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kubernetes

    AI-AgenticAI

    AI-DeepLearning

    AI-GenAI

    AI-Infrastructure

    AI-Machine-Learning

    AI-Math

    AWS

    Azure

    kubernetes
    • Kubernetes: Control Loops, Scheduling, and GPUs


    • Image Internals: From OCI Layers to a Running Container


    • Container Internals: What a Container Really Is


    • Kubernetes Pod Internals: What a Pod Really Is


    • Kubernetes API Server Internals


    • Kubernetes Resource Allocation: Requests, Limits, QoS, and Quotas


    • etcd Architecture Explained


    • Kubernetes Scheduler Internals


    • Kubelet Internals: The Node Agent That Runs Everything


    • Kubernetes Informers & Controllers Explained


    • Kubernetes Networking: Pods, Services, Ingress, and CNI


    • Kubernetes Storage: PV, PVC, StorageClass, and CSI


    • Helm: Kubernetes Package Manager


    • Cloud Native Observability: Prometheus, Grafana, OpenTelemetry, and Tracing


    • GPU Scheduling in Kubernetes: Device Plugins, GPU Operator & MIG


    • NVIDIA Network Operator: InfiniBand, SR-IOV, RDMA, and Multus


    • Dynamic Resource Allocation: The Future of GPU Scheduling in Kubernetes


    • Kubernetes Performance at Scale


    • Optimizing AI Inference at Scale: The Full Stack


    • Kueue: Kubernetes-Native Job Queuing and Quota Management


    • Multi-Node Distributed Training on Kubernetes


    • Kubernetes Topology Manager: NUMA-Aware GPU Scheduling


    • NVIDIA NIM: Optimized Inference Microservices on Kubernetes


    • GPU Autoscaling on Kubernetes: KEDA, HPA, and Cluster Autoscaler


    • Fine-Tuning LLMs: LoRA, QLoRA, PEFT, and NeMo on Kubernetes


    • Flash Attention: Fast, Memory-Efficient Attention for LLMs


    • Kubernetes and Cloud Native Certification Path


    • KCNA Mock Exam — Set 1


    • KCNA Mock Exam — Set 2


    • KCSA Mock Exam — Set 1


    • KCSA Mock Exam — Set 2


    • kubernetes Index


    Management

    Programming

    Terraform

    Z_Appendix

Cover Image for Kubernetes and Cloud Native Certification Path
kubernetes

Kubernetes and Cloud Native Certification Path

Foundational concepts of Kubernetes and the cloud native ecosystem, covering container orchestration, architecture, observability, and core Kubernetes components.

Kubernetes
Cloud Native
KCNA
CNCF
Containers
DevOps
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Kubernetes Certification Path

Which Certification Should You Start With?

RoleRecommended Path
Software EngineerKCNA → CKAD
Platform EngineerKCNA → CKA
DevOps EngineerKCNA → CKA
Cloud EngineerKCNA → CKA
SREKCNA → CKA
AI / MLOps EngineerKCNA → CKAD → CKA
flowchart LR
    KCNA[KCNA<br/>Cloud Native Fundamentals]
    CKAD[CKAD<br/>Application Developer]
    CKA[CKA<br/>Cluster Administrator]

    KCNA --> CKAD
    KCNA --> CKA

    CKAD --> Expert[Production Kubernetes]
    CKA --> Expert

1. KCNA (Kubernetes and Cloud Native Associate)

Focuses on conceptual understanding rather than deep hands-on configuration.

Difficulty: ⭐⭐☆☆☆

  • Format: MCQs
  • Price: $250 (Euro 212)
  • Duration: 1.5 hours
  • Focus: Concepts over commands
  • No heavy kubectl troubleshooting

KCNA Syllabus Overview

DomainWeightKey Areas
Kubernetes Fundamentals44%Kubernetes Core Concepts
Cluster Architecture (control plane & worker nodes)
Administration basics
Scheduling concepts
Containerization fundamentals
Container Orchestration28%Networking model and CNI basics
Security fundamentals
Troubleshooting concepts
Storage (PV, PVC, StorageClass)
Cloud Native Application Delivery16%Application delivery models
CI/CD fundamentals
GitOps basics
Debugging concepts
Cloud Native Architecture12%Observability (metrics, logs, traces)
Cloud native ecosystem and CNCF landscape
Principles (microservices, immutable infra, declarative systems)
Community and collaboration fundamentals

2. Certified Kubernetes Application Developer (CKAD)

Focuses on application development and deployment in Kubernetes.

Difficulty: ⭐⭐⭐⭐☆

  • Format: Performance-based (hands-on tasks)
  • price: $300 (Euro 254)
  • Duration: 2 hours
  • Focus: Application design, deployment, and maintenance
  • Heavy use of kubectl for troubleshooting and configuration

CKAD Syllabus Overview

DomainWeightKey Topics
Application Design and Build20%Define, build, and modify container images
Choose correct workload resource (Deployment, DaemonSet, Job, CronJob, StatefulSet)
Multi-container Pod patterns (sidecar, init, ambassador, adapter)
Persistent and ephemeral volumes
Application Deployment20%Rolling updates and rollbacks
Blue/Green and Canary strategies using Kubernetes primitives
Deploy applications with Helm
Manage configurations using Kustomize
Application Observability and Maintenance15%API deprecations awareness
Liveness, Readiness, and Startup probes
kubectl monitoring commands
Container logs
Debugging techniques
Application Environment, Configuration and Security25%CRDs and Operators
Authentication, Authorization, Admission Control
Requests, Limits, ResourceQuotas
ConfigMaps
Secrets (create and consume)
ServiceAccounts
SecurityContexts and Linux capabilities
Services and Networking20%Service types (ClusterIP, NodePort, LoadBalancer, Headless)
NetworkPolicies (ingress/egress rules)
Ingress configuration and routing
Troubleshooting service connectivity

3 Certified Kubernetes Administrator (CKA)

Focuses on cluster administration and management.

Difficulty: ⭐⭐⭐⭐⭐

  • Format: Performance-based (hands-on tasks)
  • price: $445 (Euro 254)
  • Duration: 2 hours
  • Focus: Cluster setup, maintenance, and troubleshooting

CKA Syllabus Overview

DomainWeightKey Topics
Storage10%Implement StorageClasses and dynamic provisioning
Configure volume types, access modes (RWO, ROX, RWX) and reclaim policies
Create and manage PersistentVolumes (PV) and PersistentVolumeClaims (PVC)
Troubleshooting30%Troubleshoot cluster and node failures
Troubleshoot control plane components
Monitor cluster and application resource usage
Inspect and manage container logs and output streams
Troubleshoot Services and networking issues
Workloads & Scheduling15%Perform rolling updates and rollbacks
Configure applications with ConfigMaps and Secrets
Implement Horizontal Pod Autoscaling
Understand self-healing primitives (ReplicaSet, Deployment)
Configure scheduling constraints (resource limits, nodeSelector, affinity, taints/tolerations)
Cluster Architecture, Installation & Configuration25%Manage RBAC (Roles, ClusterRoles, RoleBindings)
Prepare infrastructure for cluster installation
Create and manage clusters using kubeadm
Upgrade and manage cluster lifecycle
Configure highly available control plane
Install components using Helm and Kustomize
Understand extension interfaces (CNI, CSI, CRI)
Install and manage CRDs and Operators
Services & Networking20%Pod-to-Pod connectivity
Implement and enforce NetworkPolicies
Use Service types (ClusterIP, NodePort, LoadBalancer)
Configure Gateway API and Ingress
Use Ingress controllers and resources
Understand CoreDNS and service discovery

Related Posts

  • KCNA Mock Exam — Set 1 — practice questions for the KCNA exam on this path
  • KCSA Mock Exam — Set 1 — practice questions for the KCSA exam on this path
Hitesh Sahu
Written by Hitesh Sahu, a passionate developer and blogger.

Tue Feb 24 2026

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Ethical AI vs Responsible AI vs Trustworthy AI

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What is AI Models and How to pick the right one?

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