Splunk Splunk Certifications SPLK-4001 Questions & Answers

• Question 21:

  Which of the following can be configured when subscribing to a built-in detector?

  A. Alerts on team landing page.

  B. Alerts on a dashboard.

  C. Outbound notifications.

  D. Links to a chart.

  Correct Answer: C

  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 sources.

  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 on. You can also create a new notification channel by clicking the +

  icon.

  Enter the notification details for the selected channel. This may include your email address, Slack channel name, PagerDuty service key, webhook URL, and so on. You can also customize the notification message with variables and

  markdown formatting.

  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.

• Question 22:

  How is it possible to create a dashboard group that no one else can edit?

  A. Ask the admin to lock the dashboard group.

  B. Restrict the write access on the dashboard group.

  C. Link the dashboard group to the team.

  D. Hide the edit menu on the dashboard group.

  Correct Answer: B

  According to the web search results, dashboard groups are a feature of Splunk Observability Cloud that allows you to organize and share dashboards with other users in your organization. You can set permissions for each dashboard group, such as who can view, edit, or manage the dashboards in the group. To create a dashboard group that no one else can edit, you need to do the following steps:

  Create a dashboard group as usual, by selecting Dashboard Group from the Create menu on the navigation bar, entering a name and description, and adding dashboards to the group.

  Select Alert settings from the Dashboard actions menu () on the top right corner of the dashboard group. This will open a dialog box where you can configure the permissions for the dashboard group.

  Under Write access, select Only me. This will restrict the write access to the dashboard group to yourself only. No one else will be able to edit or delete the dashboards in the group.

  Click Save. This will create a dashboard group that no one else can edit.

• Question 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. Invoke a webhook URL.

  B. Export to CSV.

  C. Send an SMS message.

  D. Send to email addresses.

  Correct Answer: ACD

  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 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 Therefore, the correct answer is A, C, and D. https://docs.splunk.com/Documentation/Splunk/latest/Alert/Webhooks https://docs.splunk.com/Documentation/Splunk/latest/Alert/SMSnotification https://docs.splunk.com/Documentation/Splunk/latest/Alert/Emailnotification

• Question 24:

  Which of the following statements about adding properties to MTS are true? (select all that apply)

  A. Properties can be set via the API.

  B. Properties are sent in with datapoints.

  C. Properties are applied to dimension key:value pairs and propagated to all MTS with that dimension

  D. Properties can be set in the UI under Metric Metadata.

  Correct Answer: AD

  According to the web search results, properties are key-value pairs that you can assign to dimensions of existing metric time series (MTS) in Splunk Observability Cloud1. Properties provide additional context and information about the metrics, such as the environment, role, or owner of the dimension. For example, you can add the property use: QA to the host dimension of your metrics to indicate that the host that is sending the data is used for QA. To add properties to MTS, you can use either the API or the UI. The API allows you to programmatically create, update, delete, and list properties for dimensions using HTTP requests2. The UI allows you to interactively create, edit, and delete properties for dimensions using the Metric Metadata page under Settings3. Therefore, option A and D are correct.

• Question 25:

  With exceptions for transformations or timeshifts, at what resolution do detectors operate?

  A. 10 seconds

  B. The resolution of the chart

  C. The resolution of the dashboard

  D. Native resolution

  Correct Answer: D

  According to the Splunk Observability Cloud documentation1, detectors operate at the native resolution of the metric or dimension that they monitor, with some exceptions for transformations or timeshifts. The native resolution is the frequency at which the data points are reported by the source. For example, if a metric is reported every 10 seconds, the detector will evaluate the metric every 10 seconds. The native resolution ensures that the detector uses the most granular and accurate data available for alerting.

• Question 26:

  What is one reason a user of Splunk Observability Cloud would want to subscribe to an alert?

  A. To determine the root cause of the Issue triggering the detector.

  B. To perform transformations on the data used by the detector.

  C. To receive an email notification when a detector is triggered.

  D. To be able to modify the alert parameters.

  Correct Answer: C

  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 goals 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 time 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 detector To learn more about how to use detectors and subscriptions in Splunk Observability Cloud, you can refer to these documentations. https://docs.splunk.com/Observability/alerts-detectors-notifications/detectors.html https://docs.splunk.com/Observability/alerts-detectors-notifications/subscribe-to-detectors.html

• Question 27:

  For a high-resolution metric, what is the highest possible native resolution of the metric?

  A. 2 seconds

  B. 15 seconds

  C. 1 second

  D. 5 seconds

  Correct Answer: C

  The correct answer is C. 1 second.

  According to the Splunk Test Blueprint - O11y Cloud Metrics User document1, one of the metrics concepts that is covered in the exam is data resolution and rollups. Data resolution refers to the granularity of the metric data points, and rollups are the process of aggregating data points over time to reduce the amount of data stored. The Splunk O11y Cloud Certified Metrics User Track document2 states that one of the recommended courses for preparing for the exam is Introduction to Splunk Infrastructure Monitoring, which covers the basics of metrics monitoring and visualization. In the Introduction to Splunk Infrastructure Monitoring course, there is a section on Data Resolution and Rollups, which explains that Splunk Observability Cloud collects high- resolution metrics at 1-second intervals by default, and then applies rollups to reduce the data volume over time. The document also provides a table that shows the different rollup intervals and retention periods for different resolutions. Therefore, based on these documents, we can conclude that for a high-resolution metric, the highest possible native resolution of the metric is 1 second.

• Question 28:

  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

  Correct Answer: A

  According to the Splunk O11y Cloud Certified Metrics User Track document, 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"))

• Question 29:

  To smooth a very spiky cpu.utilization metric, what is the correct analytic function to better see if the cpu. utilization for servers is trending up over time?

  A. Rate/Sec

  B. Median

  C. Mean (by host)

  D. Mean (Transformation)

  Correct Answer: D

  The correct answer is D. Mean (Transformation).

  According to the web search results, a mean transformation is an analytic function that returns the average value of a metric or a dimension over a specified time interval. A mean transformation can be used to smooth a very spiky metric, such as cpu.utilization, by reducing the impact of outliers and noise. A mean transformation can also help to see if the metric is trending up or down over time, by showing the general direction of the average value. For example, to smooth the cpu.utilization metric and see if it is trending up over time, you can use the following SignalFlow code: mean(1h, counters("cpu.utilization")) This will return the average value of the cpu.utilization counter metric for each metric time series (MTS) over the last hour. You can then use a chart to visualize the results and compare the mean values across different MTS. Option A is incorrect because rate/sec is not an analytic function, but rather a rollup function that returns the rate of change of data points in the MTS reporting interval1. Rate/sec can be used to convert cumulative counter metrics into counter metrics, but it does not smooth or trend a metric. Option B is incorrect because median is not an analytic function, but rather an aggregation function that returns the middle value of a metric or a dimension over the entire time range1. Median can be used to find the typical value of a metric, but it does not smooth or trend a metric. Option C is incorrect because mean (by host) is not an analytic function, but rather an aggregation function that returns the average value of a metric or a dimension across all MTS with the same host dimension1. Mean (by host) can be used to compare the performance of different hosts, but it does not smooth or trend a metric. Mean (Transformation) is an analytic function that allows you to smooth a very spiky metric by applying a moving average over a specified time window. This can help you see the general trend of the metric over time, without being distracted by the short-term fluctuations To use Mean (Transformation) on a cpu.utilization metric, you need to select the metric from the Metric Finder, then click on Add Analytics and choose Mean (Transformation) from the list of functions. You can then specify the time window for the moving average, such as 5 minutes, 15 minutes, or 1 hour. You can also group the metric by host or any other dimension to compare the smoothed values across different servers2 To learn more about how to use Mean (Transformation) and other analytic functions in Splunk Observability Cloud, you can refer to this documentation. https://docs.splunk.com/Observability/gdi/metrics/analytics.html#Mean-Transformation https://docs.splunk.com/Observability/gdi/metrics/analytics.html

• Question 30:

  What is the limit on the number of properties that an MTS can have?

  A. 64

  B. 36

  C. No limit

  D. 50

  Correct Answer: A

  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 QA 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 documentation. https://docs.splunk.com/Observability/metrics-and-metadata/metrics-dimensions- mts.html#Custom-properties https://docs.splunk.com/Observability/metrics-and- metadata/metrics-dimensions-mts.html