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| Section | Weight | Objectives |
|---|---|---|
| Intro to Alerting on Metrics using Detectors | 10% | - Make a solo detector - Make the detector from a chart - Clone an existing detector - Make a muting rule |
| Metrics Concepts | 15% | - Discriminate between types of metadata - Data resolution, rollups - List the components of a datapoint - Define components of the Splunk IM Data Model, Metrics, MTS, datapoints |
| Monitor Using Built-in Content | 10% | - Use the Kubernetes Navigator to investigate problems with nodes, pods, and containers - Subscribe to alerts - Use the Cluster Analyzer to pinpoint the root of some problems - Correctly interpret data in charts based on rollups, analytic functions, and chart resolution - Interact with data using built-in content |
| Get Metrics In with OpenTelemetry | 10% | - Edit the configuration - General OpenTelemetry Concepts - Configure the OTel Collector - Troubleshooting common errors - Deploy the OTel Collector on Linux |
| Create Efficient Dashboards and Alerts | 10% | - Create single-instance dashboard panels - View dashboard happenings - Configure personal information linkages - Include instructions on interfaces |
| Introduction to Metric Visualization | 15% | - Visualize a measure in a chart - Create widgets and showcase groups - Differentiate between several chart visualization types - Create charts and dashboards - Look for metrics - Use rollups and analytical tools correctly - Analyze data in charts |
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TestSimulate offers the complete package that includes all exam questions conforming to the syllabus for passing the Splunk O11y Cloud Certified Metrics User (SPLK-4001) exam certificate in the first try. These formats of actual Splunk SPLK-4001 Questions are specifically designed to make preparation easier for you.
NEW QUESTION # 31
What are all the possible components of a datapoint in Splunk Observability Cloud?
Answer: B
Explanation:
A datapoint in Splunk Observability Cloud includes the metric type, metric name, dimensions, metric value, and timestamp. These components identify what is being measured, provide contextual metadata, record the measured value, and associate it with a specific time.
NEW QUESTION # 32
Which mode is needed when the OpenTelemetry Collector is deployed on the same host as the application being monitored?
Answer: B
Explanation:
When the OpenTelemetry Collector runs on the same host as the application, it operates in agent mode. In this mode, it directly receives telemetry data from the application and forwards it to a centralized backend or gateway for further processing.
NEW QUESTION # 33
What constitutes a single metrics time series (MTS)?
Answer: C
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 # 34
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?
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 # 35
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?
Answer: D
Explanation:
According to the Splunk O11y Cloud Certified Metrics User Track document, 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.
NEW QUESTION # 36
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