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| Section | Weight | Objectives |
|---|
| Topic 1: Monitor Using Built-in Content | 10% | - Observability Navigation & Monitoring
- 1. Kubernetes Navigator usage
- 2. Interpret charts using rollups and analytics functions
- 3. Cluster Analyzer troubleshooting
- 4. Interact with built-in dashboards and content
- 5. Use alerts and detectors
|
| Topic 2: Alerting on Metrics with Detectors | 10% | - Detectors and Alerting
- 1. Clone and manage detectors
- 2. Standalone detectors
- 3. Create detectors from charts
- 4. Muting rules
|
| Topic 3: Detectors for Common Use Cases | 15% | - Advanced Detector Scenarios
- 1. Population monitoring
- 2. Large-scale monitoring
- 3. Troubleshoot detectors
- 4. Detect common issues
- 5. Non-flapping detectors
- 6. Cyclic pattern monitoring
- 7. Ephemeral infrastructure monitoring
|
| Topic 4: Create Efficient Dashboards and Alerts | 10% | - Dashboard Optimization
- 1. Data links configuration
- 2. Dashboard instructions
- 3. Event overlays
- 4. Alert customization
- 5. Single-instance dashboards
- 6. Troubleshooting charts and alerts
|
| Topic 5: Metrics Concepts | 15% | - Core Metrics Data Model
- 1. Types of metadata
- 2. Data resolution and rollups
- 3. Splunk IM data model, metrics, MTS, datapoints
- 4. Components of a datapoint
|
| Topic 6: Introduction to Visualizing Metrics | 15% | - Metrics Visualization
- 1. Search and visualize metrics
- 2. Dashboard groups
- 3. Visualization types
- 4. Apply rollups and analytics functions
- 5. Create charts and dashboards
|
| Topic 7: Get Metrics In with OpenTelemetry | 10% | - OpenTelemetry Collector Deployment
- 1. Edit configuration files
- 2. Configure the OTel Collector
- 3. Deploy the OTel Collector on Linux
- 4. Troubleshooting common errors
- 5. General OpenTelemetry concepts
|
| Topic 8: Finding Insights Using Analytics | 15% | - Metrics Analytics
- 1. Moving and calendar window analytics
- 2. Time-based comparisons
- 3. Subset analysis of MTS signals
- 4. Combining plots in charts
- 5. Ratios and percentage trends
- 6. Aggregation across sources
|
>> Valid SPLK-4001 Test Topics <<
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Splunk O11y Cloud Certified Metrics User Sample Questions (Q118-Q123):
NEW QUESTION # 118
Which of the following rollups will display the time delta between a datapoint being sent and a datapoint being received?
- A. Jitter
- B. Lag
- C. Latency
- D. Delay
Answer: B
Explanation:
According to the Splunk Observability Cloud documentation1, lag is a rollup function that returns the difference between the most recent and the previous data point values seen in the metric time series reporting interval. This can be used to measure the time delta between a data point being sent and a data point being received, as long as the data points have timestamps that reflect their send and receive times. For example, if a data point is sent at 10:00:00 and received at 10:00:05, the lag value for that data point is 5 seconds.
NEW QUESTION # 119
How can you effectively monitor metrics with cyclic patterns using detectors?
- A. Use historical data to predict cyclic patterns
- B. Apply a moving average to smooth out cyclic fluctuations
- C. Trigger alerts based on the highest and lowest points of the cycles
- D. Configure multiple detectors with different extrapolation policies
Answer: B
NEW QUESTION # 120
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. Chart Options and metadata
- B. Timeshift and Bottom N
- C. Percentages and ratios
- D. Timeshift and Top N
Answer: C
Explanation:
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 # 121
Which of the following is optional, but highly recommended to include in a datapoint?
- A. Timestamp
- B. Value
- C. Metric type
- D. Metric name
Answer: C
Explanation:
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 correctly.
NEW QUESTION # 122
Which of the following can be configured when subscribing to a built-in detector?
- A. Outbound notifications.
- B. Alerts on a dashboard.
- C. Alerts on team landing page.
- D. Links to a chart.
Answer: A
Explanation:
According to the web search results, 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 OpenTelemetry. 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 settings.
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.
NEW QUESTION # 123
......
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