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Linux Foundation KCNA Exam Syllabus Topics:

SectionWeightObjectives
Kubernetes Fundamentals46%- Scheduling
  • 1. Taints and Tolerations
  • 2. Node Selection and Affinity
  • 3. Resource Requests and Limits
- Containers
  • 1. Basic kubectl Commands
  • 2. Container Images and Registries
  • 3. Container Runtime Interface (CRI)
- Kubernetes Architecture
  • 1. Control Plane Components (API Server, etcd, Scheduler, Controller Manager)
  • 2. Worker Node Components (Kubelet, Kube-proxy, Container Runtime)
- Kubernetes Resources
  • 1. Workload Resources (Pods, Deployments, StatefulSets, DaemonSets, ReplicaSets, Jobs, CronJobs)
  • 2. Networking Resources (Services, Ingress)
  • 3. Configuration Resources (ConfigMaps, Secrets)
- Kubernetes API
  • 1. Declarative Management (Manifests/YAML)
  • 2. API Resource Structure and Versioning
Cloud Native Architecture16%- Infrastructure and Practices
  • 1. DevOps Practices and Culture
  • 2. Immutable Infrastructure
  • 3. Infrastructure as Code (IaC)
- Cloud Native Landscape
  • 1. CNCF Role and Governance
  • 2. CNCF Project Categories (Sandbox, Incubating, Graduated)
- Architecture Concepts
  • 1. Serverless and FaaS
  • 2. Autoscaling (HPA, VPA, Cluster Autoscaler)
  • 3. Elasticity and Resilience
  • 4. Microservices Architecture
Cloud Native Application Delivery8%- CI/CD
  • 1. Continuous Integration and Continuous Delivery Pipelines
  • 2. Artifact Management and Image Registries
- Deployment Strategies
  • 1. Blue/Green, Canary, Rolling Updates
- GitOps
  • 1. Tools (Argo CD, Flux)
  • 2. GitOps Principles and Workflow
Container Orchestration22%- Networking
  • 1. CoreDNS and Service Networking
  • 2. Kubernetes Networking Model
- Storage
  • 1. Storage Classes and Dynamic Provisioning
  • 2. Volumes, PersistentVolumes (PV), PersistentVolumeClaims (PVC)
- Container Runtimes
  • 1. Docker, containerd, CRI-O
- Orchestration Fundamentals
  • 1. Service Discovery and Load Balancing
  • 2. Scheduling and Resource Management
  • 3. Self-healing and Rolling Updates
- Service Mesh
  • 1. Sidecar Pattern and Traffic Management
  • 2. Service Mesh Concepts (Istio, Linkerd)
- Security
  • 1. Network Policies
  • 2. Pod Security Standards (Admission Control)
  • 3. RBAC (Role-Based Access Control)
Cloud Native Observability8%- Tracing
  • 1. Distributed Tracing Concepts (OpenTelemetry, Jaeger)
- Logging
  • 1. Kubernetes Logging Architecture
  • 2. Centralized Logging (Fluentd, Elasticsearch, Kibana)
- Monitoring and Metrics
  • 1. Dashboards and Visualization (Grafana)
  • 2. Prometheus and Metrics Collection

>> KCNA Latest Test Report <<

Linux Foundation - KCNA - The Best Kubernetes and Cloud Native Associate Latest Test Report

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Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q105-Q110):

NEW QUESTION # 105
Which component of the Kubernetes architecture is responsible for integration with the CRI container runtime?

Answer: B

Explanation:
The correct answer is B: kubelet. The Container Runtime Interface (CRI) defines how Kubernetes interacts with container runtimes in a consistent, pluggable way. The component that speaks CRI is the kubelet, the node agent responsible for running Pods on each node. When the kube-scheduler assigns a Pod to a node, the kubelet reads the PodSpec and makes the runtime calls needed to realize that desired state-pull images, create a Pod sandbox, start containers, stop containers, and retrieve status and logs. Those calls are made via CRI to a CRI-compliant runtime such as containerd or CRI-O.
Why not the others:
kubeadm bootstraps clusters (init/join/upgrade workflows) but does not run containers or speak CRI for workload execution.
kube-apiserver is the control plane API frontend; it stores and serves cluster state and does not directly integrate with runtimes.
kubectl is just a client tool that sends API requests; it is not involved in runtime integration on nodes.
This distinction matters operationally. If the runtime is misconfigured or CRI endpoints are unreachable, kubelet will report errors and Pods can get stuck in ContainerCreating, image pull failures, or runtime errors. Debugging often involves checking kubelet logs and runtime service health, because kubelet is the integration point bridging Kubernetes scheduling/state with actual container execution.
So, the node-level component responsible for CRI integration is the kubelet-option B.


NEW QUESTION # 106
Which of the following will view the snapshot of previously terminated ruby container logs from Pod web-1?

Answer: D


NEW QUESTION # 107
Which of the following is not the Kubernetes AutoScaling Strategy?

Answer: B

Explanation:
https://learnk8s.io/kubernetes-autoscaling-strategies


NEW QUESTION # 108
Which of the following cloud native proxies is used for ingress/egress in a service mesh and can also serve as an application gateway?

Answer: B

Explanation:
Envoy proxy is a cloud native, high-performance proxy commonly used as the data plane in service meshes for handling ingress and egress traffic, and it can also function as an application gateway by providing features such as routing, load balancing, observability, and security.


NEW QUESTION # 109
What is a Service?

Answer: A

Explanation:
The correct answer is B: a Kubernetes Service is a stable way to expose an application running on a set of Pods. Pods are ephemeral-IPs can change when Pods are recreated, rescheduled, or scaled. A Service provides a consistent network identity (DNS name and usually a ClusterIP virtual IP) and a policy for routing traffic to the current healthy backends.
Typically, a Service uses a label selector to determine which Pods are part of the backend set. Kubernetes then maintains the corresponding endpoint data (Endpoints/EndpointSlice), and the cluster dataplane (kube- proxy or an eBPF-based implementation) forwards traffic from the Service IP/port to one of the Pod IPs. This enables reliable service discovery and load distribution across replicas, especially during rolling updates where Pods are constantly replaced.
Option A is incorrect because Service routing is not a "static mapping from a Pod to a port." It's dynamic and targets a set of Pods. Option C is too vague and misstates the concept; while Services relate to networking, they are not "the network configuration for a group of Pods" (that's closer to NetworkPolicy/CNI configuration). Option D is incorrect because Kubernetes does not automatically deploy an NGINX load balancer when you create a Service. NGINX might be used as an Ingress controller or external load balancer in some setups, but a Service is a Kubernetes API abstraction, not a specific NGINX component.
Services come in several types (ClusterIP, NodePort, LoadBalancer, ExternalName), but the core definition remains the same: stable access to a dynamic set of Pods. This is foundational for microservices and for decoupling clients from the churn of Pod lifecycles.
So, the verified correct definition is B.
=========


NEW QUESTION # 110
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