Real Splunk SPLK-4001 Exam Questions [Updated 2026]
SPLK-4001 Exam Dumps Pass with Updated 2026 Splunk O11y Cloud Certified Metrics User
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.
The Splunk O11y Cloud Certified Metrics User certification exam will test the candidate’s knowledge and skills in various aspects of the Splunk Metrics platform, including data ingestion, troubleshooting, and analysis. Through this certification program, candidates will also learn about the various tools and technologies used to collect and analyze metrics, such as dashboards, reports, and alerts. In addition, the exam will cover various topics related to cloud monitoring and analytics, such as monitoring cloud-based applications and infrastructure, detecting and troubleshooting issues, and optimizing performance.
NEW QUESTION # 26
With exceptions for transformations or timeshifts, at what resolution do detectors operate?
- A. The resolution of the chart
- B. The resolution of the dashboard
- C. 10 seconds
- D. Native resolution
Answer: D
Explanation:
Explanation
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.
NEW QUESTION # 27
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. Tlmeshift
- B. Standard deviation
- C. Rate
- D. Sum transformation
Answer: A
Explanation:
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.
NEW 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. Timeshift and Bottom N
- B. Percentages and ratios
- C. Timeshift and Top N
- D. Chart Options and metadata
Answer: B
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"))
NEW QUESTION # 29
What constitutes a single metrics time series (MTS)?
- A. A series of timestamps that all reflect the same metric.
- B. A set of data points that use different dimensions but the same metric name.
- 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.
Answer: C
Explanation:
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
NEW QUESTION # 30
What happens when the limit of allowed dimensions is exceeded for an MTS?
- A. The datapoint is updated.
- B. The datapoint is dropped.
- C. The additional dimensions are dropped.
- D. The datapoint is averaged.
Answer: C
Explanation:
Explanation
According to the web search results, dimensions are metadata in the form of key-value pairs that monitoring software sends in along with the metrics. The set of metric time series (MTS) dimensions sent during ingest is used, along with the metric name, to uniquely identify an MTS1. Splunk Observability Cloud has a limit of 36 unique dimensions per MTS2. If the limit of allowed dimensions is exceeded for an MTS, the additional dimensions are dropped and not stored or indexed by Observability Cloud2. This means that the data point is still ingested, but without the extra dimensions. Therefore, option A is correct.
NEW QUESTION # 31
A customer wants to share a collection of charts with their entire SRE organization. What feature of Splunk Observability Cloud makes this possible?
- A. Chart exporter
- B. Public dashboards
- C. Dashboard groups
- D. Shared charts
Answer: C
Explanation:
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 create dashboard groups based on different criteria, such as service, team, role, or topic. You can also set permissions for each dashboard group, such as who can view, edit, or manage the dashboards in the group. Dashboard groups make it possible to share a collection of charts with your entire SRE organization, or any other group of users that you want to collaborate with.
NEW QUESTION # 32
The Sum Aggregation option for analytic functions does which of the following?
- A. Calculates the sum of values per time series across a period of time.
- B. Calculates the number of MTS present in the plot.
- C. Calculates the sum of values present in the input time series across the entire environment or per group.
- D. Calculates 1/2 of the values present in the input time series.
Answer: C
Explanation:
Explanation
According to the Splunk Test Blueprint - O11y Cloud Metrics User document1, one of the metrics concepts that is covered in the exam is analytic functions. Analytic functions are mathematical operations that can be applied to metrics to transform, aggregate, or analyze them.
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 Analytic Functions, which explains that analytic functions can be used to perform calculations on metrics, such as sum, average, min, max, count, etc. The document also provides examples of how to use analytic functions in charts and dashboards.
One of the analytic functions that can be used is Sum Aggregation, which calculates the sum of values present in the input time series across the entire environment or per group. The document gives an example of how to use Sum Aggregation to calculate the total CPU usage across all hosts in a group by using the following syntax:
sum(cpu.utilization) by hostgroup
NEW QUESTION # 33
To refine a search for a metric a customer types host: test-*. What does this filter return?
- A. Only metrics with a dimension of host and a value beginning with test-.
- B. Error
- C. Every metric except those with a dimension of host and a value equal to test.
- D. Only metrics with a value of test- beginning with host.
Answer: A
Explanation:
The correct answer is A. Only metrics with a dimension of host and a value beginning with test-.
This filter returns the metrics that have a host dimension that matches the pattern test-. For example, test-01, test-abc, test-xyz, etc. The asterisk () is a wildcard character that can match any string of characters1 To learn more about how to filter metrics in Splunk Observability Cloud, you can refer to this documentation2.
1: https://docs.splunk.com/Observability/gdi/metrics/search.html#Filter-metrics 2: https://docs.splunk.com/Observability/gdi/metrics/search.html
NEW QUESTION # 34
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/system/default/
- D. /etc/opentelemetry/
Answer: B
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
NEW QUESTION # 35
Which of the following are correct ports for the specified components in the OpenTelemetry Collector?
- A. gRPC (6831), SignalFx (4317), Fluentd (9080)
- B. gRPC (4459), SignalFx (9166), Fluentd (8956)
- C. gRPC (4000), SignalFx (9943), Fluentd (6060)
- D. gRPC (4317), SignalFx (9080), Fluentd (8006)
Answer: D
Explanation:
The correct answer is D. gRPC (4317), SignalFx (9080), Fluentd (8006).
According to the web search results, these are the default ports for the corresponding components in the OpenTelemetry Collector. You can verify this by looking at the table of exposed ports and endpoints in the first result1. You can also see the agent and gateway configuration files in the same result for more details.
1: https://docs.splunk.com/observability/gdi/opentelemetry/exposed-endpoints.html
NEW QUESTION # 36
A customer is experiencing issues getting metrics from a new receiver they have configured in the OpenTelemetry Collector. How would the customer go about troubleshooting further with the logging exporter?
- A. Adding logging into the metrics receiver pipeline:
- B. Adding debug into the metrics receiver pipeline:
- C. Adding debug into the metrics exporter pipeline:
- D. Adding logging into the metrics exporter pipeline:
Answer: A
Explanation:
Explanation
The correct answer is B. Adding logging into the metrics receiver pipeline.
The logging exporter is a component that allows the OpenTelemetry Collector to send traces, metrics, and logs directly to the console. It can be used to diagnose and troubleshoot issues with telemetry received and processed by the Collector, or to obtain samples for other purposes1 To activate the logging exporter, you need to add it to the pipeline that you want to diagnose. In this case, since you are experiencing issues with a new receiver for metrics, you need to add the logging exporter to the metrics receiver pipeline. This will create a new plot that shows the metrics received by the Collector and any errors or warnings that might occur1 The image that you have sent with your question shows how to add the logging exporter to the metrics receiver pipeline. You can see that the exporters section of the metrics pipeline includes logging as one of the options.
This means that the metrics received by any of the receivers listed in the receivers section will be sent to the logging exporter as well as to any other exporters listed2 To learn more about how to use the logging exporter in Splunk Observability Cloud, you can refer to this documentation1.
1: https://docs.splunk.com/Observability/gdi/opentelemetry/components/logging-exporter.html 2:
https://docs.splunk.com/Observability/gdi/opentelemetry/exposed-endpoints.html
NEW QUESTION # 37
What is the limit on the number of properties that an MTS can have?
- A. 0
- B. No limit
- C. 1
- D. 2
Answer: C
Explanation:
Explanation
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
NEW QUESTION # 38
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. Tlmeshift
- B. Standard deviation
- C. Rate
- D. Sum transformation
Answer: A
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.
NEW QUESTION # 39
When installing OpenTelemetry Collector, which error message is indicative that there is a misconfigured realm or access token?
- A. 401 (UNAUTHORIZED)
- B. 503 (SERVICE UNREACHABLE)
- C. 403 (NOT ALLOWED)
- D. 404 (NOT FOUND)
Answer: A
Explanation:
The correct answer is C. 401 (UNAUTHORIZED).
According to the web search results, a 401 (UNAUTHORIZED) error message is indicative that there is a misconfigured realm or access token when installing OpenTelemetry Collector1. A 401 (UNAUTHORIZED) error message means that the request was not authorized by the server due to invalid credentials. A realm is a parameter that specifies the scope of protection for a resource, such as a Splunk Observability Cloud endpoint. An access token is a credential that grants access to a resource, such as a Splunk Observability Cloud API. If the realm or the access token is misconfigured, the request to install OpenTelemetry Collector will be rejected by the server with a 401 (UNAUTHORIZED) error message.
Option A is incorrect because a 403 (NOT ALLOWED) error message is not indicative that there is a misconfigured realm or access token when installing OpenTelemetry Collector. A 403 (NOT ALLOWED) error message means that the request was authorized by the server but not allowed due to insufficient permissions. Option B is incorrect because a 404 (NOT FOUND) error message is not indicative that there is a misconfigured realm or access token when installing OpenTelemetry Collector. A 404 (NOT FOUND) error message means that the request was not found by the server due to an invalid URL or resource. Option D is incorrect because a 503 (SERVICE UNREACHABLE) error message is not indicative that there is a misconfigured realm or access token when installing OpenTelemetry Collector. A 503 (SERVICE UNREACHABLE) error message means that the server was unable to handle the request due to temporary overload or maintenance.
NEW QUESTION # 40
Which of the following are required in the configuration of a data point? (select all that apply)
- A. Value
- B. Metric Name
- C. Metric Type
- D. Timestamp
Answer: A,B,D
Explanation:
The required components in the configuration of a data point are:
Metric Name: A metric name is a string that identifies the type of measurement that the data point represents, such as cpu.utilization, memory.usage, or response.time. A metric name is mandatory for every data point, and it must be unique within a Splunk Observability Cloud organization1 Timestamp: A timestamp is a numerical value that indicates the time at which the data point was collected or generated. A timestamp is mandatory for every data point, and it must be in epoch time format, which is the number of seconds since January 1, 1970 UTC1 Value: A value is a numerical value that indicates the magnitude or quantity of the measurement that the data point represents. A value is mandatory for every data point, and it must be compatible with the metric type of the data point1 Therefore, the correct answer is A, C, and D.
To learn more about how to configure data points in Splunk Observability Cloud, you can refer to this documentation1.
1: https://docs.splunk.com/Observability/gdi/metrics/metrics.html#Data-points
NEW QUESTION # 41
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. Local data links can only have a Splunk Observability Cloud internal destination.
- D. Anyone with write permission for a dashboard can add local data links that appear on that dashboard.
Answer: A,D
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 # 42
Which of the following are true about organization metrics? (select all that apply)
- A. Organization metrics are included for free.
- B. Organization metrics count towards custom MTS limits.
- C. Organization metrics give insights into system usage, system limits, data ingested and token quotas.
- D. A user can plot and alert on them like metrics they send to Splunk Observability Cloud.
Answer: A,C,D
Explanation:
Explanation
The correct answer is A, C, and D. Organization metrics give insights into system usage, system limits, data ingested and token quotas. Organization metrics are included for free. A user can plot and alert on them like metrics they send to Splunk Observability Cloud.
Organization metrics are a set of metrics that Splunk Observability Cloud provides to help you measure your organization's usage of the platform. They include metrics such as:
Ingest metrics: Measure the data you're sending to Infrastructure Monitoring, such as the number of data points you've sent.
App usage metrics: Measure your use of application features, such as the number of dashboards in your organization.
Integration metrics: Measure your use of cloud services integrated with your organization, such as the number of calls to the AWS CloudWatch API.
Resource metrics: Measure your use of resources that you can specify limits for, such as the number of custom metric time series (MTS) you've created1 Organization metrics are not charged and do not count against any system limits. You can view them in built-in charts on the Organization Overview page or in custom charts using the Metric Finder. You can also create alerts based on organization metrics to monitor your usage and performance1 To learn more about how to use organization metrics in Splunk Observability Cloud, you can refer to this documentation1.
1: https://docs.splunk.com/observability/admin/org-metrics.html
NEW QUESTION # 43
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The Splunk O11y Cloud Certified Metrics User certification exam is available online and can be taken from anywhere in the world. SPLK-4001 exam consists of 60 multiple-choice questions and candidates have two hours to complete the exam. Candidates who pass the exam will receive the Splunk O11y Cloud Certified Metrics User certification, which is valid for two years.
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