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Splunk SPLK-4001, also known as the Splunk O11y Cloud Certified Metrics User Certification Exam, is a certification program designed for professionals who want to demonstrate their expertise in using Splunk's O11y Cloud platform to monitor and analyze metrics. SPLK-4001 Exam is designed to test the candidate's knowledge and skillset in using Splunk's O11y Cloud platform to collect, analyze, and visualize metrics from various sources. Splunk O11y Cloud Certified Metrics User certification program is ideal for IT professionals, system administrators, network engineers, and security analysts who want to validate their skills in using Splunk to monitor their infrastructure and applications.

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Splunk O11y Cloud Certified Metrics User Sample Questions (Q57-Q62):

NEW QUESTION # 57
Changes to which type of metadata result in a new metric time series?

Answer: A

Explanation:
The correct answer is A. Dimensions.
Dimensions are metadata in the form of key-value pairs that are sent along with the metrics at the time of ingest. They provide additional information about the metric, such as the name of the host that sent the metric, or the location of the server. Along with the metric name, they uniquely identify a metric time series (MTS)1 Changes to dimensions result in a new MTS, because they create a different combination of metric name and dimensions. For example, if you change the hostname dimension from host1 to host2, you will create a new MTS for the same metric name1 Properties, sources, and tags are other types of metadata that can be applied to existing MTSes after ingest. They do not contribute to uniquely identify an MTS, and they do not create a new MTS when changed2 To learn more about how to use metadata in Splunk Observability Cloud, you can refer to this documentation2.
1: https://docs.splunk.com/Observability/metrics-and-metadata/metrics.html#Dimensions 2: https://docs.splunk.com/Observability/metrics-and-metadata/metrics-dimensions-mts.html


NEW QUESTION # 58
Which of the following are correct ports for the specified components in the OpenTelemetry Collector?

Answer: C

Explanation:
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 result1. You can also see the agent and gateway configuration files in the same result for more details.
1: https://docs.splunk.com/observability/gdi/opentelemetry/exposed-endpoints.html


NEW QUESTION # 59
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?

Answer: B

Explanation:
Explanation
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.
To learn more about how to use analytics functions in Splunk Observability Cloud, you can refer to this documentation1.
1: https://docs.splunk.com/Observability/gdi/metrics/analytics.html


NEW QUESTION # 60
Which component of the OpenTelemetry Collector allows for the modification of metadata?

Answer: C

Explanation:
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 information1 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 kind2 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 documentation1.
1: https://opentelemetry.io/docs/collector/configuration/#processors 2: https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/processor/attributesprocessor 3: https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/processor/resourceprocessor


NEW QUESTION # 61
In the Splunk distribution of the OpenTelemetry Collector, what is the difference between the agent_config.yaml and the splunk-otel-collector.conf files?

Answer: A


NEW QUESTION # 62
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