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Linux Foundation KCNA Exam Syllabus Topics:

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

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Linux Foundation Kubernetes and Cloud Native Associate 認定 KCNA 試験問題 (Q70-Q75):

質問 # 70
What helps an organization to deliver software more securely at a higher velocity?

正解：C

解説：
A CI/CD pipeline is a core practice/tooling approach that enables organizations to deliver software faster and more securely, so D is correct. CI (Continuous Integration) automates building and testing code changes frequently, reducing integration risk and catching defects early. CD (Continuous Delivery/Deployment) automates releasing validated builds into environments using consistent, repeatable steps-reducing manual errors and enabling rapid iteration.
Security improves because automation enables standardized checks on every change: static analysis, dependency scanning, container image scanning, policy validation, and signing/verification steps can be integrated into the pipeline. Instead of relying on ad-hoc human processes, security controls become repeatable gates. In Kubernetes environments, pipelines commonly build container images, run tests, publish artifacts to registries, and then deploy via manifests, Helm, or GitOps controllers-keeping deployments consistent and auditable.
Option A (Kubernetes) is a platform that helps run and manage workloads, but by itself it doesn't guarantee secure high-velocity delivery. It provides primitives (rollouts, declarative config, RBAC), yet the delivery workflow still needs automation. Option B (apt-get) is a package manager for Debian-based systems and is not a delivery pipeline. Option C (Docker Images) are artifacts; they improve portability and repeatability, but they don't provide the end-to-end automation of building, testing, promoting, and deploying across environments.
In cloud-native application delivery, the pipeline is the "engine" that turns code changes into safe production releases. Combined with Kubernetes' declarative deployment model (Deployments, rolling updates, health probes), a CI/CD pipeline supports frequent releases with controlled rollouts, fast rollback, and strong auditability. That is exactly what the question is targeting. Therefore, the verified answer is D.


質問 # 71
Which cloud native tool keeps Kubernetes clusters in sync with sources of configuration (like Git repositories), and automates updates to configuration when there is new code to deploy?

正解：B

解説：
Tools that continuously reconcile cluster state to match a Git repository's desired configuration are GitOps controllers, and the best match here is Flux and ArgoCD, so A is correct. GitOps is the practice where Git is the source of truth for declarative system configuration. A GitOps tool continuously compares the desired state (manifests/Helm/Kustomize outputs stored in Git) with the actual state in the cluster and then applies changes to eliminate drift.
Flux and Argo CD both implement this reconciliation loop. They watch Git repositories, detect updates (new commits/tags), and apply the updated Kubernetes resources. They also surface drift and sync status, enabling auditable, repeatable deployments and easy rollbacks (revert Git). This model improves delivery velocity and security because changes flow through code review, and cluster changes can be restricted to the GitOps controller identity rather than ad-hoc human kubectl access.
Option B ("GitOps Toolkit") is related-Flux uses a GitOps Toolkit internally-but the question asks for a
"tool" that keeps clusters in sync; the recognized tools are Flux and Argo CD in this list. Option C lists service meshes (traffic/security/telemetry), not deployment synchronization tools. Option D lists packaging
/templating tools; Helm and Kustomize help build manifests, but they do not, by themselves, continuously reconcile cluster state to a Git source.
In Kubernetes application delivery, GitOps tools become the deployment engine: CI builds artifacts, updates references in Git (image tags/digests), and the GitOps controller deploys those changes. This separation strengthens traceability and reduces configuration drift. Therefore, A is the verified correct answer.
=========


質問 # 72
You have a CI/CD pipeline that builds and deploys a new version of your application to Kubernetes. After deployment, you notice performance issues and need to roll back to the previous version. Which of the following strategies can be used to achieve a smooth rollback?

正解：D

解説：
Kubernetes Deployments track historical revisions. By leveraging rollback capabilities within Deployments, you can easily revert to a previous successful deployment revision, ensuring a smooth transition without manual intervention.


質問 # 73
Which statement is true about the Container Storage Interface (CSI) in Kubernetes?

正解：B

解説：
CSI provides a standardized interface that allows storage vendors to develop and deploy external drivers. This enables Kubernetes to support new storage systems without changing or recompiling its core components.


質問 # 74
Which of the following actions is supported when working with Pods in Kubernetes?

正解：C

解説：
Pods are commonly created and managed indirectly through higher-level workload resources such as Deployments, which handle Pod creation, scaling, and lifecycle management in a declarative and resilient manner.


質問 # 75
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