Kubernetes and Cloud Native Associate (KCNA) Study Notes

I sat the Kubernetes and Cloud Native Associate (KCNA) and passed. KCNA is the entry-level CNCF certification - it covers Kubernetes fundamentals and the wider cloud native landscape at a conceptual level, and it is the natural first step before the hands-on CKA, CKAD, and CKS exams.

It is a multiple-choice exam, so it rewards knowing what the pieces are and how they relate, not hands-on kubectl skill. If you already work with Kubernetes, a lot of this will be familiar, so calibrate the prep to what you already know.

Start with Docker Fundamentals first if containers themselves are not yet familiar - the Kubernetes Fundamentals domain below assumes that container runtime knowledge going in, and this post does not re-teach it.

For more content on other relevant certifications, check Certifications.

The exam at a glance

The pass mark is a flat 75%, not a scaled score, so the smaller domains still count - do not leave them to chance.

The four domains

KCNA has four domains. The percentages are the share of scored content, straight from the official curriculum - the bigger the share, the more of your study time it deserves. Note the curriculum was restructured: older guides reference a five-domain version, so calibrate against the current one below.

Kubernetes Fundamentals (44%)

Focus areas:

• Kubernetes architecture - control plane vs node components - see Chapter 1 of the Kubernetes Fundamentals series
• Core resources - Pods, Deployments, ReplicaSets, Services, namespaces - covered across the Kubernetes Fundamentals series
• Configuration - ConfigMaps and Secrets
• kubectl basics and the API-driven, declarative model - see Chapter 2 of the same series
• Containers and the container runtime (CRI)

Container Orchestration (28%)

Focus areas:

• Scheduling and how Pods land on nodes - see Chapter 5 of the Kubernetes Fundamentals series
• Networking model - Services, the CNI, Pod-to-Pod communication - see Chapter 7 of the same series
• Storage - volumes, persistent volumes, the CSI
• Container security and the runtime ecosystem - see Chapter 6 of the same series
• Service mesh and the role it plays

Cloud Native Application Delivery (16%)

Focus areas:

• CI/CD fundamentals in a cloud native context
• GitOps and declarative delivery
• Packaging - Helm and templating
• Application delivery patterns and rollout strategies

Cloud Native Architecture (12%)

Focus areas:

• Autoscaling - HPA vs VPA, the Cluster Autoscaler, and KEDA’s event-driven scaling (including scale-to-zero)
• Serverless and event-driven concepts - FaaS, cold starts, concurrency, the CloudEvents spec
• Open standards and the role of the CNCF
• Observability concepts - metrics, logs, traces (Prometheus, OpenTelemetry)
• Community, governance, and personas - including the CNCF TOC’s role

Mnemonics

Concepts to know well

For KCNA you need to recognise what each piece is and what it is for, not how to configure it:

Easy things to mix up

These are the distinctions the exam likes to probe. Knowing the boundary between a pair is usually the whole question:

• Deployment vs StatefulSet vs DaemonSet - Deployments for stateless replicas, StatefulSets for stable identity and storage, DaemonSets for one Pod per node.
• Service types - ClusterIP is internal only, NodePort exposes a port on every node, LoadBalancer provisions an external load balancer.
• ConfigMap vs Secret - both inject configuration, but Secrets are for sensitive data and are base64-encoded (not encrypted by default).
• HPA vs VPA - the Horizontal Pod Autoscaler changes replica count, the Vertical Pod Autoscaler changes a Pod’s CPU/memory requests and limits.
• Continuous Delivery vs Continuous Deployment - Delivery means code is always release-ready but ships on a manual approval; Deployment pushes to production automatically with no manual gate. KCNA’s “CD” means Delivery, not Deployment.
• Liveness vs readiness vs startup probes - liveness restarts a stuck container, readiness gates traffic, startup protects slow-starting apps.
• Requests vs limits - requests are what the scheduler reserves, limits are the hard ceiling the runtime enforces.
• Labels vs annotations - labels are for selecting and grouping objects, annotations are for non-identifying metadata.
• Control plane vs node components - api-server, scheduler, etcd, and controllers run the cluster; kubelet, kube-proxy, and the runtime run the workloads.
• Container vs container runtime - the container is the running unit, the runtime (containerd, CRI-O) is what runs it via the CRI.

Resources

KCNA is conceptual, so a structured course plus practice questions covers most of it. You do not need to spend much.

Essential

• KCNA Curriculum (CNCF) - the syllabus. The domains and their weights tell you exactly what is in scope.
• LFS250: Kubernetes and Cloud Native Essentials - the Linux Foundation’s own course, written to the KCNA curriculum. The closest thing to an official study path.
• KodeKloud KCNA course - the most recommended third-party prep, with hands-on labs and practice questions. Pick this or LFS250 if you want one guided path.
• James Spurin’s Dive Into… courses - hands-on Docker and Kubernetes training; another solid guided option alongside LFS250 and KodeKloud.
• A throwaway cluster to poke at - minikube, kind, or a free Killercoda sandbox - plus the kubectl Quick Reference. Even on a conceptual exam, touching the objects makes them stick.

Useful

• The KCNA Sample Curriculum Path - the Linux Foundation’s suggested learning order.

Skip if you are tight on time

• Community write-ups like How to Ace the KCNA and Pass the KCNA Exam - good for orientation and a second pass over the topics, but they overlap with the course and curriculum. Pick one, skim the rest.

Notes