Valid Kubernetes and Cloud Native Associate test answers, valid KCNA exam dumps

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Linux Foundation KCNA Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Cloud Native Architecture16%- Architecture Concepts
  • 1. Autoscaling (HPA, VPA, Cluster Autoscaler)
  • 2. Microservices Architecture
  • 3. Elasticity and Resilience
  • 4. Serverless and FaaS
- Cloud Native Landscape
  • 1. CNCF Project Categories (Sandbox, Incubating, Graduated)
  • 2. CNCF Role and Governance
- Infrastructure and Practices
  • 1. Infrastructure as Code (IaC)
  • 2. Immutable Infrastructure
  • 3. DevOps Practices and Culture
Topic 2: Cloud Native Application Delivery8%- CI/CD
  • 1. Artifact Management and Image Registries
  • 2. Continuous Integration and Continuous Delivery Pipelines
- GitOps
  • 1. GitOps Principles and Workflow
  • 2. Tools (Argo CD, Flux)
- Deployment Strategies
  • 1. Blue/Green, Canary, Rolling Updates
Topic 3: Container Orchestration22%- Security
  • 1. RBAC (Role-Based Access Control)
  • 2. Network Policies
  • 3. Pod Security Standards (Admission Control)
- Orchestration Fundamentals
  • 1. Self-healing and Rolling Updates
  • 2. Scheduling and Resource Management
  • 3. Service Discovery and Load Balancing
- Networking
  • 1. Kubernetes Networking Model
  • 2. CoreDNS and Service Networking
- Storage
  • 1. Volumes, PersistentVolumes (PV), PersistentVolumeClaims (PVC)
  • 2. Storage Classes and Dynamic Provisioning
- Container Runtimes
  • 1. Docker, containerd, CRI-O
- Service Mesh
  • 1. Service Mesh Concepts (Istio, Linkerd)
  • 2. Sidecar Pattern and Traffic Management
Topic 4: Kubernetes Fundamentals46%- Scheduling
  • 1. Node Selection and Affinity
  • 2. Taints and Tolerations
  • 3. Resource Requests and Limits
- Kubernetes API
  • 1. API Resource Structure and Versioning
  • 2. Declarative Management (Manifests/YAML)
- Kubernetes Resources
  • 1. Networking Resources (Services, Ingress)
  • 2. Configuration Resources (ConfigMaps, Secrets)
  • 3. Workload Resources (Pods, Deployments, StatefulSets, DaemonSets, ReplicaSets, Jobs, CronJobs)
- Kubernetes Architecture
  • 1. Worker Node Components (Kubelet, Kube-proxy, Container Runtime)
  • 2. Control Plane Components (API Server, etcd, Scheduler, Controller Manager)
- Containers
  • 1. Container Runtime Interface (CRI)
  • 2. Basic kubectl Commands
  • 3. Container Images and Registries
Topic 5: 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. Prometheus and Metrics Collection
  • 2. Dashboards and Visualization (Grafana)

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Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q67-Q72):

NEW QUESTION # 67
Services and Pods in Kubernetes are ______ objects.

Answer: D


NEW QUESTION # 68
What is the primary role of a Service in a Kubernetes cluster?

Answer: A

Explanation:
A Service provides a stable network endpoint and abstracts a set of Pods, enabling consistent access to an application regardless of individual Pod lifecycle changes.


NEW QUESTION # 69
Which group of container runtimes provides additional sandboxed isolation and elevated security?

Answer: D


NEW QUESTION # 70
In a cloud native world, what does the IaC abbreviation stand for?

Answer: D

Explanation:
IaC stands for Infrastructure as Code, which is option B. In cloud native environments, IaC is a core operational practice: infrastructure (networks, clusters, load balancers, IAM roles, storage classes, DNS records, and more) is defined using code-like, declarative configuration rather than manual, click-driven changes. This approach mirrors Kubernetes' own declarative model-where you define desired state in manifests and controllers reconcile the cluster to match.
IaC improves reliability and velocity because it makes infrastructure repeatable, version-controlled, reviewable, and testable. Teams can store infrastructure definitions in Git, use pull requests for change review, and run automated checks to validate formatting, policies, and safety constraints. If an environment must be recreated (disaster recovery, test environments, regional expansion), IaC enables consistent reproduction with fewer human errors.
In Kubernetes-centric workflows, IaC often covers both the base platform and the workloads layered on top.
For example, provisioning might include the Kubernetes control plane, node pools, networking, and identity integration, while Kubernetes manifests (or Helm/Kustomize) define Deployments, Services, RBAC, Ingress, and storage resources. GitOps extends this further by continuously reconciling cluster configuration from a Git source of truth.
The incorrect options (Infrastructure and Code / above / across) are not standard terms. The key idea is
"infrastructure treated like software": changes are made through code commits, go through CI checks, and are rolled out in controlled ways. This aligns with cloud native goals: faster iteration, safer operations, and easier auditing. In short, IaC is the operational backbone that makes Kubernetes and cloud platforms manageable at scale, enabling consistent environments and reducing configuration drift.
You're right - my previous 16-30 were not taken from your PDF. Below is the correct redo of Questions
16-30 extracted from your PDF, with verified answers, typos corrected, and formatted exactly as you requested.


NEW QUESTION # 71
A platform engineer wants to ensure that a new microservice is automatically deployed to every cluster registered in Argo CD. Which configuration best achieves this goal?

Answer: C

Explanation:
An Argo CD ApplicationSet can dynamically generate Applications for all registered clusters based on a shared configuration, ensuring the microservice is automatically deployed and kept in sync across every cluster without manual intervention.


NEW QUESTION # 72
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