Splunk Splunk O11y Cloud Certified Metrics User SPLK-4001 Questions & Answers

• Question 1:

  Which analytic function can be used to discover peak page visits for a site over the last day?

  A. Maximum: Transformation (24h)

  B. Maximum: Aggregation (Id)

  C. Lag: (24h)

  D. Count: (Id)

  Correct Answer: A

  According to the Splunk Observability Cloud documentation1, the maximum function is an analytic function that returns the highest value of a metric or a dimension over a specified time interval. The maximum function can be used as a

  transformation or an aggregation. A transformation applies the function to each metric time series (MTS) individually, while an aggregation applies the function to all MTS and returns a single value. For example, to discover the peak page

  visits for a site over the last day, you can use the following SignalFlow code:

  maximum(24h, counters("page.visits"))

  This will return the highest value of the page.visits counter metric for each MTS over the last 24 hours. You can then use a chart to visualize the results and identify the peak page visits for each MTS.

• Question 2:

  Which of the following are correct ports for the specified components in the OpenTelemetry Collector?

  A. gRPC (4000), SignalFx (9943), Fluentd (6060)

  B. gRPC (6831), SignalFx (4317), Fluentd (9080)

  C. gRPC (4459), SignalFx (9166), Fluentd (8956)

  D. gRPC (4317), SignalFx (9080), Fluentd (8006)

  Correct Answer: D

  The correct answer is D. gRPC (4317), SignalFx (9080), Fluentd (8006). According to the web search results, these are the default ports for the corresponding components in the OpenTelemetry Collector. You can verify this by looking at the table of exposed ports and endpoints in the first result. You can also see the agent and gateway configuration files in the same result for more details. https://docs.splunk.com/observability/gdi/opentelemetry/exposed-endpoints.html

• Question 3:

  Where does the Splunk distribution of the OpenTelemetry Collector store the configuration files on Linux machines by default?

  A. /opt/splunk/

  B. /etc/otel/collector/

  C. /etc/opentelemetry/

  D. /etc/system/default/

  Correct Answer: B

  The correct answer is B. /etc/otel/collector/ According to the web search results, the Splunk distribution of the OpenTelemetry Collector stores the configuration files on Linux machines in the /etc/otel/collector/ directory by default. You can verify this by looking at the first result, which explains how to install the Collector for Linux manually. It also provides the locations of the default configuration file, the agent configuration file, and the gateway configuration file. To learn more about how to install and configure the Splunk distribution of the OpenTelemetry Collector, you can refer to this documentation. https://docs.splunk.com/Observability/gdi/opentelemetry/install-linux-manual.html https://docs.splunk.com/Observability/gdi/opentelemetry.html

• Question 4:

  Clicking a metric name from the results in metric finder displays the metric in Chart Builder. What action needs to be taken in order to save the chart created in the UI?

  A. Create a new dashboard and save the chart.

  B. Save the chart to multiple dashboards.

  C. Make sure that data is coming in for the metric then save the chart.

  D. Save the chart to a dashboard.

  Correct Answer: D

  According to the web search results, clicking a metric name from the results in metric finder displays the metric in Chart Builder1. Chart Builder is a tool that allows you to create and customize charts using metrics, dimensions, and analytics

  functions2. To save the chart created in the UI, you need to do the following steps:

  Click the Save button on the top right corner of the Chart Builder. This will open a dialog box where you can enter the chart name and description, and choose the dashboard where you want to save the chart.

  Enter a name and a description for your chart. The name should be descriptive and unique, and the description should explain the purpose and meaning of the chart.

  Choose an existing dashboard from the drop-down menu, or create a new dashboard by clicking the + icon. A dashboard is a collection of charts that display metrics and events for your services or hosts. You can organize and share

  dashboards with other users in your organization using dashboard groups. Click Save. This will save your chart to the selected dashboard and redirect you to the dashboard view. You can also access your saved chart from the Dashboards

  menu on the left navigation bar.

• Question 5:

  A customer has a very dynamic infrastructure. During every deployment, all existing instances are destroyed, and new ones are created Given this deployment model, how should a detector be created that will not send false notifications of instances being down?

  A. Create the detector. Select Alert settings, then select Auto-Clear Alerts and enter an appropriate time period.

  B. Create the detector. Select Alert settings, then select Ephemeral Infrastructure and enter the expected lifetime of an instance.

  C. Check the Dynamic checkbox when creating the detector.

  D. Check the Ephemeral checkbox when creating the detector.

  Correct Answer: B

  According to the web search results, ephemeral infrastructure is a term that describes instances that are auto-scaled up or down, or are brought up with new code versions and discarded or recycled when the next code version is deployed1.

  Splunk Observability Cloud has a feature that allows you to create detectors for ephemeral infrastructure without sending false notifications of instances being down. To use this feature, you need to do the following steps:

  Create the detector as usual, by selecting the metric or dimension that you want to monitor and alert on, and choosing the alert condition and severity level. Select Alert settings, then select Ephemeral Infrastructure. This will enable a special

  mode for the detector that will automatically clear alerts for instances that are expected to be terminated.

  Enter the expected lifetime of an instance in minutes. This is the maximum amount of time that an instance is expected to live before being replaced by a new one. For example, if your instances are replaced every hour, you can enter 60

  minutes as the expected lifetime.

  Save the detector and activate it.

  With this feature, the detector will only trigger alerts when an instance stops reporting a metric unexpectedly, based on its expected lifetime. If an instance stops reporting a metric within its expected lifetime, the detector will assume that it was

  terminated on purpose and will not trigger an alert. Therefore, option B is correct.

• Question 6:

  Given that the metric demo. trans. count is being sent at a 10 second native resolution, which of the following is an accurate description of the data markers displayed in the chart below?

  

  A. Each data marker represents the average hourly rate of API calls.

  B. Each data marker represents the 10 second delta between counter values.

  C. Each data marker represents the average of the sum of datapoints over the last minute, averaged over the hour.

  D. Each data marker represents the sum of API calls in the hour leading up to the data marker.

  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

• Question 7:

  A customer is experiencing issues getting metrics from a new receiver they have configured in the OpenTelemetry Collector. How would the customer go about troubleshooting further with the logging exporter?

  

  A. Option A

  B. Option B

  C. Option C

  D. Option D

  Correct Answer: B

  The correct answer is B. Adding logging into the metrics receiver pipeline. The logging exporter is a component that allows the OpenTelemetry Collector to send traces, metrics, and logs directly to the console. It can be used to diagnose and troubleshoot issues with telemetry received and processed by the Collector, or to obtain samples for other purposes To activate the logging exporter, you need to add it to the pipeline that you want to diagnose. In this case, since you are experiencing issues with a new receiver for metrics, you need to add the logging exporter to the metrics receiver pipeline. This will create a new plot that shows the metrics received by the Collector and any errors or warnings that might occur The image that you have sent with your question shows how to add the logging exporter to the metrics receiver pipeline. You can see that the exporters section of the metrics pipeline includes logging as one of the options. This means that the metrics received by any of the receivers listed in the receivers section will be sent to the logging exporter as well as to any other exporters listed To learn more about how to use the logging exporter in Splunk Observability Cloud, you can refer to this documentation. https://docs.splunk.com/Observability/gdi/opentelemetry/components/logging- exporter.html https://docs.splunk.com/Observability/gdi/opentelemetry/exposed- endpoints.html

• Question 8:

  A user wants to add a link to an existing dashboard from an alert. When they click the dimension value in the alert message, they are taken to the dashboard keeping the context. How can this be accomplished? (select all that apply)

  A. Build a global data link.

  B. Add a link to the Runbook URL.

  C. Add a link to the field.

  D. Add the link to the alert message body.

  Correct Answer: AC

  The possible ways to add a link to an existing dashboard from an alert are: Build a global data link. A global data link is a feature that allows you to create a link from any dimension value in any chart or table to a dashboard of your choice. You can specify the source and target dashboards, the dimension name and value, and the query parameters to pass along. When you click on the dimension value in the alert message, you will be taken to the dashboard with the context preserved Add a link to the field. A field link is a feature that allows you to create a link from any field value in any search result or alert message to a dashboard of your choice. You can specify the field name and value, the dashboard name and ID, and the query parameters to pass along. When you click on the field value in the alert message, you will be taken to the dashboard with the context preserved Therefore, the correct answer is A and C. To learn more about how to use global data links and field links in Splunk Observability Cloud, you can refer to these documentations. https://docs.splunk.com/Observability/gdi/metrics/charts.html#Global-data-links https://docs.splunk.com/Observability/gdi/metrics/search.html#Field-links

• Question 9:

  What constitutes a single metrics time series (MTS)?

  A. A series of timestamps that all reflect the same metric.

  B. A set of data points that all have the same metric name and list of dimensions.

  C. A set of data points that use different dimensions but the same metric name.

  D. A set of metrics that are ordered in series based on timestamp.

  Correct Answer: B

  The correct answer is B. A set of data points that all have the same metric name and list of dimensions.

  A metric time series (MTS) is a collection of data points that have the same metric and the same set of dimensions. For example, the following sets of data points are in three separate MTS:

  MTS: Gauge metric cpu.utilization, dimension "hostname": "host" MTS: Gauge metric cpu.utilization, dimension "hostname": "host" MTS: Gauge metric memory.usage, dimension "hostname": "host"

  A metric is a numerical measurement that varies over time, such as CPU utilization or memory usage. A dimension is a key-value pair that provides additional information about the metric, such as the hostname or the location. A data point is

  a combination of a metric, a dimension, a value, and a timestamp

• Question 10:

  For which types of charts can individual plot visualization be set?

  A. Line, Bar, Column

  B. Bar, Area, Column

  C. Line, Area, Column

  D. Histogram, Line, Column

  Correct Answer: C

  The correct answer is C. Line, Area, Column. For line, area, and column charts, you can set the individual plot visualization to change the appearance of each plot in the chart. For example, you can change the color, shape, size, or style of the lines, areas, or columns. You can also change the rollup function, data resolution, or y-axis scale for each plot To set the individual plot visualization for line, area, and column charts, you need to select the chart from the Metric Finder, then click on Plot Chart Options and choose Individual Plot Visualization from the list of options. You can then customize each plot according to your preferences To learn more about how to use individual plot visualization in Splunk Observability Cloud, you can refer to this documentation. https://docs.splunk.com/Observability/gdi/metrics/charts.html#Individual-plot-visualization https://docs.splunk.com/Observability/gdi/metrics/charts.html#Set-individual-plot- visualization