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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Alerting with Detectors | 15% | - Common use cases: latency, saturation, errors - Threshold, anomaly, and multi-condition detectors - Notification rules and incident response |
| Topic 2: Built-in Monitoring Content | 10% | - Using pre-built dashboards and navigators - Content packs and quick-start monitoring |
| Topic 3: Visualizing Metrics | 20% | - Using SignalFlow for custom queries - Creating and configuring charts, graphs, and time-series - Visualization best practices and effective communication |
| Topic 4: Dashboards & Operational Efficiency | 10% | - Designing clear, performant dashboards - Reducing alert fatigue and optimizing monitoring |
| Topic 5: Metrics Concepts | 20% | - Dimensions, time-series data, and cardinality - Data retention and resolution settings - Metric types: Gauges, Counters, Histograms, Summaries |
| Topic 6: Analytics & Insights | 10% | - Aggregation, filtering, and transformation functions - Correlation and pattern detection |
| Topic 7: Data Collection & Ingestion | 15% | - Integration with Kubernetes and cloud environments - Signal flow and data processing pipeline - OpenTelemetry configuration and deployment |
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NEW QUESTION # 43
The built-in Kubernetes Navigator includes which of the following?
Answer: D
Explanation:
The correct answer is D. Map, Nodes, Workloads, Node Detail, Workload Detail, Pod Detail, Container Detail.
The built-in Kubernetes Navigator is a feature of Splunk Observability Cloud that provides a comprehensive and intuitive way to monitor the performance and health of Kubernetes environments. It includes the following views:
Map: A graphical representation of the Kubernetes cluster topology, showing the relationships and dependencies among nodes, pods, containers, and services. You can use the map to quickly identify and troubleshoot issues in your cluster1 Nodes: A tabular view of all the nodes in your cluster, showing key metrics such as CPU utilization, memory usage, disk usage, and network traffic. You can use the nodes view to compare and analyze the performance of different nodes1 Workloads: A tabular view of all the workloads in your cluster, showing key metrics such as CPU utilization, memory usage, network traffic, and error rate. You can use the workloads view to compare and analyze the performance of different workloads, such as deployments, stateful sets, daemon sets, or jobs1 Node Detail: A detailed view of a specific node in your cluster, showing key metrics and charts for CPU utilization, memory usage, disk usage, network traffic, and pod count. You can also see the list of pods running on the node and their status. You can use the node detail view to drill down into the performance of a single node2 Workload Detail: A detailed view of a specific workload in your cluster, showing key metrics and charts for CPU utilization, memory usage, network traffic, error rate, and pod count. You can also see the list of pods belonging to the workload and their status. You can use the workload detail view to drill down into the performance of a single workload2 Pod Detail: A detailed view of a specific pod in your cluster, showing key metrics and charts for CPU utilization, memory usage, network traffic, error rate, and container count. You can also see the list of containers within the pod and their status. You can use the pod detail view to drill down into the performance of a single pod2 Container Detail: A detailed view of a specific container in your cluster, showing key metrics and charts for CPU utilization, memory usage, network traffic, error rate, and log events. You can use the container detail view to drill down into the performance of a single container2 To learn more about how to use Kubernetes Navigator in Splunk Observability Cloud, you can refer to this documentation3.
1: https://docs.splunk.com/observability/infrastructure/monitor/k8s-nav.html#Kubernetes-Navigator 2: https://docs.splunk.com/observability/infrastructure/monitor/k8s-nav.html#Detail-pages 3: https://docs.splunk.com/observability/infrastructure/monitor/k8s-nav.html
NEW QUESTION # 44
Which component of the OTel Collector is responsible for receiving telemetry data from instrumented applications?
Answer: C
NEW QUESTION # 45
Given that the metric demo. trans. count is being sent at a 10 second native resolution, which of the following is an accurate description of the data markers displayed in the chart below?
Answer: D
Explanation:
Explanation
The correct answer is D. Each data marker represents the sum of API calls in the hour leading up to the data marker.
The metric demo.trans.count is a cumulative counter metric, which means that it represents the total number of API calls since the start of the measurement. A cumulative counter metric can be used to measure the rate of change or the sum of events over a time period1 The chart below shows the metric demo.trans.count with a one-hour rollup and a line chart type. A rollup is a way to aggregate data points over a specified time interval, such as one hour, to reduce the number of data points displayed on a chart. A line chart type connects the data points with a line to show the trend of the metric over time2 Each data marker on the chart represents the sum of API calls in the hour leading up to the data marker. This is because the rollup function for cumulative counter metrics is sum by default, which means that it adds up all the data points in each time interval. For example, the data marker at 10:00 AM shows the sum of API calls from 9:00 AM to 10:00 AM3 To learn more about how to use metrics and charts in Splunk Observability Cloud, you can refer to these documentations123.
1: https://docs.splunk.com/Observability/gdi/metrics/metrics.html#Metric-types 2:
https://docs.splunk.com/Observability/gdi/metrics/charts.html#Data-resolution-and-rollups-in-charts 3:
https://docs.splunk.com/Observability/gdi/metrics/charts.html#Rollup-functions-for-metric-types
NEW QUESTION # 46
To refine a search for a metric a customer types host: test-*. What does this filter return?
Answer: D
Explanation:
This filter returns the metrics that have a host dimension that matches the pattern test-. For example, test-01, test-abc, test-xyz, etc. The asterisk () is a wildcard character that can match any string of characters.
NEW QUESTION # 47
What approach can be used to effectively monitor cyclic metrics with unpredictable periods?
Answer: C
NEW QUESTION # 48
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