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Splunk SPLK-4001 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Create Efficient Dashboards and Alerts10%- Dashboard Optimization
  • 1. Single-instance dashboards
    • 2. Alert customization
      • 3. Dashboard instructions
        • 4. Event overlays
          • 5. Data links configuration
            • 6. Troubleshooting charts and alerts
              Topic 2: Get Metrics In with OpenTelemetry10%- OpenTelemetry Collector Deployment
              • 1. Edit configuration files
                • 2. Deploy the OTel Collector on Linux
                  • 3. Configure the OTel Collector
                    • 4. Troubleshooting common errors
                      • 5. General OpenTelemetry concepts
                        Topic 3: Alerting on Metrics with Detectors10%- Detectors and Alerting
                        • 1. Create detectors from charts
                          • 2. Clone and manage detectors
                            • 3. Standalone detectors
                              • 4. Muting rules
                                Topic 4: Metrics Concepts15%- Core Metrics Data Model
                                • 1. Splunk IM data model, metrics, MTS, datapoints
                                  • 2. Types of metadata
                                    • 3. Components of a datapoint
                                      • 4. Data resolution and rollups
                                        Topic 5: Detectors for Common Use Cases15%- Advanced Detector Scenarios
                                        • 1. Ephemeral infrastructure monitoring
                                          • 2. Troubleshoot detectors
                                            • 3. Non-flapping detectors
                                              • 4. Large-scale monitoring
                                                • 5. Cyclic pattern monitoring
                                                  • 6. Population monitoring
                                                    • 7. Detect common issues
                                                      Topic 6: Monitor Using Built-in Content10%- Observability Navigation & Monitoring
                                                      • 1. Cluster Analyzer troubleshooting
                                                        • 2. Kubernetes Navigator usage
                                                          • 3. Interact with built-in dashboards and content
                                                            • 4. Interpret charts using rollups and analytics functions
                                                              • 5. Use alerts and detectors
                                                                Topic 7: Introduction to Visualizing Metrics15%- Metrics Visualization
                                                                • 1. Visualization types
                                                                  • 2. Dashboard groups
                                                                    • 3. Search and visualize metrics
                                                                      • 4. Apply rollups and analytics functions
                                                                        • 5. Create charts and dashboards
                                                                          Topic 8: Finding Insights Using Analytics15%- Metrics Analytics
                                                                          • 1. Time-based comparisons
                                                                            • 2. Subset analysis of MTS signals
                                                                              • 3. Combining plots in charts
                                                                                • 4. Aggregation across sources
                                                                                  • 5. Moving and calendar window analytics
                                                                                    • 6. Ratios and percentage trends

                                                                                      >> SPLK-4001 Test Tutorials <<

                                                                                      2026 Splunk High-quality SPLK-4001: Splunk O11y Cloud Certified Metrics User Test Tutorials

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                                                                                      Splunk O11y Cloud Certified Metrics User Sample Questions (Q118-Q123):

                                                                                      NEW QUESTION # 118
                                                                                      With exceptions for transformations or timeshifts, at what resolution do detectors operate?

                                                                                      Answer: B

                                                                                      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 # 119
                                                                                      The Sum Aggregation option for analytic functions does which of the following?

                                                                                      Answer: C

                                                                                      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 # 120
                                                                                      What Pod conditions does the Analyzer panel in Kubernetes Navigator monitor? (select all that apply)

                                                                                      Answer: A,B,C,D

                                                                                      Explanation:
                                                                                      The Pod conditions that the Analyzer panel in Kubernetes Navigator monitors are:
                                                                                      Not Scheduled: This condition indicates that the Pod has not been assigned to a Node yet. This could be due to insufficient resources, node affinity, or other scheduling constraints1 Unknown: This condition indicates that the Pod status could not be obtained or is not known by the system. This could be due to communication errors, node failures, or other unexpected situations1 Failed: This condition indicates that the Pod has terminated in a failure state. This could be due to errors in the application code, container configuration, or external factors1 Pending: This condition indicates that the Pod has been accepted by the system, but one or more of its containers has not been created or started yet. This could be due to image pulling, volume mounting, or network issues1 Therefore, the correct answer is A, B, C, and D.
                                                                                      To learn more about how to use the Analyzer panel in Kubernetes Navigator, you can refer to this documentation2.
                                                                                      1: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#pod-phase 2: https://docs.splunk.com/observability/infrastructure/monitor/k8s-nav.html#Analyzer-panel


                                                                                      NEW QUESTION # 121
                                                                                      What Pod conditions does the Analyzer panel in Kubernetes Navigator monitor? (select all that apply)

                                                                                      Answer: A,B,C,D

                                                                                      Explanation:
                                                                                      Explanation
                                                                                      The Pod conditions that the Analyzer panel in Kubernetes Navigator monitors are:
                                                                                      Not Scheduled: This condition indicates that the Pod has not been assigned to a Node yet. This could be due to insufficient resources, node affinity, or other scheduling constraints1 Unknown: This condition indicates that the Pod status could not be obtained or is not known by the system. This could be due to communication errors, node failures, or other unexpected situations1 Failed: This condition indicates that the Pod has terminated in a failure state. This could be due to errors in the application code, container configuration, or external factors1 Pending: This condition indicates that the Pod has been accepted by the system, but one or more of its containers has not been created or started yet. This could be due to image pulling, volume mounting, or network issues1 Therefore, the correct answer is A, B, C, and D.
                                                                                      To learn more about how to use the Analyzer panel in Kubernetes Navigator, you can refer to this documentation2.
                                                                                      1: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#pod-phase 2:
                                                                                      https://docs.splunk.com/observability/infrastructure/monitor/k8s-nav.html#Analyzer-panel


                                                                                      NEW QUESTION # 122
                                                                                      Which of the following can be configured when subscribing to a built-in detector?

                                                                                      Answer: B

                                                                                      Explanation:
                                                                                      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.


                                                                                      NEW QUESTION # 123
                                                                                      ......

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