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Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q224-Q229):
NEW QUESTION # 224
How to get the logs of the previously terminated nginx container from the web pod?
- A. kubectl logs -f -c nginx web
- B. kubectl logs nginx
- C. kubectl logs -p -c web nginx
- D. kubectl logs -p -c nginx web
Answer: D
Explanation:
https://kubernetes.io/docs/reference/generated/kubectl/kubectl-commands#logs

NEW QUESTION # 225
A Pod named my-app must be created to run a simple nginx container. Which kubectl command should be used?
- A. kubectl run my-app --image=nginx
- B. kubectl create nginx --name=my-app
- C. kubectl run nginx --name=my-app
- D. kubectl create my-app --image=nginx
Answer: A
Explanation:
In Kubernetes, the simplest and most direct way to create a Pod that runs a single container is to use the kubectl run command with the appropriate image specification. The command kubectl run my-app -- image=nginx explicitly instructs Kubernetes to create a Pod named my-app using the nginx container image, which makes option B the correct answer.
The kubectl run command is designed to quickly create and run a Pod (or, in some contexts, a higher-level workload resource) from the command line. When no additional flags such as --restart=Always are specified, Kubernetes creates a standalone Pod by default. This is ideal for simple use cases like testing, demonstrations, or learning scenarios where only a single container is required.
Option A is incorrect because kubectl create nginx --name=my-app is not valid syntax; the create subcommand requires a resource type (such as pod, deployment, or service) or a manifest file. Option C is also incorrect because kubectl create my-app --image=nginx omits the resource type and therefore is not a valid kubectl create command. Option D is incorrect because kubectl run nginx --name=my-app attempts to use the deprecated --name flag, which is no longer supported in modern versions of kubectl.
Using kubectl run with explicit naming and image flags is consistent with Kubernetes command-line conventions and is widely documented as the correct approach for creating simple Pods. The resulting Pod can be verified using commands such as kubectl get pods and kubectl describe pod my-app.
In summary, Option B is the correct and verified answer because it uses valid kubectl syntax to create a Pod named my-app running the nginx container image in a straightforward and predictable way.
NEW QUESTION # 226
What is the common standard for Service Meshes?
- A. Service Mesh Interface (SMI)
- B. Service Mesh Technology (SMT)
- C. Service Mesh Function (SMF)
- D. Service Mesh Specification (SMS)
Answer: A
Explanation:
A widely referenced interoperability standard in the service mesh ecosystem is the Service Mesh Interface (SMI), so C is correct. SMI was created to provide a common set of APIs for basic service mesh capabilities-helping users avoid being locked into a single mesh implementation for core features. While service meshes differ in architecture and implementation (e.g., Istio, Linkerd, Consul), SMI aims to standardize how common behaviors are expressed.
In cloud native architecture, service meshes address cross-cutting concerns for service-to-service communication: traffic policies, observability, and security (mTLS, identity). Rather than baking these concerns into every application, a mesh typically introduces data-plane proxies and a control plane to manage policy and configuration. SMI sits above those implementations as a common API model.
The other options are not commonly used industry standards. You may see other efforts and emerging APIs, but among the listed choices, SMI is the recognized standard name that appears in cloud native discussions and tooling integrations.
Also note a practical nuance: even with SMI, not every mesh implements every SMI spec fully, and many users still adopt mesh-specific CRDs and APIs for advanced features. But for this question's framing-
"common standard"-Service Mesh Interface is the correct answer.
NEW QUESTION # 227
In Prometheus, what is the purpose of recording rules and how do they differ from alerting rules?
- A. Recording rules create new time series based on existing metrics, while alerting rules trigger notifications based on metric conditions.
- B. Recording rules define data aggregation and analysis, while alerting rules focus on time-series data visualization.
- C. Recording rules are primarily used for troubleshooting, while alerting rules are used for proactive issue detection.
- D. Recording rules and alerting rules are interchangeable and can be used for similar purposes.
- E. Recording rules are used for data storage optimization, while alerting rules are used for system performance monitoring.
Answer: A
Explanation:
Recording rules transform existing time series data into new, calculated metrics. Alerting rules, on the other hand, trigger notifications when certain metric conditions are met. Recording rules are used for data pre-processing, while alerting rules focus on proactive monitoring.
NEW QUESTION # 228
What are default kubernetes namespaces?
- A. default, kube-public, kube-systems, kube-node-lease
- B. default, kube-public, kube-system, kube-node-lease
- C. kube-default, kube-public, kube-system, kube-node-lease
- D. default, kube-public, kube-system, kube-node-leases
Answer: B
Explanation:
https://kubernetes.io/docs/concepts/overview/working-with-objects/namespaces/

NEW QUESTION # 229
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