[2024年05月10日] 合格Splunk O11y Cloud Certified SPLK-4001試験問題集には56問があります
究極ガイドの無料準備Splunk SPLK-4001試験問題と解答
SPLK-4001（SPLUNK O11Y Cloud Certified Metricsユーザー）認定試験は、Splunk Cloudを使用してメトリックデータを扱う専門家にとって貴重な認定です。この試験では、メトリックの基礎、Splunk Metrics Data Model、Splunk Metrics Store、高度なメトリックの分析と視覚化技術など、幅広いトピックをカバーしています。認証は、メトリックの深い理解とデータ駆動型の決定を行う能力を示すため、専門家と組織の両方にとって貴重な資産です。
SPLK-4001試験は、データインジェスション、データ変換、フィールド抽出、検索とレポート、アラートと通知、およびダッシュボードの作成など、様々なトピックをカバーしています。また、スケーラビリティ、弾力性、高可用性などのクラウドコンピューティングの概念に対する理解も候補者の能力をテストします。この試験は、複数選択肢のテスト形式で、監督されたテストセンターでオンラインまたは対面で受けることができます。試験に合格すると、候補者はSplunkを使用してクラウドアプリケーションやインフラストラクチャの監視とトラブルシューティングを行うために必要なスキルを持っていることが証明され、クラウドコンピューティングの分野でキャリアアップするのに役立ちます。
質問 # 12
A customer has a large population of servers. They want to identify the servers where utilization has increased the most since last week. Which analytics function is needed to achieve this?
- A. Sum transformation
- B. Standard deviation
- C. Rate
- D. Tlmeshift
正解：D
解説：
Explanation
The correct answer is C. Timeshift.
According to the Splunk Observability Cloud documentation1, timeshift is an analytic function that allows you to compare the current value of a metric with its value at a previous time interval, such as an hour ago or a week ago. You can use the timeshift function to measure the change in a metric over time and identify trends, anomalies, or patterns. For example, to identify the servers where utilization has increased the most since last week, you can use the following SignalFlow code:
timeshift(1w, counters("server.utilization"))
This will return the value of the server.utilization counter metric for each server one week ago. You can then subtract this value from the current value of the same metric to get the difference in utilization. You can also use a chart to visualize the results and sort them by the highest difference in utilization.
質問 # 13
Which of the following can be configured when subscribing to a built-in detector?
- A. Links to a chart.
- B. Alerts on team landing page.
- C. Outbound notifications.
- D. Alerts on a dashboard.
正解：C
解説：
Explanation
According to the web search results1, subscribing to a built-in detector is a way to receive alerts and notifications from Splunk Observability Cloud when certain criteria are met. A built-in detector is a detector that is automatically created and configured by Splunk Observability Cloud based on the data from your integrations, such as AWS, Kubernetes, or OpenTelemetry1. To subscribe to a built-in detector, you need to do the following steps:
Find the built-in detector that you want to subscribe to. You can use the metric finder or the dashboard groups to locate the built-in detectors that are relevant to your data sources1.
Hover over the built-in detector and click the Subscribe button. This will open a dialog box where you can configure your subscription settings1.
Choose an outbound notification channel from the drop-down menu. This is where you can specify how you want to receive the alert notifications from the built-in detector. You can choose from various channels, such as email, Slack, PagerDuty, webhook, and so on2. You can also create a new notification channel by clicking the + icon2.
Enter the notification details for the selected channel. This may include your email address, Slack channel name, PagerDuty service key, webhook URL, and so on2. You can also customize the notification message with variables and markdown formatting2.
Click Save. This will subscribe you to the built-in detector and send you alert notifications through the chosen channel when the detector triggers or clears an alert.
Therefore, option C is correct.
質問 # 14
Changes to which type of metadata result in a new metric time series?
- A. Tags
- B. Dimensions
- C. Properties
- D. Sources
正解：B
解説：
Explanation
The correct answer is A. Dimensions.
Dimensions are metadata in the form of key-value pairs that are sent along with the metrics at the time of ingest. They provide additional information about the metric, such as the name of the host that sent the metric, or the location of the server. Along with the metric name, they uniquely identify a metric time series (MTS)1 Changes to dimensions result in a new MTS, because they create a different combination of metric name and dimensions. For example, if you change the hostname dimension from host1 to host2, you will create a new MTS for the same metric name1 Properties, sources, and tags are other types of metadata that can be applied to existing MTSes after ingest.
They do not contribute to uniquely identify an MTS, and they do not create a new MTS when changed2 To learn more about how to use metadata in Splunk Observability Cloud, you can refer to this documentation2.
1: https://docs.splunk.com/Observability/metrics-and-metadata/metrics.html#Dimensions 2:
https://docs.splunk.com/Observability/metrics-and-metadata/metrics-dimensions-mts.html
質問 # 15
When writing a detector with a large number of MTS, such as memory. free in a deployment with 30,000 hosts, it is possible to exceed the cap of MTS that can be contained in a single plot. Which of the choices below would most likely reduce the number of MTS below the plot cap?
- A. When creating the plot, add a discriminator.
- B. Select the Sharded option when creating the plot.
- C. Add a filter to narrow the scope of the measurement.
- D. Add a restricted scope adjustment to the plot.
正解：C
解説：
Explanation
The correct answer is B. Add a filter to narrow the scope of the measurement.
A filter is a way to reduce the number of metric time series (MTS) that are displayed on a chart or used in a detector. A filter specifies one or more dimensions and values that the MTS must have in order to be included.
For example, if you want to monitor the memory.free metric only for hosts that belong to a certain cluster, you can add a filter like cluster:my-cluster to the plot or detector. This will exclude any MTS that do not have the cluster dimension or have a different value for it1 Adding a filter can help you avoid exceeding the plot cap, which is the maximum number of MTS that can be contained in a single plot. The plot cap is 100,000 by default, but it can be changed by contacting Splunk Support2 To learn more about how to use filters in Splunk Observability Cloud, you can refer to this documentation3.
1: https://docs.splunk.com/Observability/gdi/metrics/search.html#Filter-metrics 2:
https://docs.splunk.com/Observability/gdi/metrics/detectors.html#Plot-cap 3:
https://docs.splunk.com/Observability/gdi/metrics/search.html
質問 # 16
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. Export to CSV.
- C. Send an SMS message.
- D. Invoke a webhook URL.
正解：A、C、D
解説：
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
質問 # 17
Clicking a metric name from the results in metric finder displays the metric in Chart Builder. What action needs to be taken in order to save the chart created in the UI?
- A. Make sure that data is coming in for the metric then save the chart.
- B. Save the chart to a dashboard.
- C. Create a new dashboard and save the chart.
- D. Save the chart to multiple dashboards.
正解：B
解説：
Explanation
According to the web search results, clicking a metric name from the results in metric finder displays the metric in Chart Builder1. Chart Builder is a tool that allows you to create and customize charts using metrics, dimensions, and analytics functions2. To save the chart created in the UI, you need to do the following steps:
Click the Save button on the top right corner of the Chart Builder. This will open a dialog box where you can enter the chart name and description, and choose the dashboard where you want to save the chart.
Enter a name and a description for your chart. The name should be descriptive and unique, and the description should explain the purpose and meaning of the chart.
Choose an existing dashboard from the drop-down menu, or create a new dashboard by clicking the + icon. A dashboard is a collection of charts that display metrics and events for your services or hosts3. You can organize and share dashboards with other users in your organization using dashboard groups3.
Click Save. This will save your chart to the selected dashboard and redirect you to the dashboard view.
You can also access your saved chart from the Dashboards menu on the left navigation bar.
質問 # 18
What constitutes a single metrics time series (MTS)?
- A. A set of data points that use different dimensions but the same metric name.
- B. A series of timestamps that all reflect the same metric.
- C. A set of data points that all have the same metric name and list of dimensions.
- D. A set of metrics that are ordered in series based on timestamp.
正解：C
解説：
Explanation
The correct answer is B. A set of data points that all have the same metric name and list of dimensions.
A metric time series (MTS) is a collection of data points that have the same metric and the same set of dimensions. For example, the following sets of data points are in three separate MTS:
MTS1: Gauge metric cpu.utilization, dimension "hostname": "host1" MTS2: Gauge metric cpu.utilization, dimension "hostname": "host2" MTS3: Gauge metric memory.usage, dimension "hostname": "host1" A metric is a numerical measurement that varies over time, such as CPU utilization or memory usage. A dimension is a key-value pair that provides additional information about the metric, such as the hostname or the location. A data point is a combination of a metric, a dimension, a value, and a timestamp1
質問 # 19
When creating a standalone detector, individual rules in it are labeled according to severity. Which of the choices below represents the possible severity levels that can be selected?
- A. Info, Warning, Minor, Major, and Emergency.
- B. Info, Warning, Minor, Severe, and Critical.
- C. Debug, Warning, Minor, Major, and Critical.
- D. Info, Warning, Minor, Major, and Critical.
正解：D
解説：
Explanation
The correct answer is C. Info, Warning, Minor, Major, and Critical.
When creating a standalone detector, you can define one or more rules that specify the alert conditions and the severity level for each rule. The severity level indicates how urgent or important the alert is, and it can also affect the notification settings and the escalation policy for the alert1 Splunk Observability Cloud provides five predefined severity levels that you can choose from when creating a rule: Info, Warning, Minor, Major, and Critical. Each severity level has a different color and icon to help you identify the alert status at a glance. You can also customize the severity levels by changing their names, colors, or icons2 To learn more about how to create standalone detectors and use severity levels in Splunk Observability Cloud, you can refer to these documentations12.
1:
https://docs.splunk.com/Observability/alerts-detectors-notifications/detectors.html#Create-a-standalone-detector
2: https://docs.splunk.com/Observability/alerts-detectors-notifications/detector-options.html#Severity-levels
質問 # 20
What is one reason a user of Splunk Observability Cloud would want to subscribe to an alert?
- A. To perform transformations on the data used by the detector.
- B. To receive an email notification when a detector is triggered.
- C. To be able to modify the alert parameters.
- D. To determine the root cause of the Issue triggering the detector.
正解：B
解説：
Explanation
One reason a user of Splunk Observability Cloud would want to subscribe to an alert is C. To receive an email notification when a detector is triggered.
A detector is a component of Splunk Observability Cloud that monitors metrics or events and triggers alerts when certain conditions are met. A user can create and configure detectors to suit their monitoring needs and goals1 A subscription is a way for a user to receive notifications when a detector triggers an alert. A user can subscribe to a detector by entering their email address in the Subscription tab of the detector page. A user can also unsubscribe from a detector at any time2 When a user subscribes to an alert, they will receive an email notification that contains information about the alert, such as the detector name, the alert status, the alert severity, the alert time, and the alert message. The email notification also includes links to view the detector, acknowledge the alert, or unsubscribe from the detector2 To learn more about how to use detectors and subscriptions in Splunk Observability Cloud, you can refer to these documentations12.
1: https://docs.splunk.com/Observability/alerts-detectors-notifications/detectors.html 2:
https://docs.splunk.com/Observability/alerts-detectors-notifications/subscribe-to-detectors.html
質問 # 21
An SRE creates a new detector to receive an alert when server latency is higher than 260 milliseconds.
Latency below 260 milliseconds is healthy for their service. The SRE creates a New Detector with a Custom Metrics Alert Rule for latency and sets a Static Threshold alert condition at 260ms.
How can the number of alerts be reduced?
- A. Choose another signal.
- B. Adjust the threshold.
- C. Adjust the notification sensitivity. Duration set to 1 minute.
- D. Adjust the Trigger sensitivity. Duration set to 1 minute.
正解：D
解説：
Explanation
According to the Splunk O11y Cloud Certified Metrics User Track document1, trigger sensitivity is a setting that determines how long a signal must remain above or below a threshold before an alert is triggered. By default, trigger sensitivity is set to Immediate, which means that an alert is triggered as soon as the signal crosses the threshold. This can result in a lot of alerts, especially if the signal fluctuates frequently around the threshold value. To reduce the number of alerts, you can adjust the trigger sensitivity to a longer duration, such as 1 minute, 5 minutes, or 15 minutes. This means that an alert is only triggered if the signal stays above or below the threshold for the specified duration. This can help filter out noise and focus on more persistent issues.
質問 # 22
A customer operates a caching web proxy. They want to calculate the cache hit rate for their service. What is the best way to achieve this?
- A. Percentages and ratios
- B. Timeshift and Bottom N
- C. Timeshift and Top N
- D. Chart Options and metadata
正解：A
解説：
Explanation
According to the Splunk O11y Cloud Certified Metrics User Track document1, percentages and ratios are useful for calculating the proportion of one metric to another, such as cache hits to cache misses, or successful requests to failed requests. You can use the percentage() or ratio() functions in SignalFlow to compute these values and display them in charts. For example, to calculate the cache hit rate for a service, you can use the following SignalFlow code:
percentage(counters("cache.hits"), counters("cache.misses"))
This will return the percentage of cache hits out of the total number of cache attempts. You can also use the ratio() function to get the same result, but as a decimal value instead of a percentage.
ratio(counters("cache.hits"), counters("cache.misses"))
質問 # 23
Which of the following statements are true about local data links? (select all that apply)
- A. Anyone with write permission for a dashboard can add local data links that appear on that dashboard.
- B. Local data links are available on only one dashboard.
- C. Local data links can only have a Splunk Observability Cloud internal destination.
- D. Only Splunk Observability Cloud administrators can create local links.
正解：A、B
解説：
Explanation
The correct answers are A and D.
According to the Get started with Splunk Observability Cloud document1, one of the topics that is covered in the Getting Data into Splunk Observability Cloud course is global and local data links. Data links are shortcuts that provide convenient access to related resources, such as Splunk Observability Cloud dashboards, Splunk Cloud Platform and Splunk Enterprise, custom URLs, and Kibana logs.
The document explains that there are two types of data links: global and local. Global data links are available on all dashboards and charts, while local data links are available on only one dashboard. The document also provides the following information about local data links:
Anyone with write permission for a dashboard can add local data links that appear on that dashboard.
Local data links can have either a Splunk Observability Cloud internal destination or an external destination, such as a custom URL or a Kibana log.
Only Splunk Observability Cloud administrators can delete local data links.
Therefore, based on this document, we can conclude that A and D are true statements about local data links. B and C are false statements because:
B is false because local data links can have an external destination as well as an internal one.
C is false because anyone with write permission for a dashboard can create local data links, not just administrators.
質問 # 24
Where does the Splunk distribution of the OpenTelemetry Collector store the configuration files on Linux machines by default?
- A. /opt/splunk/
- B. /etc/otel/collector/
- C. /etc/opentelemetry/
- D. /etc/system/default/
正解：B
解説：
Explanation
The correct answer is B. /etc/otel/collector/
According to the web search results, the Splunk distribution of the OpenTelemetry Collector stores the configuration files on Linux machines in the /etc/otel/collector/ directory by default. You can verify this by looking at the first result1, which explains how to install the Collector for Linux manually. It also provides the locations of the default configuration file, the agent configuration file, and the gateway configuration file.
To learn more about how to install and configure the Splunk distribution of the OpenTelemetry Collector, you can refer to this documentation2.
1: https://docs.splunk.com/Observability/gdi/opentelemetry/install-linux-manual.html 2:
https://docs.splunk.com/Observability/gdi/opentelemetry.html
質問 # 25
A DevOps engineer wants to determine if the latency their application experiences is growing fester after a new software release a week ago. They have already created two plot lines, A and B, that represent the current latency and the latency a week ago, respectively. How can the engineer use these two plot lines to determine the rate of change in latency?
- A. Create a temporary plot by dragging items A and B into the Analytics Explorer window.
- B. Create a plot C using the formula (A/B-l) and add a scale: 100 function to express the rate of change as a percentage.
- C. Create a temporary plot by clicking the Change% button in the upper-right corner of the plot showing lines A and B.
- D. Create a plot C using the formula (A-B) and add a scale:percent function to express the rate of change as a percentage.
正解：B
解説：
Explanation
The correct answer is C. Create a plot C using the formula (A/B-l) and add a scale: 100 function to express the rate of change as a percentage.
To calculate the rate of change in latency, you need to compare the current latency (plot A) with the latency a week ago (plot B). One way to do this is to use the formula (A/B-l), which gives you the ratio of the current latency to the previous latency minus one. This ratio represents how much the current latency has increased or decreased relative to the previous latency. For example, if the current latency is 200 ms and the previous latency is 100 ms, then the ratio is (200/100-l) = 1, which means the current latency is 100% higher than the previous latency1 To express the rate of change as a percentage, you need to multiply the ratio by 100. You can do this by adding a scale: 100 function to the formula. This function scales the values of the plot by a factor of 100. For example, if the ratio is 1, then the scaled value is 100%2 To create a plot C using the formula (A/B-l) and add a scale: 100 function, you need to follow these steps:
Select plot A and plot B from the Metric Finder.
Click on Add Analytics and choose Formula from the list of functions.
In the Formula window, enter (A/B-l) as the formula and click Apply.
Click on Add Analytics again and choose Scale from the list of functions.
In the Scale window, enter 100 as the factor and click Apply.
You should see a new plot C that shows the rate of change in latency as a percentage.
To learn more about how to use formulas and scale functions in Splunk Observability Cloud, you can refer to these documentations34.
1: https://www.mathsisfun.com/numbers/percentage-change.html 2:
https://docs.splunk.com/Observability/gdi/metrics/analytics.html#Scale 3:
https://docs.splunk.com/Observability/gdi/metrics/analytics.html#Formula 4:
https://docs.splunk.com/Observability/gdi/metrics/analytics.html#Scale
質問 # 26
Which of the following rollups will display the time delta between a datapoint being sent and a datapoint being received?
- A. Delay
- B. Jitter
- C. Lag
- D. Latency
正解：C
解説：
Explanation
According to the Splunk Observability Cloud documentation1, lag is a rollup function that returns the difference between the most recent and the previous data point values seen in the metric time series reporting interval. This can be used to measure the time delta between a data point being sent and a data point being received, as long as the data points have timestamps that reflect their send and receive times. For example, if a data point is sent at 10:00:00 and received at 10:00:05, the lag value for that data point is 5 seconds.
質問 # 27
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Splunk SPLK-4001認定を獲得することは、個人がSplunkのメトリック監視機能を深く理解しており、クラウド環境でこれらのツールを活用できることを示しています。これは、クラウドインフラストラクチャの管理と監視を担当し、この分野での専門知識を実証したいと考えているITプロフェッショナルにとって貴重な資格です。この認定は、クラウドインフラ管理の分野でより挑戦的な役割を引き受けるために必要なスキルと知識を提供することにより、専門家がキャリアを促進するのに役立ちます。
Splunk O11y Cloud Certified Metrics User練習テスト2024年最新のストレスなしでSPLK-4001合格！：https://drive.google.com/open?id=1O6v0jTIJCv-vbveGghFn1yhEX2zlJ_LI
合格させるSPLK-4001テストエンジンとPDFで完全版無料問題集：https://www.goshiken.com/Splunk/SPLK-4001-mondaishu.html