TRACK YOUR PROGRESS WITH LINUX FOUNDATION KCNA PRACTICE TEST

Track Your Progress with Linux Foundation KCNA Practice Test

Track Your Progress with Linux Foundation KCNA Practice Test

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>> Lab KCNA Questions <<

Free PDF Linux Foundation - KCNA - Authoritative Lab Kubernetes and Cloud Native Associate Questions

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Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q85-Q90):

NEW QUESTION # 85
Explain the concept of "histogram" metrics in Prometheus and provide an example of when they would be beneficial for monitoring.

  • A. Histogram metrics are designed to track changes in metric values over time, providing a historical view of performance trends.
  • B. Histogram metrics provide a detailed distribution of values for a specific metric, allowing for analysis of performance bottlenecks or outlier behavior.
  • C. Histogram metrics are used for storing and retrieving time series data in a compressed format, optimizing storage space.
  • D. Histogram metrics are used to create custom dashboards with interactive elements for visualizing data.
  • E. Histogram metrics are only applicable to monitoring Kubernetes clusters, not for general system monitoring.

Answer: B

Explanation:
Histogram metrics provide a distribution of values for a metric. This is beneficial for monitoring scenarios where you want to understand the spread of values, such as response times of a web service. You can use the histogram to see how many requests fall within different response time buckets, helping identify performance bottlenecks or outlier requests. Histogram metrics can help identify performance issues that might not be evident with a simple average or sum metric.


NEW QUESTION # 86
Your Kubernetes cluster is running a batch processing workload that only needs to run during specific time windows. How can you effectively manage the cost associated with this workload?

  • A. Use a CronJob to schedule the batch processing workload to run only during the required time window.
  • B. Manually scale the workload up and down during the required time window.
  • C. Utilize spot instances or preemptible nodes for the batch processing workload, leveraging their discounted pricing.
  • D. Create a separate namespace for the batch processing workload and apply resource quotas to limit its resource consumption.
  • E. Configure a horizontal pod autoscaler (HPA) to scale the workload up during the time window and down afterward.

Answer: A,C

Explanation:
For batch processing workloads with defined time windows, scheduling and leveraging cost- effective resources are key. CronJobs can be used to schedule the workload to run only during the required time window, eliminating unnecessary resource consumption. Utilizing spot instances or preemptible nodes provides discounted pricing for workloads that can tolerate interruptions, further reducing costs. While HPA can scale workloads, it's not the most efficient approach for time-bound batch processing. Creating a separate namespace and applying resource quotas can limit resource usage, but doesn't directly address the intermittent nature of the workload. Manually scaling up and down is inefficient and prone to errors.


NEW QUESTION # 87
You are running a large-scale, microservice-based application in Kubernetes, and you are using HorizontalPodAutoscalers (HPAs) for automatic scaling. Which of the following statements about resource utilization monitoring in this scenario is true?

  • A. It is essential to monitor resource utilization at both the Pod and namespace levels to get a comprehensive view of resource usage and optimize scaling
  • B. Resource utilization monitoring is not critical in Kubernetes as the system automatically manages resource allocation and scaling.
  • C. Monitoring resource utilization at the Pod level provides sufficient insights for overall application health and scaling decisions-
  • D. Monitoring resource utilization at the node level is sufficient for scaling individual microservices.
  • E. Monitoring resource utilization is only necessary during peak load periods, not during normal operations.

Answer: A

Explanation:
Monitoring resource utilization at both the Pod and namespace levels provides a comprehensive understanding of resource usage. Monitoring Pods allows you to identify resource-intensive services and fine-tune their scaling behavior. Monitoring namespaces helps you understand the overall resource consumption and optimize scaling across the entire application. This is crucial in large-scale microservice deployments where resources can be easily exhausted if not carefully monitored


NEW QUESTION # 88
You are monitoring a Kubernetes cluster using Prometheus. You notice a sudden spike in the number of requests to a specific pod, followed by a corresponding increase in pod CPU utilization. Which Prometheus query can you use to identify the specific endpoint being heavily accessed?

  • A. kube_http_server_requests_seconds_bucket{job="", method="GET", uri="/specific_endpoint"}
  • B. kube_pod_container_status_restart_count{pod=""}
  • C. kube_deployment_status_replicas{deployment=""}
  • D. kube_pod_container_resource_requests_cpu_cores{pod=""}
  • E. kube_pod_status_phase{pod=""}

Answer: A

Explanation:
The correct answer is E . The query 'kube_http_server_requests_seconds_bucket{job="", method="GET", uri="/specific_endpoint"}" targets HTTP requests made to a specific endpoint within a pod (identified by the •job', •method', and 'uri' labels). This query allows you to see the number of requests made to the '/specific_endpoint• and identify spikes in traffic to that endpoint. The other options are not relevant to identifying specific endpoints being heavily accessed. Option A shows CPU resource requests for a pod, option B shows the pod's phase, option C shows the number of replicas in a deployment, and option D shows the restart count for a pod's containers. These queries do not provide information about specific endpoints and traffic patterns.


NEW QUESTION # 89
You need to create a Kubernetes service that exposes a TCP-based application on port 8080. You want the service to be accessible from external clients. Which type of service should you create?

  • A. LoadBalancer
  • B. ClusteriP
  • C. ExternalName
  • D. NodePort
  • E. Headless

Answer: A

Explanation:
The *LoadBalancer• service type is the most suitable for exposing your TCP-based application on port 8080 to external clients. It will automatically create a load balancer in the cloud provider's infrastructure, allowing external access to your application. Option 'A' (ClusterlP) only allows access from within the cluster. Option 'C' (NodePort) exposes the service on a specific port on each node, making it accessible via the node's IP address. Option 'D' (ExternalName) is for exposing services that are already externally accessible using a DNS name. Option 'E' (Headless) is for services where you want to access Pods directly by their names, which is not the case here.


NEW QUESTION # 90
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