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| Section | Weight | Objectives |
|---|---|---|
| Introduction to Visualizing Metrics | 15% | - Metrics Visualization
|
| Create Efficient Dashboards and Alerts | 10% | - Dashboard Optimization
|
| Metrics Concepts | 15% | - Core Metrics Data Model
|
| Get Metrics In with OpenTelemetry | 10% | - OpenTelemetry Collector Deployment
|
| Finding Insights Using Analytics | 15% | - Metrics Analytics
|
| Alerting on Metrics with Detectors | 10% | - Detectors and Alerting
|
| Monitor Using Built-in Content | 10% | - Observability Navigation & Monitoring
|
| Detectors for Common Use Cases | 15% | - Advanced Detector Scenarios
|
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NEW QUESTION # 125
The built-in Kubernetes Navigator includes which of the following?
Answer: C
Explanation:
Explanation
The correct answer is D. Map, Nodes, Workloads, Node Detail, Workload Detail, Pod Detail, Container Detail.
The built-in Kubernetes Navigator is a feature of Splunk Observability Cloud that provides a comprehensive and intuitive way to monitor the performance and health of Kubernetes environments. It includes the following views:
Map: A graphical representation of the Kubernetes cluster topology, showing the relationships and dependencies among nodes, pods, containers, and services. You can use the map to quickly identify and troubleshoot issues in your cluster1 Nodes: A tabular view of all the nodes in your cluster, showing key metrics such as CPU utilization, memory usage, disk usage, and network traffic. You can use the nodes view to compare and analyze the performance of different nodes1 Workloads: A tabular view of all the workloads in your cluster, showing key metrics such as CPU utilization, memory usage, network traffic, and error rate. You can use the workloads view to compare and analyze the performance of different workloads, such as deployments, stateful sets, daemon sets, or jobs1 Node Detail: A detailed view of a specific node in your cluster, showing key metrics and charts for CPU utilization, memory usage, disk usage, network traffic, and pod count. You can also see the list of pods running on the node and their status. You can use the node detail view to drill down into the performance of a single node2 Workload Detail: A detailed view of a specific workload in your cluster, showing key metrics and charts for CPU utilization, memory usage, network traffic, error rate, and pod count. You can also see the list of pods belonging to the workload and their status. You can use the workload detail view to drill down into the performance of a single workload2 Pod Detail: A detailed view of a specific pod in your cluster, showing key metrics and charts for CPU utilization, memory usage, network traffic, error rate, and container count. You can also see the list of containers within the pod and their status. You can use the pod detail view to drill down into the performance of a single pod2 Container Detail: A detailed view of a specific container in your cluster, showing key metrics and charts for CPU utilization, memory usage, network traffic, error rate, and log events. You can use the container detail view to drill down into the performance of a single container2 To learn more about how to use Kubernetes Navigator in Splunk Observability Cloud, you can refer to this documentation3.
1: https://docs.splunk.com/observability/infrastructure/monitor/k8s-nav.html#Kubernetes-Navigator 2:
https://docs.splunk.com/observability/infrastructure/monitor/k8s-nav.html#Detail-pages 3:
https://docs.splunk.com/observability/infrastructure/monitor/k8s-nav.html
NEW QUESTION # 126
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: C
Explanation:
The correct answer is B. 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 it1 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 Support2 To learn more about how to use filters in Splunk Observability Cloud, you can refer to this documentation3.
1: https://docs.splunk.com/Observability/gdi/metrics/search.html#Filter-metrics 2: https://docs.splunk.com/Observability/gdi/metrics/detectors.html#Plot-cap 3: https://docs.splunk.com/Observability/gdi/metrics/search.html
NEW QUESTION # 127
Which of the following is a valid use case for Service Level Objectives (SLOs) in Splunk Observability Cloud?
Answer: A
Explanation:
SLOs are used to define, measure, and track whether a service is meeting agreed-upon reliability or performance targets over a rolling time window, and can trigger alerts when error budgets are at risk.
NEW QUESTION # 128
In monitoring systems, which feature allows you to troubleshoot and identify issues with charts and alerts effectively?
Answer: B
NEW QUESTION # 129
A customer wants to find the total number of transmission errors that occurred over a discrete period of time. Assuming that the metric type is Cumulative Counter, which of the following combinations of rollup and analytic function could be used to accomplish this?
Answer: B
Explanation:
For a cumulative counter, the Delta rollup calculates the change in the counter value over each interval. Applying the Sum Transformation analytic function then adds those deltas together to get the total number of transmission errors over the selected time period.
NEW QUESTION # 130
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