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| Section | Weight | Objectives |
|---|---|---|
| Metrics Concepts | 20% | - Metric types: Gauges, Counters, Histograms, Summaries - Dimensions, time-series data, and cardinality - Data retention and resolution settings |
| Dashboards & Operational Efficiency | 10% | - Reducing alert fatigue and optimizing monitoring - Designing clear, performant dashboards |
| Built-in Monitoring Content | 10% | - Using pre-built dashboards and navigators - Content packs and quick-start monitoring |
| Analytics & Insights | 10% | - Correlation and pattern detection - Aggregation, filtering, and transformation functions |
| Visualizing Metrics | 20% | - Visualization best practices and effective communication - Using SignalFlow for custom queries - Creating and configuring charts, graphs, and time-series |
| Alerting with Detectors | 15% | - Common use cases: latency, saturation, errors - Threshold, anomaly, and multi-condition detectors - Notification rules and incident response |
| Data Collection & Ingestion | 15% | - OpenTelemetry configuration and deployment - Signal flow and data processing pipeline - Integration with Kubernetes and cloud environments |
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NEW QUESTION # 69
How can analytic functions be applied to a subset of multiple time series (MTS) in a signal?
(Select all that apply)
Answer: A,C
NEW QUESTION # 70
Which of the following are true about organization metrics? (select all that apply)
Answer: A,C,D
Explanation:
Organization metrics give insights into system usage, system limits, data ingested and token quotas. Organization metrics are included for free. A user can plot and alert on them like metrics they send to Splunk Observability Cloud. Organization metrics are a set of metrics that Splunk Observability Cloud provides to help you measure your organization's usage of the platform. They include metrics such as:
Ingest metrics: Measure the data you're sending to Infrastructure Monitoring, such as the number of data points you've sent.
App usage metrics: Measure your use of application features, such as the number of dashboards in your organization.
Integration metrics: Measure your use of cloud services integrated with your organization, such as the number of calls to the AWS CloudWatch API.
Resource metrics: Measure your use of resources that you can specify limits for, such as the number of custom metric time series (MTS) you've created.
Organization metrics are not charged and do not count against any system limits. You can view them in built-in charts on the Organization Overview page or in custom charts using the Metric Finder. You can also create alerts based on organization metrics to monitor your usage and performance.
NEW QUESTION # 71
Which analytic function can be used to discover peak page visits for a site over the last day?
Answer: C
Explanation:
According to the Splunk Observability Cloud documentation1, the maximum function is an analytic function that returns the highest value of a metric or a dimension over a specified time interval. The maximum function can be used as a transformation or an aggregation. A transformation applies the function to each metric time series (MTS) individually, while an aggregation applies the function to all MTS and returns a single value. For example, to discover the peak page visits for a site over the last day, you can use the following SignalFlow code:
maximum(24h, counters("page.visits"))
This will return the highest value of the page.visits counter metric for each MTS over the last 24 hours. You can then use a chart to visualize the results and identify the peak page visits for each MTS.
NEW QUESTION # 72
A customer wants to know when no data has been reported for a critical host in the last 10 minutes. Which detector condition should they configure?
Answer: B
Explanation:
The No Data condition is specifically designed to alert when a signal stops reporting data for a specified duration, which is useful for detecting hosts or services that may have gone offline or stopped emitting metrics.
NEW QUESTION # 73
A customer has a dashboard that tracks multiple performance metrics for hosts related to a production application. They want to create an alert based on an existing chart that shows them the p90 latency for a service of their application. What is the most efficient way to achieve this?
Answer: C
Explanation:
Creating a new detector from an existing chart allows the alert to leverage the same signals and analytic functions, such as p90 latency, efficiently without having to rebuild the logic manually.
NEW QUESTION # 74
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