The correct answer is A, C, and D. Organization metrics give insights into system usage, system limits, data ingested and token quotas. Organization metrics are included for free. A user can plot and alert on them like metrics they send to Splunk Observability Cloud.

Organization metrics are a set of metrics that Splunk Observability Cloud provides to help you measure your organization’s usage of the platform. They include metrics such as:

Ingest metrics: Measure the data you’re sending to Infrastructure Monitoring, such as the number of data points you’ve sent.

App usage metrics: Measure your use of application features, such as the number of dashboards in your organization.

Integration metrics: Measure your use of cloud services integrated with your organization, such as the number of calls to the AWS CloudWatch API.

Resource metrics: Measure your use of resources that you can specify limits for, such as the number of custom metric time series (MTS) you’ve created 1

Organization metrics are not charged and do not count against any system limits. You can view them in built-in charts on the Organization Overview page or in custom charts using the Metric Finder. You can also create alerts based on organization metrics to monitor your usage and performance 1

To learn more about how to use organization metrics in Splunk Observability Cloud, you can refer to this documentation 1 .

1 : https://docs.splunk.com/observability/admin/org-metrics.html

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 1 . 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

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:

MTS1: Gauge metric cpu.utilization, dimension “hostname”: “host1” MTS2: Gauge metric cpu.utilization, dimension “hostname”: “host2” MTS3: Gauge metric memory.usage, dimension “hostname”: “host1”

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 1

The correct answer is C. 401 (UNAUTHORIZED).

According to the web search results, a 401 (UNAUTHORIZED) error message is indicative that there is a misconfigured realm or access token when installing OpenTelemetry Collector 1 . A 401 (UNAUTHORIZED) error message means that the request was not authorized by the server due to invalid credentials. A realm is a parameter that specifies the scope of protection for a resource, such as a Splunk Observability Cloud endpoint. An access token is a credential that grants access to a resource, such as a Splunk Observability Cloud API. If the realm or the access token is misconfigured, the request to install OpenTelemetry Collector will be rejected by the server with a 401 (UNAUTHORIZED) error message.

Option A is incorrect because a 403 (NOT ALLOWED) error message is not indicative that there is a misconfigured realm or access token when installing OpenTelemetry Collector. A 403 (NOT ALLOWED) error message means that the request was authorized by the server but not allowed due to insufficient permissions. Option B is incorrect because a 404 (NOT FOUND) error message is not indicative that there is a misconfigured realm or access token when installing OpenTelemetry Collector. A 404 (NOT FOUND) error message means that the request was not found by the server due to an invalid URL or resource. Option D is incorrect because a 503 (SERVICE UNREACHABLE) error message is not indicative that there is a misconfigured realm or access token when installing OpenTelemetry Collector. A 503 (SERVICE UNREACHABLE) error message means that the server was unable to handle the request due to temporary overload or maintenance.

The correct answers are A and D.

According to the Get started with Splunk Observability Cloud document 1 , one of the topics that is covered in the Getting Data into Splunk Observability Cloud course is global and local data links. Data links are shortcuts that provide convenient access to related resources, such as Splunk Observability Cloud dashboards, Splunk Cloud Platform and Splunk Enterprise, custom URLs, and Kibana logs.

The document explains that there are two types of data links: global and local. Global data links are available on all dashboards and charts, while local data links are available on only one dashboard. The document also provides the following information about local data links:

Anyone with write permission for a dashboard can add local data links that appear on that dashboard.

Local data links can have either a Splunk Observability Cloud internal destination or an external destination, such as a custom URL or a Kibana log.

Only Splunk Observability Cloud administrators can delete local data links.

Therefore, based on this document, we can conclude that A and D are true statements about local data links. B and C are false statements because:

B is false because local data links can have an external destination as well as an internal one.

C is false because anyone with write permission for a dashboard can create local data links, not just administrators.

According to the web search results, clicking a metric name from the results in metric finder displays the metric in Chart Builder 1 .  Chart Builder is a tool that allows you to create and customize charts using metrics, dimensions, and analytics functions 2 . 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 3 .  You can organize and share dashboards with other users in your organization using dashboard groups 3 .

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.

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 1

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 2

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 type 3

To learn more about how to use processors in the OpenTelemetry Collector, you can refer to this documentation 1 .

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