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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Detectors for Common Use Cases | 15% | - Advanced Detector Scenarios
|
| Topic 2: Introduction to Visualizing Metrics | 15% | - Metrics Visualization
|
| Topic 3: Metrics Concepts | 15% | - Core Metrics Data Model
|
| Topic 4: Finding Insights Using Analytics | 15% | - Metrics Analytics
|
| Topic 5: Monitor Using Built-in Content | 10% | - Observability Navigation & Monitoring
|
| Topic 6: Alerting on Metrics with Detectors | 10% | - Detectors and Alerting
|
| Topic 7: Create Efficient Dashboards and Alerts | 10% | - Dashboard Optimization
|
| Topic 8: Get Metrics In with OpenTelemetry | 10% | - OpenTelemetry Collector Deployment
|
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NEW QUESTION # 49
Which of the following are accurate reasons to clone a detector? (select all that apply)
Answer: A,C
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 # 50
What happens when the limit of allowed dimensions is exceeded for an MTS?
Answer: A
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 # 51
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?
Answer: B
Explanation:
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 latency, 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%. 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.
NEW QUESTION # 52
When writing a detector with a large number of MTS, such as memory. free in a deployment with
30,000 hosts, it is possible to exceed the cap of MTS that can be contained in a single plot.
Which of the choices below would most likely reduce the number of MTS below the plot cap?
Answer: B
Explanation:
Add a filter to narrow the scope of the measurement. A filter is a way to reduce the number of metric time series (MTS) that are displayed on a chart or used in a detector. A filter specifies one or more dimensions and values that the MTS must have in order to be included. For example, if you want to monitor the memory.free metric only for hosts that belong to a certain cluster, you can add a filter like cluster:my-cluster to the plot or detector. This will exclude any MTS that do not have the cluster dimension or have a different value for it. Adding a filter can help you avoid exceeding the plot cap, which is the maximum number of MTS that can be contained in a single plot. The plot cap is 100,000 by default, but it can be changed by contacting Splunk Support.
NEW QUESTION # 53
When applying analytic functions to a subset of multiple time series (MTS) in a signal, what is the resulting data structure?
Answer: B
NEW QUESTION # 54
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