SPLK-4001 Exam Dumps

Explanation:

When you click a metric name in Metric Finder, it opens Chart Builder to visualize that metric.
After customizing the chart (e.g., adjusting time range, filters, or functions), you must explicitly save it to a dashboard to persist it. You can choose an existing dashboard or create a new one during the save process.

The other options are incorrect because:

A: You don’t necessarily need to create a new dashboard (you can add to an existing one).
B: While Splunk allows adding a chart to multiple dashboards, this isn’t a requirement to save it.
C: Data visibility isn’t a prerequisite for saving the chart (though it’s good practice to verify data).

Key Concept:
Chart Builder is for ad-hoc analysis, but charts must be saved to a dashboard for reuse.
The save button (💾 icon) prompts you to select a dashboard.

Explanation:

When subscribing to a built-in detector in Splunk Observability Cloud, you can configure:
Outbound notifications (e.g., email, Slack, PagerDuty, webhooks) to alert stakeholders when the detector triggers.
This is the primary purpose of subscriptions—to route alerts to external systems or teams.

Why the Other Options Are Incorrect:

A: "Alerts on team landing page" is not a configurable subscription option. Built-in detectors may appear on dashboards or alert feeds, but this isn’t part of the subscription setup.
B: "Alerts on a dashboard" refers to embedding detectors directly, not subscribing to them.
D: "Links to a chart" are part of detector configuration (e.g., linking to a related dashboard), but not a subscription feature.

Key Concept:
Subscriptions are about notification routing, not visualization or dashboard placement.
Built-in detectors (e.g., for AWS, Kubernetes) come preconfigured with logic, but you must add subscriptions to receive alerts.

Explanation:

In the OpenTelemetry (OTel) Collector, components are organized as follows:

Processors:
Modify metadata (e.g., attributes, resource labels) and data (metrics, logs, traces).
Examples: attributes processor (add/update/delete attributes), filter processor.

Other components do not handle metadata modification:

B. Pipelines: Define the flow of data (receivers → processors → exporters) but don’t modify data.
C. Exporters: Send data to external systems (e.g., Splunk, Jaeger) without altering it.
D. Receivers: Collect data from sources (e.g., OTLP, Prometheus) but don’t transform it.

Key Concept:
Use processors for tasks like:

Enriching metrics with metadata (e.g., adding environment=prod).
Redacting sensitive data.
Sampling traces.

Explanation:

One reason a user of Splunk Observability Cloud would want to subscribe to an alert is C. To receive an email notification when a detector is triggered.

A detector is a component of Splunk Observability Cloud that monitors metrics or events and triggers alerts when certain conditions are met. A user can create and configure detectors to suit their monitoring needs and goals1.

A subscription is a way for a user to receive notifications when a detector triggers an alert. A user can subscribe to a detector by entering their email address in the Subscription tab of the detector page. A user can also unsubscribe from a detector at any time2.

When a user subscribes to an alert, they will receive an email notification that contains information about the alert, such as the detector name, the alert status, the alert severity, the alert time, and the alert message. The email notification also includes links to view the detector, acknowledge the alert, or unsubscribe from the detector2.

Explanation:

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 Collector1. 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.

Explanation

Including the metric type (such as gauge, counter, summary, or histogram) is optional in many telemetry systems, but it’s highly recommended. It provides critical context for how the metric should be interpreted and aggregated, especially when working with systems like Prometheus or custom analytics pipelines.

On the other hand:
Metric name, timestamp, and value are typically required for the datapoint to have meaning or be processed correctly.

Explanation:

Best practices for creating detectors in Splunk Observability Cloud include:

A. View data at the highest resolution
High-resolution data (e.g., raw metrics before rollup) helps ensure accurate alerting by reducing false positives/negatives caused by aggregation.

C. View detector in a chart
Visualizing the detector's logic (e.g., threshold, anomaly detection) in a chart confirms it behaves as expected before enabling alerts.

D. Have a consistent type of measurement
Ensure the metric type (e.g., gauge, counter) aligns with the detector logic (e.g., avoid mixing rates with absolute values).

Why B is incorrect:
"Have a consistent value" is vague and not a standard best practice. Detectors rely on dynamic thresholds (e.g., deviations, static/dynamic baselines) rather than fixed values.

Key Concepts:
Test detectors with historical data (via charts) before activation.
High-resolution data minimizes alert latency and inaccuracies.
Metric type consistency ensures correct SignalFlow functions (e.g., rate() for counters).

Explanation:
According to the Splunk Test Blueprint - O11y Cloud Metrics User document1, one of the metrics concepts that is covered in the exam is analytic functions. Analytic functions are mathematical operations that can be applied to metrics to transform, aggregate, or analyze them.
The Splunk O11y Cloud Certified Metrics User Track document2 states that one of the recommended courses for preparing for the exam is Introduction to Splunk Infrastructure Monitoring, which covers the basics of metrics monitoring and visualization.
In the Introduction to Splunk Infrastructure Monitoring course, there is a section on Analytic Functions, which explains that analytic functions can be used to perform calculations on metrics, such as sum, average, min, max, count, etc. The document also provides examples of how to use analytic functions in charts and dashboards.
One of the analytic functions that can be used is Sum Aggregation, which calculates the sum of values present in the input time series across the entire environment or per group.
The document gives an example of how to use Sum Aggregation to calculate the total CPU usage across all hosts in a group by using the following syntax:
sum(cpu.utilization) by hostgroup

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.

Explanation: The chart visualization types that are unaffected by changing the time picker on a dashboard are:
Single Value: A single value chart shows the current value of a metric or an expression. It does not depend on the time range of the dashboard, but only on the data resolution and rollup function of the chart1.
List: A list chart shows the values of a metric or an expression for each dimension value in a table format. It does not depend on the time range of the dashboard, but only on the data resolution and rollup function of the chart2.
Therefore, the correct answer is A and D.