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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Finding Insights Using Analytics | 15% | - Metrics Analytics
|
| Topic 2: Detectors for Common Use Cases | 15% | - Advanced Detector Scenarios
|
| Topic 3: Get Metrics In with OpenTelemetry | 10% | - OpenTelemetry Collector Deployment
|
| Topic 4: Metrics Concepts | 15% | - Core Metrics Data Model
|
| Topic 5: Create Efficient Dashboards and Alerts | 10% | - Dashboard Optimization
|
| Topic 6: Introduction to Visualizing Metrics | 15% | - Metrics Visualization
|
| Topic 7: Alerting on Metrics with Detectors | 10% | - Detectors and Alerting
|
| Topic 8: Monitor Using Built-in Content | 10% | - Observability Navigation & Monitoring
|
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111. Frage
A customer operates a caching web proxy. They want to calculate the cache hit rate for their service. What is the best way to achieve this?
Antwort: B
Begründung:
According to the Splunk O11y Cloud Certified Metrics User Track document1, percentages and ratios are useful for calculating the proportion of one metric to another, such as cache hits to cache misses, or successful requests to failed requests. You can use the percentage() or ratio() functions in SignalFlow to compute these values and display them in charts. For example, to calculate the cache hit rate for a service, you can use the following SignalFlow code:
percentage(counters("cache.hits"), counters("cache.misses"))
This will return the percentage of cache hits out of the total number of cache attempts. You can also use the ratio() function to get the same result, but as a decimal value instead of a percentage.
ratio(counters("cache.hits"), counters("cache.misses"))
112. Frage
Which of the following are ways to reduce flapping of a detector? (select all that apply)
Antwort: B,C
Begründung:
According to the Splunk Lantern article Resolving flapping detectors in Splunk Infrastructure Monitoring, flapping is a phenomenon where alerts fire and clear repeatedly in a short period of time, due to the signal fluctuating around the threshold value. To reduce flapping, the article suggests the following ways:
Configure a duration or percent of duration for the alert: This means that you require the signal to stay above or below the threshold for a certain amount of time or percentage of time before triggering an alert. This can help filter out noise and focus on more persistent issues.
Apply a smoothing transformation (like a rolling mean) to the input data for the detector: This means that you replace the original signal with the average of its last several values, where you can specify the window length. This can reduce the impact of a single extreme observation and make the signal less fluctuating.
113. Frage
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?
Antwort: B
Begründung:
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 latency, 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%. 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.
114. Frage
Interpreting data in charts can be affected by which of the following? (Choose all that apply.)
Antwort: B,C,D
Begründung:
Chart interpretation can be affected by rollups, analytic functions, and chart resolution because each can change how raw metric data is summarized, transformed, or visually represented over the selected time range.
115. Frage
A user wants to create an alert that only fires if CPU usage is above 90% AND memory usage is above 85% at the same time. What should they configure?
Antwort: C
Begründung:
Splunk Observability Cloud allows users to build detectors using signal expressions that combine multiple conditions (such as AND logic across two metrics), enabling alerts that trigger only when all specified conditions are met simultaneously.
116. Frage
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