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| Section | Weight | Objectives |
|---|---|---|
| Dashboards & Operational Efficiency | 10% | - Designing clear, performant dashboards - Reducing alert fatigue and optimizing monitoring |
| Data Collection & Ingestion | 15% | - Signal flow and data processing pipeline - OpenTelemetry configuration and deployment - Integration with Kubernetes and cloud environments |
| Built-in Monitoring Content | 10% | - Using pre-built dashboards and navigators - Content packs and quick-start monitoring |
| Alerting with Detectors | 15% | - Notification rules and incident response - Threshold, anomaly, and multi-condition detectors - Common use cases: latency, saturation, errors |
| Metrics Concepts | 20% | - Data retention and resolution settings - Dimensions, time-series data, and cardinality - Metric types: Gauges, Counters, Histograms, Summaries |
| Visualizing Metrics | 20% | - Creating and configuring charts, graphs, and time-series - Using SignalFlow for custom queries - Visualization best practices and effective communication |
| Analytics & Insights | 10% | - Correlation and pattern detection - Aggregation, filtering, and transformation functions |
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93. Frage
A customer is sending in datapoints regarding the number of API calls made to a particular service. The datapoints are being sent every 10 seconds, and represent the number of API calls seen in the last 10 seconds. What metric type is this?
Antwort: D
Begründung:
A gauge metric represents a value measured at a specific point in time or over a defined interval.
In this scenario, the datapoints indicate the number of API calls observed in each 10-second interval, which aligns with the characteristics of a gauge metric.
94. Frage
Which of the following are ways to reduce flapping of a detector? (select all that apply)
Antwort: B,D
Begründung:
Explanation
According to the Splunk Lantern article Resolving flapping detectors in Splunk Infrastructure Monitoring, flapping is a phenomenon where alerts fire and clear repeatedly in a short period of time, due to the signal fluctuating around the threshold value. To reduce flapping, the article suggests the following ways:
Configure a duration or percent of duration for the alert: This means that you require the signal to stay above or below the threshold for a certain amount of time or percentage of time before triggering an alert. This can help filter out noise and focus on more persistent issues.
Apply a smoothing transformation (like a rolling mean) to the input data for the detector: This means that you replace the original signal with the average of its last several values, where you can specify the window length. This can reduce the impact of a single extreme observation and make the signal less fluctuating.
95. Frage
An SRE creates an event feed chart in a dashboard that shows a list of events that meet criteria they specify. Which of the following should they include? (select all that apply)
Antwort: B,C,D
Begründung:
According to the web search results1, an event feed chart is a type of chart that shows a list of events that meet criteria you specify. An event feed chart can display one or more event types depending on how you specify the criteria. The event types that you can include in an event feed chart are:
Custom events that have been sent in from an external source: These are events that you have created or received from a third-party service or tool, such as AWS CloudWatch, GitHub, Jenkins, or PagerDuty. You can send custom events to Splunk Observability Cloud using the API or the Event Ingest Service.
Events created when a detector triggers or clears an alert: These are events that are automatically generated by Splunk Observability Cloud when a detector evaluates a metric or dimension and finds that it meets the alert condition or returns to normal. You can create detectors to monitor and alert on various metrics and dimensions using the UI or the API.
Therefore, option A, B, and D are correct.
96. Frage
For a high-resolution metric, what is the highest possible native resolution of the metric?
Antwort: A
Begründung:
The correct answer is C. 1 second.
According to the Splunk Test Blueprint - O11y Cloud Metrics User document1, one of the metrics concepts that is covered in the exam is data resolution and rollups. Data resolution refers to the granularity of the metric data points, and rollups are the process of aggregating data points over time to reduce the amount of data stored.
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 Data Resolution and Rollups, which explains that Splunk Observability Cloud collects high-resolution metrics at 1-second intervals by default, and then applies rollups to reduce the data volume over time. The document also provides a table that shows the different rollup intervals and retention periods for different resolutions.
Therefore, based on these documents, we can conclude that for a high-resolution metric, the highest possible native resolution of the metric is 1 second.
97. Frage
Which of the following are supported rollup functions in Splunk Observability Cloud?
Antwort: C
Begründung:
According to the Splunk O11y Cloud Certified Metrics User Track document1, Observability Cloud has the following rollup functions:
Sum: (default for counter metrics): Returns the sum of all data points in the MTS reporting interval.
Average (default for gauge metrics): Returns the average value of all data points in the MTS reporting interval.
Min: Returns the minimum data point value seen in the MTS reporting interval.
Max: Returns the maximum data point value seen in the MTS reporting interval.
Latest: Returns the most recent data point value seen in the MTS reporting interval.
Lag: Returns the difference between the most recent and the previous data point values seen in the MTS reporting interval.
Rate: Returns the rate of change of data points in the MTS reporting interval.
98. Frage
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