
NEW QUESTION # 57
A DevOps engineer wants to determine if the latency their application experiences is growing fester after a new software release a week ago. They have already created two plot lines, A and B, that represent the current latency and the latency a week ago, respectively. How can the engineer use these two plot lines to determine the rate of change in latency?
Answer: A
Explanation:
The correct answer is C. Create a plot C using the formula (A/B-l) and add a scale: 100 function to express the rate of change as a percentage.
To calculate the rate of change in latency, you need to compare the current latency (plot A) with the latency a week ago (plot B). One way to do this is to use the formula (A/B-l), which gives you the ratio of the current latency to the previous latency minus one. This ratio represents how much the current latency has increased or decreased relative to the previous latency. For example, if the current latency is 200 ms and the previous latency is 100 ms, then the ratio is (200/100-l) = 1, which means the current latency is 100% higher than the previous latency1 To express the rate of change as a percentage, you need to multiply the ratio by 100. You can do this by adding a scale: 100 function to the formula. This function scales the values of the plot by a factor of 100. For example, if the ratio is 1, then the scaled value is 100%2 To create a plot C using the formula (A/B-l) and add a scale: 100 function, you need to follow these steps:
Select plot A and plot B from the Metric Finder.
Click on Add Analytics and choose Formula from the list of functions.
In the Formula window, enter (A/B-l) as the formula and click Apply.
Click on Add Analytics again and choose Scale from the list of functions.
In the Scale window, enter 100 as the factor and click Apply.
You should see a new plot C that shows the rate of change in latency as a percentage.
To learn more about how to use formulas and scale functions in Splunk Observability Cloud, you can refer to these documentations34.
1: https://www.mathsisfun.com/numbers/percentage-change.html 2: https://docs.splunk.com/Observability/gdi/metrics/analytics.html#Scale 3: https://docs.splunk.com/Observability/gdi/metrics/analytics.html#Formula 4: https://docs.splunk.com/Observability/gdi/metrics/analytics.html#Scale
NEW QUESTION # 58
In monitoring systems, which feature allows you to troubleshoot and identify issues with charts and alerts effectively?
Answer: D
NEW QUESTION # 59
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