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Möchten Sie die Splunk SPLK-4001 Zertifizierungsrüfung mühlos bestehen? Die SchulungsMaterialien von PrüfungFrage über Splunk SPLK-4001 Zertifizierung sind eine gute Wahl. Die Testaufgaben von Splunk SPLK-4001 Prüfung aus PrüfungFrage enthalten alle Inhalte und Antworten, die Sie bei der SPLK-4001 Prüfung wissen müssen. Daher können Sie in begrenzter Zeit die Schwerpunkte der SPLK-4001 Prüfung greifen und einmalig bestehen, so dass Sie Ihren beruflichen Wert erhöhen und näher zu ihrem Erfolg kommen können.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Metrics Concepts | 15% | - Core Metrics Data Model
|
| Topic 2: Alerting on Metrics with Detectors | 10% | - Detectors and Alerting
|
| Topic 3: Get Metrics In with OpenTelemetry | 10% | - OpenTelemetry Collector Deployment
|
| Topic 4: Detectors for Common Use Cases | 15% | - Advanced Detector Scenarios
|
| Topic 5: Create Efficient Dashboards and Alerts | 10% | - Dashboard Optimization
|
| Topic 6: Monitor Using Built-in Content | 10% | - Observability Navigation & Monitoring
|
| Topic 7: Finding Insights Using Analytics | 15% | - Metrics Analytics
|
| Topic 8: Introduction to Visualizing Metrics | 15% | - Metrics Visualization
|
>> SPLK-4001 Originale Fragen <<
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93. Frage
The built-in Kubernetes Navigator includes which of the following?
Antwort: C
Begründung:
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
94. Frage
A team is troubleshooting high cardinality issues with a custom metric. What is a recommended best practice to reduce cardinality?
Antwort: A
Begründung:
Using high-cardinality values, such as unique request IDs or timestamps, as dimensions can cause an explosion in the number of unique time series. Avoiding this practice helps keep cardinality manageable and reduces cost and performance issues.
95. Frage
The alert recipients tab specifies where notification messages should be sent when alerts are triggered or cleared. Which of the below options can be used? (select all that apply)
Antwort: A,B,D
Begründung:
The alert recipients tab specifies where notification messages should be sent when alerts are triggered or cleared. The options that can be used are:
Invoke a webhook URL. This option allows you to send a HTTP POST request to a custom URL that can perform various actions based on the alert information. For example, you can use a webhook to create a ticket in a service desk system, post a message to a chat channel, or trigger another workflow.
Send an SMS message. This option allows you to send a text message to one or more phone numbers when an alert is triggered or cleared. You can customize the message content and format using variables and templates.
Send to email addresses. This option allows you to send an email notification to one or more recipients when an alert is triggered or cleared. You can customize the email subject, body, and attachments using variables and templates. You can also include information from search results, the search job, and alert triggering in the email.
96. Frage
A customer has a very dynamic infrastructure. During every deployment, all existing instances are destroyed, and new ones are created Given this deployment model, how should a detector be created that will not send false notifications of instances being down?
Antwort: B
Begründung:
According to the web search results, ephemeral infrastructure is a term that describes instances that are auto-scaled up or down, or are brought up with new code versions and discarded or recycled when the next code version is deployed1. Splunk Observability Cloud has a feature that allows you to create detectors for ephemeral infrastructure without sending false notifications of instances being down2. To use this feature, you need to do the following steps:
Create the detector as usual, by selecting the metric or dimension that you want to monitor and alert on, and choosing the alert condition and severity level.
Select Alert settings, then select Ephemeral Infrastructure. This will enable a special mode for the detector that will automatically clear alerts for instances that are expected to be terminated.
Enter the expected lifetime of an instance in minutes. This is the maximum amount of time that an instance is expected to live before being replaced by a new one. For example, if your instances are replaced every hour, you can enter 60 minutes as the expected lifetime.
Save the detector and activate it.
With this feature, the detector will only trigger alerts when an instance stops reporting a metric unexpectedly, based on its expected lifetime. If an instance stops reporting a metric within its expected lifetime, the detector will assume that it was terminated on purpose and will not trigger an alert. Therefore, option B is correct.
97. Frage
What is the recommended approach to monitor a large number of metric time series (MTS)?
Antwort: C
Begründung:
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.
98. Frage
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P.S. Kostenlose und neue SPLK-4001 Prüfungsfragen sind auf Google Drive freigegeben von PrüfungFrage verfügbar: https://drive.google.com/open?id=1Uu-8UEAORh6ga_qNHxDMPfVrMDtS0H0S