An SRE came across an existing detector that is a good starting point for a detector they want to create. They clone the detector, update the metric, and add multiple new signals. As a result of the cloned detector, which of the following is true?
Option A is incorrect because the new signals will not be reflected in the original detector. Option B is incorrect because the new signals will not be reflected in the original chart. Option C is incorrect because you can monitor all of the new signals that you add to the cloned detector.
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?
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.
1: https://docs.splunk.com/Observability/gdi/metrics/analytics.html
Which of the following statements is true of detectors created from a chart on a custom dashboard?
The correct answer is D. The detector is automatically linked to the chart.
To refine a search for a metric a customer types host: test-*. What does this filter return?
The correct answer is A. Only metrics with a dimension of host and a value beginning with test-.
A customer has a large population of servers. They want to identify the servers where utilization has increased the most since last week. Which analytics function is needed to achieve this?
The correct answer is C. Timeshift.
timeshift(1w, counters(''server.utilization''))
This will return the value of the server.utilization counter metric for each server one week ago. You can then subtract this value from the current value of the same metric to get the difference in utilization. You can also use a chart to visualize the results and sort them by the highest difference in utilization.
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