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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Analytics & Insights | 10% | - Aggregation, filtering, and transformation functions - Correlation and pattern detection |
| Topic 2: Alerting with Detectors | 15% | - Common use cases: latency, saturation, errors - Threshold, anomaly, and multi-condition detectors - Notification rules and incident response |
| Topic 3: Visualizing Metrics | 20% | - Creating and configuring charts, graphs, and time-series - Using SignalFlow for custom queries - Visualization best practices and effective communication |
| Topic 4: Built-in Monitoring Content | 10% | - Using pre-built dashboards and navigators - Content packs and quick-start monitoring |
| Topic 5: Dashboards & Operational Efficiency | 10% | - Designing clear, performant dashboards - Reducing alert fatigue and optimizing monitoring |
| Topic 6: Data Collection & Ingestion | 15% | - OpenTelemetry configuration and deployment - Integration with Kubernetes and cloud environments - Signal flow and data processing pipeline |
| Topic 7: Metrics Concepts | 20% | - Dimensions, time-series data, and cardinality - Metric types: Gauges, Counters, Histograms, Summaries - Data retention and resolution settings |
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NEW QUESTION # 92
Which of the following are supported rollup functions in Splunk Observability Cloud?
Answer: D
Explanation:
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.
NEW QUESTION # 93
What information is needed to create a detector?
Answer: A
Explanation:
According to the Splunk Observability Cloud documentation1, to create a detector, you need the following information:
Alert Signal: This is the metric or dimension that you want to monitor and alert on. You can select a signal from a chart or a dashboard, or enter a SignalFlow query to define the signal.
Alert Condition: This is the criteria that determines when an alert is triggered or cleared. You can choose from various built-in alert conditions, such as static threshold, dynamic threshold, outlier, missing data, and so on. You can also specify the severity level and the trigger sensitivity for each alert condition.
Alert Settings: This is the configuration that determines how the detector behaves and interacts with other detectors. You can set the detector name, description, resolution, run lag, max delay, and detector rules. You can also enable or disable the detector, and mute or unmute the alerts.
Alert Message: This is the text that appears in the alert notification and event feed. You can customize the alert message with variables, such as signal name, value, condition, severity, and so on. You can also use markdown formatting to enhance the message appearance.
Alert Recipients: This is the list of destinations where you want to send the alert notifications. You can choose from various channels, such as email, Slack, PagerDuty, webhook, and so on. You can also specify the notification frequency and suppression settings.
NEW QUESTION # 94
A customer deals with a holiday rush of traffic during November each year, but does not want to be flooded with alerts when this happens. The increase in traffic is expected and consistent each year. Which detector condition should be used when creating a detector for this data?
Answer: C
Explanation:
historical anomaly is a detector condition that allows you to trigger an alert when a signal deviates from its historical pattern1. Historical anomaly uses machine learning to learn the normal behavior of a signal based on its past data, and then compares the current value of the signal with the expected value based on the learned pattern1. You can use historical anomaly to detect unusual changes in a signal that are not explained by seasonality, trends, or cycles1.
Historical anomaly is suitable for creating a detector for the customer's data, because it can account for the expected and consistent increase in traffic during November each year. Historical anomaly can learn that the traffic pattern has a seasonal component that peaks in November, and then adjust the expected value of the traffic accordingly1. This way, historical anomaly can avoid triggering alerts when the traffic increases in November, as this is not an anomaly, but rather a normal variation. However, historical anomaly can still trigger alerts when the traffic deviates from the historical pattern in other ways, such as if it drops significantly or spikes unexpectedly1.
NEW QUESTION # 95
Which chart visualization types display only the most recent value?
Answer: D
Explanation:
Single Value, List, Heatmap, and Table visualizations can be configured to display only the most recent value of a metric, providing an immediate snapshot rather than a time series trend.
NEW QUESTION # 96
What is one reason a user of Splunk Observability Cloud would want to subscribe to an alert?
Answer: C
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 To learn more about how to use detectors and subscriptions in Splunk Observability Cloud, you can refer to these documentations12.
1: https://docs.splunk.com/Observability/alerts-detectors-notifications/detectors.html 2: https://docs.splunk.com/Observability/alerts-detectors-notifications/subscribe-to-detectors.html
NEW QUESTION # 97
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