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SPLK-4001考古題介紹 & SPLK-4001熱門題庫
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>> SPLK-4001考古題介紹 <<
SPLK-4001熱門題庫 - SPLK-4001熱門考古題
Splunk SPLK-4001 認證考試已經成為了IT行業中很熱門的一個考試，但是為了通過考試需要花很多時間和精力掌握好相關專業知識。在這個時間很寶貴的時代，時間就是金錢。PDFExamDumps為Splunk SPLK-4001 認證考試提供的培訓方案只需要20個小時左右的時間就能幫你鞏固好相關專業知識，讓你為第一次參加的Splunk SPLK-4001 認證考試做好充分的準備。
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該考試涵蓋了各種主題，包括了解如何在Splunk中創建和操作指標，配置和部署指標在雲基礎設施中的使用，使用指標進行性能調試以及與其他監控工具集成指標。候選人還被測試他們分析和解釋數據的能力，在雲中解決問題並向利益相關者提供洞察。
最新的 Splunk O11y Cloud Certified SPLK-4001 免費考試真題 (Q23-Q28):
問題 #23
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)
- A. Send to email addresses.
- B. Send an SMS message.
- C. Invoke a webhook URL.
- D. Export to CSV.
答案：A,B,C
解題說明：
Explanation
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 workflow1 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 templates2 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 email3 Therefore, the correct answer is A, C, and D.
1: https://docs.splunk.com/Documentation/Splunk/latest/Alert/Webhooks 2:
https://docs.splunk.com/Documentation/Splunk/latest/Alert/SMSnotification 3:
https://docs.splunk.com/Documentation/Splunk/latest/Alert/Emailnotification
問題 #24
The built-in Kubernetes Navigator includes which of the following?
- A. Map, Clusters, Workloads, Node Detail, Workload Detail, Pod Detail, Container Detail
- B. Map, Nodes, Workloads, Node Detail, Workload Detail, Pod Detail, Container Detail
- C. Map, Nodes, Workloads, Node Detail, Workload Detail, Group Detail, Container Detail
- D. Map, Nodes, Processors, Node Detail, Workload Detail, Pod Detail, Container Detail
答案：B
解題說明：
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
問題 #25
Which of the following are accurate reasons to clone a detector? (select all that apply)
- A. To explore how a detector was created without risk of changing it.
- B. To modify the rules without affecting the existing detector.
- C. To reduce the amount of billed TAPM for the detector.
- D. To add an additional recipient to the detector's alerts.
答案：A,B
解題說明：
Explanation
The correct answers are A and D.
According to the Splunk Test Blueprint - O11y Cloud Metrics User document1, one of the alerting concepts that is covered in the exam is detectors and alerts. Detectors are the objects that define the conditions for generating alerts, and alerts are the notifications that are sent when those conditions are met.
The Splunk O11y Cloud Certified Metrics User Track document2 states that one of the recommended courses for preparing for the exam is Alerting with Detectors, which covers how to create, modify, and manage detectors and alerts.
In the Alerting with Detectors course, there is a section on Cloning Detectors, which explains that cloning a detector creates a copy of the detector with all its settings, rules, and alert recipients. The document also provides some reasons why you might want to clone a detector, such as:
To modify the rules without affecting the existing detector. This can be useful if you want to test different thresholds or conditions before applying them to the original detector.
To explore how a detector was created without risk of changing it. This can be helpful if you want to learn from an existing detector or use it as a template for creating a new one.
Therefore, based on these documents, we can conclude that A and D are accurate reasons to clone a detector.
B and C are not valid reasons because:
Cloning a detector does not reduce the amount of billed TAPM for the detector. TAPM stands for Tracked Active Problem Metric, which is a metric that has been alerted on by a detector. Cloning a detector does not change the number of TAPM that are generated by the original detector or the clone.
Cloning a detector does not add an additional recipient to the detector's alerts. Cloning a detector copies the alert recipients from the original detector, but it does not add any new ones. To add an additional recipient to a detector's alerts, you need to edit the alert settings of the detector.
問題 #26
What is the limit on the number of properties that an MTS can have?
- A. 0
- B. 1
- C. 2
- D. No limit
答案：C
解題說明：
The correct answer is A. 64.
According to the web search results, the limit on the number of properties that an MTS can have is 64. A property is a key-value pair that you can assign to a dimension of an existing MTS to add more context to the metrics. For example, you can add the property use: QA to the host dimension of your metrics to indicate that the host is used for QA1 Properties are different from dimensions, which are key-value pairs that are sent along with the metrics at the time of ingest. Dimensions, along with the metric name, uniquely identify an MTS. The limit on the number of dimensions per MTS is 362 To learn more about how to use properties and dimensions in Splunk Observability Cloud, you can refer to this documentation2.
1: https://docs.splunk.com/Observability/metrics-and-metadata/metrics-dimensions-mts.html#Custom-properties 2: https://docs.splunk.com/Observability/metrics-and-metadata/metrics-dimensions-mts.html
問題 #27
Which component of the OpenTelemetry Collector allows for the modification of metadata?
- A. Processors
- B. Pipelines
- C. Exporters
- D. Receivers
答案：A
解題說明：
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
問題 #28
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