Pass Splunk SPLK-4001 Actual Free Exam Q&As Updated Dump Apr 03, 2026
Latest SPLK-4001 Actual Free Exam Updated 59 Questions
Splunk SPLK-4001 certification exam is a globally recognized certification program that demonstrates the candidate's mastery in using Splunk's O11y Cloud platform to monitor and analyze metrics. Splunk O11y Cloud Certified Metrics User certification is recognized by industry experts and employers, providing candidates with a competitive edge in the job market. Splunk O11y Cloud Certified Metrics User certification program also provides candidates with access to Splunk's community of experts, resources, and tools, enabling them to stay up-to-date with the latest trends and best practices in using Splunk's O11y Cloud platform.
Splunk SPLK-4001 exam is designed for individuals who want to showcase their expertise in metrics collection and analysis using the Splunk platform. Splunk O11y Cloud Certified Metrics User certification is a testament to the skills and knowledge required to utilize Splunk's monitoring and observability capabilities to the fullest. As the demand for observability and monitoring solutions continues to grow, the SPLK-4001 certification can help professionals stand out in a competitive job market.
One of the key benefits of earning the Splunk SPLK-4001 certification is that it can help you stand out in a competitive job market. Employers are always looking for skilled IT professionals who can help them manage and monitor their cloud-based environments effectively. By earning this certification, you will demonstrate to potential employers that you have the skills and knowledge necessary to excel in this role. Additionally, this certification can help you advance your career by opening up new opportunities for promotion and professional development.
NEW QUESTION # 33
Which of the following statements are true about local data links? (select all that apply)
- A. Local data links are available on only one dashboard.
- B. Only Splunk Observability Cloud administrators can create local links.
- C. Anyone with write permission for a dashboard can add local data links that appear on that dashboard.
- D. Local data links can only have a Splunk Observability Cloud internal destination.
Answer: A,C
Explanation:
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.
NEW QUESTION # 34
A user wants to add a link to an existing dashboard from an alert. When they click the dimension value in the alert message, they are taken to the dashboard keeping the context. How can this be accomplished? (select all that apply)
- A. Add the link to the alert message body.
- B. Add a link to the Runbook URL.
- C. Build a global data link.
- D. Add a link to the field.
Answer: C,D
Explanation:
Explanation
The possible ways to add a link to an existing dashboard from an alert are:
Build a global data link. A global data link is a feature that allows you to create a link from any dimension value in any chart or table to a dashboard of your choice. You can specify the source and target dashboards, the dimension name and value, and the query parameters to pass along. When you click on the dimension value in the alert message, you will be taken to the dashboard with the context preserved1 Add a link to the field. A field link is a feature that allows you to create a link from any field value in any search result or alert message to a dashboard of your choice. You can specify the field name and value, the dashboard name and ID, and the query parameters to pass along. When you click on the field value in the alert message, you will be taken to the dashboard with the context preserved2 Therefore, the correct answer is A and C.
To learn more about how to use global data links and field links in Splunk Observability Cloud, you can refer to these documentations12.
1: https://docs.splunk.com/Observability/gdi/metrics/charts.html#Global-data-links 2:
https://docs.splunk.com/Observability/gdi/metrics/search.html#Field-links
NEW QUESTION # 35
Which of the following are ways to reduce flapping of a detector? (select all that apply)
- A. Apply a smoothing transformation (like a rolling mean) to the input data for the detector.
- B. Enable the anti-flap setting in the detector options menu.
- C. Configure a duration or percent of duration for the alert.
- D. Establish a reset threshold for the detector.
Answer: A,C
Explanation:
Explanation
According to the Splunk Lantern article Resolving flapping detectors in Splunk Infrastructure Monitoring, flapping is a phenomenon where alerts fire and clear repeatedly in a short period of time, due to the signal fluctuating around the threshold value. To reduce flapping, the article suggests the following ways:
Configure a duration or percent of duration for the alert: This means that you require the signal to stay above or below the threshold for a certain amount of time or percentage of time before triggering an alert. This can help filter out noise and focus on more persistent issues.
Apply a smoothing transformation (like a rolling mean) to the input data for the detector: This means that you replace the original signal with the average of its last several values, where you can specify the window length. This can reduce the impact of a single extreme observation and make the signal less fluctuating.
NEW QUESTION # 36
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. Save the chart to multiple dashboards.
- B. Make sure that data is coming in for the metric then save the chart.
- C. Save the chart to a dashboard.
- D. Create a new dashboard and save the chart.
Answer: C
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.
NEW QUESTION # 37
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. Hide the edit menu on the dashboard group.
- C. Link the dashboard group to the team.
- D. Restrict the write access on the dashboard group.
Answer: D
Explanation:
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 organization1. You can set permissions for each dashboard group, such as who can view, edit, or manage the dashboards in the group1. 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 group1.
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 group1.
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 group1.
Click Save. This will create a dashboard group that no one else can edit.
NEW QUESTION # 38
Which of the following is optional, but highly recommended to include in a datapoint?
- A. Metric name
- B. Value
- C. Metric type
- D. Timestamp
Answer: C
Explanation:
Explanation
The correct answer is D. Metric type.
A metric type is an optional, but highly recommended field that specifies the kind of measurement that a datapoint represents. For example, a metric type can be gauge, counter, cumulative counter, or histogram. A metric type helps Splunk Observability Cloud to interpret and display the data correctly1 To learn more about how to send metrics to Splunk Observability Cloud, you can refer to this documentation2.
1: https://docs.splunk.com/Observability/gdi/metrics/metrics.html#Metric-types 2:
https://docs.splunk.com/Observability/gdi/metrics/metrics.html
NEW QUESTION # 39
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. Save the chart to multiple dashboards.
- B. Make sure that data is coming in for the metric then save the chart.
- C. Save the chart to a dashboard.
- D. Create a new dashboard and save the chart.
Answer: C
Explanation:
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.
NEW QUESTION # 40
An SRE creates an event feed chart in a dashboard that shows a list of events that meet criteria they specify.
Which of the following should they include? (select all that apply)
- A. Custom events that have been sent in from an external source.
- B. Random alerts from active detectors.
- C. Events created when a detector triggers an alert.
- D. Events created when a detector clears an alert.
Answer: A,C,D
Explanation:
Explanation
According to the web search results1, an event feed chart is a type of chart that shows a list of events that meet criteria you specify. An event feed chart can display one or more event types depending on how you specify the criteria. The event types that you can include in an event feed chart are:
Custom events that have been sent in from an external source: These are events that you have created or received from a third-party service or tool, such as AWS CloudWatch, GitHub, Jenkins, or PagerDuty.
You can send custom events to Splunk Observability Cloud using the API or the Event Ingest Service.
Events created when a detector triggers or clears an alert: These are events that are automatically generated by Splunk Observability Cloud when a detector evaluates a metric or dimension and finds that it meets the alert condition or returns to normal. You can create detectors to monitor and alert on various metrics and dimensions using the UI or the API.
Therefore, option A, B, and D are correct.
NEW QUESTION # 41
Changes to which type of metadata result in a new metric time series?
- A. Sources
- B. Dimensions
- C. Properties
- D. Tags
Answer: B
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
NEW QUESTION # 42
One server in a customer's data center is regularly restarting due to power supply issues. What type of dashboard could be used to view charts and create detectors for this server?
- A. Machine dashboard
- B. Single-instance dashboard
- C. Multiple-service dashboard
- D. Server dashboard
Answer: B
Explanation:
Explanation
According to the Splunk O11y Cloud Certified Metrics User Track document1, a single-instance dashboard is a type of dashboard that displays charts and information for a single instance of a service or host. You can use a single-instance dashboard to monitor the performance and health of a specific server, such as the one that is restarting due to power supply issues. You can also create detectors for the metrics that are relevant to the server, such as CPU usage, memory usage, disk usage, and uptime. Therefore, option A is correct.
NEW QUESTION # 43
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 clicking the Change% button in the upper-right corner of the plot showing lines A and B.
- B. Create a plot C using the formula (A-B) and add a scale:percent function to express the rate of change as a percentage.
- 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.
- D. Create a temporary plot by dragging items A and B into the Analytics Explorer window.
Answer: C
Explanation:
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
NEW QUESTION # 44
A Software Engineer is troubleshooting an issue with memory utilization in their application. They released a new canary version to production and now want to determine if the average memory usage is lower for requests with the 'canary' version dimension. They've already opened the graph of memory utilization for their service.
How does the engineer see if the new release lowered average memory utilization?
- A. On the chart for plot A, select Add Analytics, then select Mean:Aggregation. In the window that appears, select 'version' from the Group By field.
- B. On the chart for plot A, scroll to the end and click Enter Function, then enter 'A/B-l'.
- C. On the chart for plot A, select Add Analytics, then select MeanrTransformation. In the window that appears, select 'version' from the Group By field.
- D. On the chart for plot A, click the Compare Means button. In the window that appears, type 'version1.
Answer: A
Explanation:
The correct answer is C. On the chart for plot A, select Add Analytics, then select Mean:Aggregation. In the window that appears, select 'version' from the Group By field.
This will create a new plot B that shows the average memory utilization for each version of the application. The engineer can then compare the values of plot B for the 'canary' and 'stable' versions to see if there is a significant difference.
To learn more about how to use analytics functions in Splunk Observability Cloud, you can refer to this documentation1.
1: https://docs.splunk.com/Observability/gdi/metrics/analytics.html
NEW QUESTION # 45
Which of the following are accurate reasons to clone a detector? (select all that apply)
- A. To modify the rules without affecting the existing detector.
- B. To explore how a detector was created without risk of changing it.
- C. To add an additional recipient to the detector's alerts.
- D. To reduce the amount of billed TAPM for the detector.
Answer: A,B
Explanation:
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.
NEW QUESTION # 46
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. Debug, Warning, Minor, Major, and Critical.
- B. Info, Warning, Minor, Major, and Emergency.
- C. Info, Warning, Minor, Major, and Critical.
- D. Info, Warning, Minor, Severe, and Critical.
Answer: C
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
NEW QUESTION # 47
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?
- A. Each data marker represents the 10 second delta between counter values.
- B. Each data marker represents the sum of API calls in the hour leading up to the data marker.
- C. Each data marker represents the average of the sum of datapoints over the last minute, averaged over the hour.
- D. Each data marker represents the average hourly rate of API calls.
Answer: B
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 # 48
Which of the following chart visualization types are unaffected by changing the time picker on a dashboard? (select all that apply)
- A. Heatmap
- B. Line
- C. List
- D. Single Value
Answer: C,D
Explanation:
The chart visualization types that are unaffected by changing the time picker on a dashboard are:
Single Value: A single value chart shows the current value of a metric or an expression. It does not depend on the time range of the dashboard, but only on the data resolution and rollup function of the chart1 List: A list chart shows the values of a metric or an expression for each dimension value in a table format. It does not depend on the time range of the dashboard, but only on the data resolution and rollup function of the chart2 Therefore, the correct answer is A and D.
To learn more about how to use different chart visualization types in Splunk Observability Cloud, you can refer to this documentation3.
1: https://docs.splunk.com/Observability/gdi/metrics/charts.html#Single-value 2: https://docs.splunk.com/Observability/gdi/metrics/charts.html#List 3: https://docs.splunk.com/Observability/gdi/metrics/charts.html
NEW QUESTION # 49
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?
- A. Each data marker represents the 10 second delta between counter values.
- B. Each data marker represents the sum of API calls in the hour leading up to the data marker.
- C. Each data marker represents the average of the sum of datapoints over the last minute, averaged over the hour.
- D. Each data marker represents the average hourly rate of API calls.
Answer: B
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 # 50
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