Splunk O11y Cloud Certified Metrics User: SPLK-4001

Correct Answer: D

The correct answer is D. Each data marker represents the sum of API calls in the hour leading up to the data marker. The metric demo.trans.count is a cumulative counter metric, which means that it represents the total number of API calls since the start of the measurement. A cumulative counter metric can be used to measure the rate of change or the sum of events over a time period1 The chart below shows the metric demo.trans.count with a one-hour rollup and a line chart type. A rollup is a way to aggregate data points over a specified time interval, such as one hour, to reduce the number of data points displayed on a chart. A line chart type connects the data points with a line to show the trend of the metric over time Each data marker on the chart represents the sum of API calls in the hour leading up to the data marker. This is because the rollup function for cumulative counter metrics is sum by default, which means that it adds up all the data points in each time interval. For example, the data marker at 10:00 AM shows the sum of API calls from 9:00 AM to 10:00 AM To learn more about how to use metrics and charts in Splunk Observability Cloud, you can refer to these documentations. https://docs.splunk.com/Observability/gdi/metrics/metrics.html#Metric-types https://docs.splunk.com/Observability/gdi/metrics/charts.html#Data-resolution-and-rollups- in-charts https://docs.splunk.com/Observability/gdi/metrics/charts.html#Rollup-functions- for-metric-types

Correct Answer: C

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 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%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 documentations. https://www.mathsisfun.com/numbers/percentage-change.html https://docs.splunk.com/Observability/gdi/metrics/analytics.html#Scale https://docs.splunk.com/Observability/gdi/metrics/analytics.html#Formula https://docs.splunk.com/Observability/gdi/metrics/analytics.html#Scale

Correct Answer: A

The component of the OpenTelemetry Collector that allows for the modification of metadata is A. Processors. Processors are components that can modify the telemetry data before sending it to exporters or other components. Processors can perform various transformations on metrics, traces, and logs, such as filtering, adding, deleting, or updating attributes, labels, or resources. Processors can also enrich the telemetry data with additional metadata from various sources, such as Kubernetes, environment variables, or system information For example, one of the processors that can modify metadata is the attributes processor. This processor can update, insert, delete, or replace existing attributes on metrics or traces. Attributes are key-value pairs that provide additional information about the telemetry data, such as the service name, the host name, or the span kind Another example is the resource processor. This processor can modify resource attributes on metrics or traces. Resource attributes are key-value pairs that describe the entity that produced the telemetry data, such as the cloud provider, the region, or the instance type3 To learn more about how to use processors in the OpenTelemetry Collector, you can refer to this documentation. https://opentelemetry.io/docs/collector/configuration/#processors https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/processor/attributesprocessor https://github.com/open- telemetry/opentelemetry-collector-contrib/tree/main/processor/resourceprocessor