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| Section | Weight | Objectives |
|---|---|---|
| Dashboards & Operational Efficiency | 10% | - Designing clear, performant dashboards - Reducing alert fatigue and optimizing monitoring |
| Analytics & Insights | 10% | - Correlation and pattern detection - Aggregation, filtering, and transformation functions |
| Built-in Monitoring Content | 10% | - Content packs and quick-start monitoring - Using pre-built dashboards and navigators |
| Visualizing Metrics | 20% | - Using SignalFlow for custom queries - Creating and configuring charts, graphs, and time-series - Visualization best practices and effective communication |
| Alerting with Detectors | 15% | - Threshold, anomaly, and multi-condition detectors - Common use cases: latency, saturation, errors - Notification rules and incident response |
| Data Collection & Ingestion | 15% | - Integration with Kubernetes and cloud environments - Signal flow and data processing pipeline - OpenTelemetry configuration and deployment |
| Metrics Concepts | 20% | - Metric types: Gauges, Counters, Histograms, Summaries - Dimensions, time-series data, and cardinality - Data retention and resolution settings |
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NEW QUESTION # 120
Which of the following statements is true of detectors created from a chart on a custom dashboard?
Answer: D
Explanation:
The correct answer is D. The detector is automatically linked to the chart.
When you create a detector from a chart on a custom dashboard, the detector is automatically linked to the chart. This means that you can see the detector status and alerts on the chart, and you can access the detector settings from the chart menu. You can also unlink the detector from the chart if you want to1 Changes made to the chart do not affect the detector, and changes made to the detector do not affect the chart. The detector and the chart are independent entities that have their own settings and parameters. However, if you change the metric or dimension of the chart, you might lose the link to the detector1 The alerts generated by the detector will show up in the Alerts page, where you can view, manage, and acknowledge them. You can also see them on the team landing page if you assign the detector to a team2 To learn more about how to create and link detectors from charts on custom dashboards, you can refer to this documentation1.
1: https://docs.splunk.com/observability/alerts-detectors-notifications/link-detectors-to-charts.html 2: https://docs.splunk.com/observability/alerts-detectors-notifications/view-manage-alerts.html
NEW QUESTION # 121
A customer wants to find the total number of transmission errors that occurred over a discrete period of time. Assuming that the metric type is Cumulative Counter, which of the following combinations of rollup and analytic function could be used to accomplish this?
Answer: C
Explanation:
For a cumulative counter, the Delta rollup calculates the change in the counter value over each interval. Applying the Sum Transformation analytic function then adds those deltas together to get the total number of transmission errors over the selected time period.
NEW QUESTION # 122
Which of the following rollups will display the time delta between a datapoint being sent and a datapoint being received?
Answer: C
Explanation:
According to the Splunk Observability Cloud documentation, lag is a rollup function that returns the difference between the most recent and the previous data point values seen in the metric time series reporting interval. This can be used to measure the time delta between a data point being sent and a data point being received, as long as the data points have timestamps that reflect their send and receive times. For example, if a data point is sent at 10:00:00 and received at 10:00:05, the lag value for that data point is 5 seconds.
NEW QUESTION # 123
What Pod conditions does the Analyzer panel in Kubernetes Navigator monitor? (select all that apply)
Answer: A,B,C,D
Explanation:
The Pod conditions that the Analyzer panel in Kubernetes Navigator monitors are:
Not Scheduled: This condition indicates that the Pod has not been assigned to a Node yet. This could be due to insufficient resources, node affinity, or other scheduling constraints. Unknown:
This condition indicates that the Pod status could not be obtained or is not known by the system.
This could be due to communication errors, node failures, or other unexpected situations. Failed:
This condition indicates that the Pod has terminated in a failure state. This could be due to errors in the application code, container configuration, or external factors. Pending: This condition indicates that the Pod has been accepted by the system, but one or more of its containers has not been created or started yet. This could be due to image pulling, volume mounting, or network issues.
NEW QUESTION # 124
One server in a customer's data center is regularly restarting due to power supply issues. What type of dashboard could be used to view charts and create detectors for this server?
Answer: C
Explanation:
According to the Splunk O11y Cloud Certified Metrics User Track document1, a single-instance dashboard is a type of dashboard that displays charts and information for a single instance of a service or host. You can use a single-instance dashboard to monitor the performance and health of a specific server, such as the one that is restarting due to power supply issues. You can also create detectors for the metrics that are relevant to the server, such as CPU usage, memory usage, disk usage, and uptime.
NEW QUESTION # 125
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