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Linux Foundation KCNA (Kubernetes and Cloud Native Associate) Exam is a certification program designed to validate the skills and knowledge of professionals who work with cloud-native technologies such as Kubernetes. The program is offered by the Linux Foundation, a non-profit organization that is dedicated to promoting the growth of Linux and open-source software.
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Once an individual has successfully completed the Linux Foundation KCNA Exam, they will be considered a certified Kubernetes and Cloud Native Associate, which can provide significant benefits for their career. Kubernetes and Cloud Native Associate certification is recognized globally and can help individuals demonstrate their expertise and credibility in the field of cloud-native technologies. Additionally, individuals who hold this certification are well-positioned to pursue other Kubernetes and cloud-native certifications offered by the Linux Foundation, which can further enhance their skills and expertise in this rapidly-evolving technology landscape.
Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q83-Q88):
NEW QUESTION # 83
You're building a new cloud-native application using gRPC for communication between microservices. You want to use Jaeger for distributed tracing to track the flow of requests through your microservices. What should you do to integrate Jaeger with your gRPC application?
- A. Configure a custom gRPC interceptor to intercept gRPC calls and emit tracing data to Jaeger.
- B. Use Jaeger's built-in support for gRPC tracing, which automatically intercepts gRPC calls and sends data to Jaeger.
- C. Use a dedicated tracing proxy that sits between your gRPC services and intercepts traffic to send tracing data to Jaeger.
- D. Configure Istio to automatically inject tracing into gRPC calls and send the data to Jaeger.
- E. Modify your gRPC client and server code to explicitly log trace information using Jaeger's logging libraries.
Answer: B,D
Explanation:
The correct answers are B and D . Jaeger provides built-in support for tracing gRPC applications, and Istio can also be used to automatically inject tracing into gRPC calls. B: Use Jaeger's built-in support for gRPC tracing, which automatically intercepts gRPC calls and sends data to Jaeger. Jaeger offers libraries and integration points for popular frameworks like gRPC. Using Jaeger's gRPC tracing capabilities, you can automatically instrument your gRPC applications and capture tracing data without needing to manually modify your code extensively. D: Configure Istio to automatically inject tracing into gRPC calls and send the data to Jaeger. Istio, a service mesh, offers automatic tracing capabilities for gRPC applications. By configuring Istio, you can enable tracing for gRPC calls and send tracing data to Jae er streamlinin the tracin rocess and reducin code modifications within our services. The other options are incorrect or less efficient: A: Configure a custom gRPC interceptor to intercept gRPC calls and emit tracing data to Jaeger. While you can create a custom interceptor, Jaeger's built-in support and Istio's automatic tracing mechanisms are more convenient and often preferred for gRPC tracing. C: Modify your gRPC client and server code to explicitly log trace information using Jaeger's logging libraries. Manual code modifications are less efficient compared to using Jaeger's built-in support or Istio's automatic tracing. E: Use a dedicated tracing proxy that sits between your gRPC services and intercepts traffic to send tracing data to Jaeger. While a tracing proxy could work, it adds an extra layer of complexity and potential performance overhead compared to built-in support or Istio's integration.
NEW QUESTION # 84
You are running a web application with a high demand for CPU resources. Which Kubernetes scheduling strategy could help you ensure pods are scheduled on nodes with the most available CPU capacity?
- A. Pod affinity
- B. Pod anti-affinity
- C. Taints and tolerations
- D. Node affinity
- E. Node anti-affinity
Answer: D
Explanation:
Node affinity allows you to define preferences for where pods should be scheduled based on node labels. You can use node affinity to prioritize scheduling on nodes with high CPU capacity. While the other options can influence scheduling, they are not directly focused on CPU availability.
NEW QUESTION # 85
Your application requires a highly available database service. You decide to deploy three instances of the database within Kubernetes. Which Kubernetes feature can you use to ensure that all three instances are properly configured and managed as a single unit?
- A. Services
- B. Deployments
- C. StatefulSets
- D. Pods
- E. DaemonSets
Answer: C
Explanation:
StatefulSets are designed for applications that require persistent storage and a stable identity for each pod. They guarantee that pods within the set retain their identities and access to the same persistent storage, making them ideal for highly available database deployments.
NEW QUESTION # 86
Explain the concept of "histogram" metrics in Prometheus and provide an example of when they would be beneficial for monitoring.
- A. Histogram metrics provide a detailed distribution of values for a specific metric, allowing for analysis of performance bottlenecks or outlier behavior.
- B. Histogram metrics are designed to track changes in metric values over time, providing a historical view of performance trends.
- C. Histogram metrics are used for storing and retrieving time series data in a compressed format, optimizing storage space.
- D. Histogram metrics are only applicable to monitoring Kubernetes clusters, not for general system monitoring.
- E. Histogram metrics are used to create custom dashboards with interactive elements for visualizing data.
Answer: A
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 # 87
You are troubleshooting a performance issue with an application running in a Kubernetes cluster. You have access to Prometheus and Jaeger, but the Jaeger Ul shows that a specific request took an unusually long time to process. Which metric in Prometheus can help you identify the specific component or service within the application that caused the delay?
- A. kube_pod_container_status_restart_count
- B. kube_deployment_status_replicas
- C. kube_pod_status_phase
- D. http_request_duration_seconds
- E. kube_pod_container_resource_requests_cpu_cores
Answer: D
Explanation:
The correct answer is E . The metric 'http_request_duration_seconds* is typically used to track the time taken for HTTP requests to be processed. In this case, by looking at the 'http_request_duration_seconds' metric for the specific request identified in Jaeger, you can see the duration of each stage of the request processing. This can pinpoint the specific component or service where the delay occurred. The other options are not relevant to identifying the specific component or service causing the delay: A : Shows CPU resource requests for a pod. B : Shows the pod's phase. C : Shows the number of replicas in a deployment. D : Shows the restart count for a pod's containers. These metrics do not provide information about the processing time of individual requests.
NEW QUESTION # 88
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