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| Certification Vendor: | Linux Foundation |
|---|---|
| Exam Name: | Kubernetes and Cloud Native Associate |
| Exam Number: | KCNA |
| Exam Format: | Multiple Choice |
| Passing Score: | 75% (approximately 45 out of 60) |
| Real Exam Qty: | 60 |
| Related Certifications: | CKS (Certified Kubernetes Security Specialist) CKAD (Certified Kubernetes Application Developer) CKA (Certified Kubernetes Administrator) |
| Exam Duration: | 90 minutes |
| Available Languages: | Japanese, English |
| Exam Price: | $250 USD |
| Certificate Validity Period: | 3 years |
| Sample Questions: | Linux Foundation KCNA Sample Questions |
| Exam Way: | Online, proctored exam |
| Pre Condition: | None. No prerequisites required. |
| Official Syllabus URL: | https://training.linuxfoundation.org/certification/kubernetes-cloud-native-associate |
This is much alike our KCNA exam with the only difference of providing services to our desktop users. It is compatible with Windows computers. Candidates find it easy to do self-assessment and they get maximum benefit by practicing Kubernetes and Cloud Native Associate (KCNA) test available only here. The Kubernetes and Cloud Native Associate (KCNA) questions provided here are compiled by over 90,000 competent professionals who handpicked all of these questions for your evaluation and concept-building.
The KCNA Exam is a valuable credential for professionals who work with Kubernetes and other cloud-native technologies. It demonstrates to employers that the candidate has a deep understanding of these technologies and can apply them effectively in real-world situations. Additionally, the certification is recognized globally and can help professionals stand out in a competitive job market.
NEW QUESTION # 285
Which is an industry-standard container runtime with an "emphasis" on simplicity, robustness, and portability?
Answer: B
Explanation:
containerd is a widely adopted, industry-standard container runtime known for simplicity, robustness, and portability, so C is correct. containerd originated as a core component extracted from Docker and has become a common runtime across Kubernetes distributions and managed services. It implements container lifecycle management (image pull, unpack, container execution, snapshotting) and typically delegates low-level container execution to an OCI runtime like runc.
In Kubernetes, kubelet communicates with container runtimes through CRI. containerd provides a CRI plugin (or can be integrated via CRI implementations) that makes it a first-class choice for Kubernetes nodes. This aligns with the runtime landscape after dockershim removal: Kubernetes users commonly run containerd or CRI-O as the node runtime.
Option A (CRI-O) is also a CRI-focused runtime and is valid in Kubernetes contexts, but the phrasing
"industry-standard ... emphasis on simplicity, robustness, and portability" is strongly associated with containerd's positioning and broad cross-platform adoption beyond Kubernetes. Option B (LXD) is a system container manager (often associated with LXC) and not the standard Kubernetes runtime in mainstream CRI discussions. Option D (kata-runtime) is associated with Kata Containers, which focuses on stronger isolation by running containers inside lightweight VMs; that is a security-oriented sandbox approach rather than a simplicity/portability "industry standard" baseline runtime.
From a cloud-native operations point of view, containerd's popularity comes from its stable API, strong ecosystem support, and alignment with OCI standards. It integrates cleanly with image registries, supports modern snapshotters, and is heavily used in production by many Kubernetes providers. Therefore, the best verified answer is C: containerd.
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NEW QUESTION # 286
A Kubernetes node is on hardware that is scheduled for maintenance. How can the Pods scheduled on that node be identified so workloads can be redirected before the node is taken out of service?
Answer: A
Explanation:
The kubectl get pods -o wide --all-namespaces command displays all Pods along with the nodes they are running on, allowing identification of Pods scheduled on the specific node before maintenance.
NEW QUESTION # 287
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?
Answer: D
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 # 288
In a Kubernetes environment, how is an Argo CD ApplicationSet configured to ensure continuous deployment of an application?
Answer: B
Explanation:
An Argo CD ApplicationSet is defined declaratively and connected to a Git repository that contains the application manifests. Argo CD continuously monitors the repository and automatically syncs the cluster state with the desired state defined in Git, enabling continuous deployment.
NEW QUESTION # 289
Which of the following is a challenge derived from running cloud native applications?
Answer: C
Explanation:
The correct answer is B. Cloud-native applications often run across multiple environments-different cloud providers, regions, accounts/projects, and sometimes hybrid deployments. This introduces real cost- management complexity: pricing models differ (compute types, storage tiers, network egress), discount mechanisms vary (reserved capacity, savings plans), and telemetry/charge attribution can be inconsistent.
When you add Kubernetes, the abstraction layer can further obscure cost drivers because costs are incurred at the infrastructure level (nodes, disks, load balancers) while consumption happens at the workload level (namespaces, Pods, services).
Option A is less relevant because cloud-native adoption often reduces dependence on maintaining a private datacenter; many organizations adopt cloud-native specifically to avoid datacenter CapEx/ops overhead.
Option C is generally untrue-public registries and vendor registries contain vast numbers of images; the challenge is more about provenance, security, and supply chain than "lack of images." Option D is incorrect because major clouds offer abundant services; the difficulty is choosing among them and controlling cost
/complexity, not a lack of services.
Cost optimization being complex is a recognized challenge because cloud-native architectures include microservices sprawl, autoscaling, ephemeral environments, and pay-per-use dependencies (managed databases, message queues, observability). Small misconfigurations can cause big bills: noisy logs, over- requested resources, unbounded HPA scaling, and egress-heavy architectures. That's why practices like FinOps, tagging/labeling for allocation, and automated guardrails are emphasized.
So the best answer describing a real, common cloud-native challenge is B.
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NEW QUESTION # 290
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