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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Visualizing Metrics | 20% | - Using SignalFlow for custom queries - Visualization best practices and effective communication - Creating and configuring charts, graphs, and time-series |
| Topic 2: Metrics Concepts | 20% | - Data retention and resolution settings - Metric types: Gauges, Counters, Histograms, Summaries - Dimensions, time-series data, and cardinality |
| Topic 3: Built-in Monitoring Content | 10% | - Using pre-built dashboards and navigators - Content packs and quick-start monitoring |
| Topic 4: Alerting with Detectors | 15% | - Threshold, anomaly, and multi-condition detectors - Common use cases: latency, saturation, errors - Notification rules and incident response |
| Topic 5: Dashboards & Operational Efficiency | 10% | - Designing clear, performant dashboards - Reducing alert fatigue and optimizing monitoring |
| Topic 6: Data Collection & Ingestion | 15% | - Signal flow and data processing pipeline - Integration with Kubernetes and cloud environments - OpenTelemetry configuration and deployment |
| Topic 7: Analytics & Insights | 10% | - Aggregation, filtering, and transformation functions - Correlation and pattern detection |
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NEW QUESTION # 117
A customer is sending data from a machine that is over-utilized. Because of a lack of system resources, data points from this machine are often delayed by up to 10 minutes. Which setting can be modified in a detector to prevent alerts from firing before the datapoints arrive?
Answer: B
Explanation:
Max Delay is a parameter that specifies the maximum amount of time that the analytics engine can wait for data to arrive for a specific detector. For example, if Max Delay is set to 10 minutes, the detector will wait for only a maximum of 10 minutes even if some data points have not arrived.
By default, Max Delay is set to Auto, allowing the analytics engine to determine the appropriate amount of time to wait for data points.
In this case, since the customer knows that the data from the over-utilized machine can be delayed by up to 10 minutes, they can modify the Max Delay setting for the detector to 10 minutes. This will prevent the detector from firing alerts before the data points arrive, and avoid false positives or missing data.
NEW QUESTION # 118
How is it possible to create a dashboard group that no one else can edit?
Answer: B
Explanation:
According to the web search results, dashboard groups are a feature of Splunk Observability Cloud that allows you to organize and share dashboards with other users in your organization1. You can set permissions for each dashboard group, such as who can view, edit, or manage the dashboards in the group1. To create a dashboard group that no one else can edit, you need to do the following steps:
Create a dashboard group as usual, by selecting Dashboard Group from the Create menu on the navigation bar, entering a name and description, and adding dashboards to the group1.
Select Alert settings from the Dashboard actions menu (⋯) on the top right corner of the dashboard group. This will open a dialog box where you can configure the permissions for the dashboard group1.
Under Write access, select Only me. This will restrict the write access to the dashboard group to yourself only. No one else will be able to edit or delete the dashboards in the group1.
Click Save. This will create a dashboard group that no one else can edit.
NEW QUESTION # 119
A customer is experiencing an issue where their detector is not sending email notifications but is generating alerts within the Splunk Observability UI. Which of the below is the root cause?
Answer: C
Explanation:
Explanation
The most likely root cause of the issue is D. The detector has a muting rule.
A muting rule is a way to temporarily stop a detector from sending notifications for certain alerts, without disabling the detector or changing its alert conditions. A muting rule can be useful when you want to avoid alert noise during planned maintenance, testing, or other situations where you expect the metrics to deviate from normal1 When a detector has a muting rule, it will still generate alerts within the Splunk Observability UI, but it will not send email notifications or any other types of notifications that you have configured for the detector. You can see if a detector has a muting rule by looking at the Muting Rules tab on the detector page. You can also create, edit, or delete muting rules from there1 To learn more about how to use muting rules in Splunk Observability Cloud, you can refer to this documentation1.
NEW QUESTION # 120
A user wants to add a link to an existing dashboard from an alert. When they click the dimension value in the alert message, they are taken to the dashboard keeping the context. How can this be accomplished? (select all that apply)
Answer: C,D
Explanation:
Explanation
The possible ways to add a link to an existing dashboard from an alert are:
Build a global data link. A global data link is a feature that allows you to create a link from any dimension value in any chart or table to a dashboard of your choice. You can specify the source and target dashboards, the dimension name and value, and the query parameters to pass along. When you click on the dimension value in the alert message, you will be taken to the dashboard with the context preserved1 Add a link to the field. A field link is a feature that allows you to create a link from any field value in any search result or alert message to a dashboard of your choice. You can specify the field name and value, the dashboard name and ID, and the query parameters to pass along. When you click on the field value in the alert message, you will be taken to the dashboard with the context preserved2 Therefore, the correct answer is A and C.
To learn more about how to use global data links and field links in Splunk Observability Cloud, you can refer to these documentations12.
1: https://docs.splunk.com/Observability/gdi/metrics/charts.html#Global-data-links 2:
https://docs.splunk.com/Observability/gdi/metrics/search.html#Field-links
NEW QUESTION # 121
What is the recommended approach to monitor a large number of metric time series (MTS)?
Answer: B
Explanation:
Using dimensions to filter and break down metric time series allows you to organize and manage large numbers of MTS efficiently. Dimensions provide context and enable grouping, filtering, and targeted analysis without overwhelming dashboards or alerts.
NEW QUESTION # 122
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