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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Analytics & Insights | 10% | - Aggregation, filtering, and transformation functions - Correlation and pattern detection |
| Topic 2: Data Collection & Ingestion | 15% | - Integration with Kubernetes and cloud environments - OpenTelemetry configuration and deployment - Signal flow and data processing pipeline |
| Topic 3: Alerting with Detectors | 15% | - Common use cases: latency, saturation, errors - Threshold, anomaly, and multi-condition detectors - Notification rules and incident response |
| Topic 4: Built-in Monitoring Content | 10% | - Content packs and quick-start monitoring - Using pre-built dashboards and navigators |
| Topic 5: Metrics Concepts | 20% | - Dimensions, time-series data, and cardinality - Data retention and resolution settings - Metric types: Gauges, Counters, Histograms, Summaries |
| Topic 6: Visualizing Metrics | 20% | - Creating and configuring charts, graphs, and time-series - Visualization best practices and effective communication - Using SignalFlow for custom queries |
| Topic 7: Dashboards & Operational Efficiency | 10% | - Reducing alert fatigue and optimizing monitoring - Designing clear, performant dashboards |
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NEW QUESTION # 127
Which component of the OpenTelemetry Collector allows for the modification of metadata?
Answer: C
Explanation:
Explanation
The component of the OpenTelemetry Collector that allows for the modification of metadata is A. Processors.
Processors are components that can modify the telemetry data before sending it to exporters or other components. Processors can perform various transformations on metrics, traces, and logs, such as filtering, adding, deleting, or updating attributes, labels, or resources. Processors can also enrich the telemetry data with additional metadata from various sources, such as Kubernetes, environment variables, or system information1 For example, one of the processors that can modify metadata is the attributes processor. This processor can update, insert, delete, or replace existing attributes on metrics or traces. Attributes are key-value pairs that provide additional information about the telemetry data, such as the service name, the host name, or the span kind2 Another example is the resource processor. This processor can modify resource attributes on metrics or traces.
Resource attributes are key-value pairs that describe the entity that produced the telemetry data, such as the cloud provider, the region, or the instance type3 To learn more about how to use processors in the OpenTelemetry Collector, you can refer to this documentation1.
1: https://opentelemetry.io/docs/collector/configuration/#processors 2:
https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/processor/attributesprocessor 3:
https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/processor/resourceprocessor
NEW QUESTION # 128
Interpreting data in charts can be affected by which of the following? (select all that apply)
Answer: A,C,D
NEW QUESTION # 129
Which of the following statements is true about rollups?
Answer: D
Explanation:
Display rollups are applied when there is more data than can be visually represented by the available pixels on a chart. They aggregate or summarize the data to ensure it can be efficiently displayed without losing the overall trends.
NEW QUESTION # 130
A customer wants to be alerted only when a condition is true across a majority of their hosts, rather than for each individual host. Which detector condition type should they use?
Answer: D
Explanation:
By aggregating the signal across all hosts before applying a custom threshold, the detector evaluates the overall condition rather than firing separately for each individual host, allowing alerts based on the majority state.
NEW QUESTION # 131
Which of the following are true about organization metrics? (select all that apply)
Answer: A,B,D
Explanation:
Explanation
The correct answer is A, C, and D. 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 created1 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 performance1 To learn more about how to use organization metrics in Splunk Observability Cloud, you can refer to this documentation1.
1: https://docs.splunk.com/observability/admin/org-metrics.html
NEW QUESTION # 132
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