Kubernetes — From Beginner to Advanced
Course Curriculum
15 modules designed to master the subject.
Module 1: Introduction to Kubernetes
Understand the purpose, positioning, and core components of Kubernetes.
What Kubernetes is and why it matters
Discover the origins of Kubernetes, its role in the modern cloud-native ecosystem, and why it has become the operating system of the cloud.
Containers vs Kubernetes
Understand the fundamental difference between building a container and orchestrating a fleet of them. Learn why Docker is the vessel and Kubernetes is the port authority.
Core components: Nodes, Pods, Services, Deployments
Meet the building blocks. Understand the four most important objects in the Kubernetes ecosystem and how they work together to run your apps.
Kubernetes Architecture Overview
Look under the hood. Understand the Control Plane and Data Plane relationship that makes Kubernetes so powerful and resilient.
Use cases and benefits
Why bother with the complexity? Discover the real-world scenarios where Kubernetes shines, from microservices to large-scale AI automation.
Module 1 Exercises: Kubernetes Foundations
Put your knowledge to the test. Identify Kubernetes-ready apps and master the basics of kubectl.
Module 2: Kubernetes Architecture
Deep dive into the control plane, worker nodes, and cluster networking.
Control plane and worker nodes deep dive
Go beyond the surface. Analyze the sophisticated communication and synchronization mechanisms between the Kubernetes Brain and Body.
API server, etcd, controller manager, and scheduler
Master the internals of the Kubernetes control plane. Understand how these four services collaborate to maintain the desired state of your global infrastructure.
Kubelet, kube-proxy, and the container runtime
Meet the residents of the worker node. Understand how the Kubelet, kube-proxy, and runtime work together to turn API instructions into running software.
Cluster networking basics
Decode the nervous system of Kubernetes. Learn how Pods talk to each other, how Services find Pods, and the role of the CNI in a distributed network.
Namespaces and resource isolation
Build a multi-tenant empire. Learn how to divide your cluster into logical virtual clusters and enforce strict resource boundaries between teams.
Module 2 Exercises: Cluster Architecture
Put your architectural knowledge to the test. Visualize the cluster, explore namespaces, and verify resource isolation.
Module 3: Kubernetes Objects
Master Pods, Services, Deployments, and persistent storage objects.
Pods: definition, lifecycle, and management
Master the atomic unit of Kubernetes. Learn to define, debug, and manage Pods, and understand how Init containers and Sidecars empower your AI applications.
Deployments and ReplicaSets
Meet the production manager of your cluster. Learn to manage scaled applications, perform zero-downtime rolling updates, and master the art of the K8s rollback.
Services: ClusterIP, NodePort, and LoadBalancer
Master the gateway to your applications. Understand how Kubernetes provides stable endpoints, handles load balancing, and integrates with cloud-native traffic managers.
ConfigMaps and Secrets
Master the art of separation. Learn to decouple your application code from its configuration and keep your most sensitive data safe in the Kubernetes vault.
PersistentVolumes and PersistentVolumeClaims
Give your cluster a memory. Master the Kubernetes storage sub-system and learn to manage stateful data, dynamic provisioning, and persistent caches for your AI models.
Module 3 Exercises: Working with Objects
From YAML to YAML. Build your first full stack on Kubernetes by creating Pods, Deployments, Services, and persistent storage.
Module 4: Deploying Applications
Learn imperative vs. declarative deployments and rolling updates.
Declarative YAML manifests
Move from 'Doing' to 'Declaring.' Master the heart of Kubernetes operations and learn why Infrastructure as Code (IaC) is the key to scalable production systems.
Imperative commands with kubectl
Master the tool of the trade. Learn to navigate your cluster at the speed of thought, debug in real-time, and prototype new services without touching a single YAML file.
Rolling updates and rollbacks
Master the art of the safe transition. Learn to fine-tune your deployment strategies, monitor rollout health, and perform lightning-fast recoveries when production goes sideways.
Labels and selectors
Master the glue that holds Kubernetes together. Learn to organize millions of resources, automate bulk operations, and build dynamic resource relationships using the power of labeling.
Resource requests and limits
Master the economics of the cluster. Learn to size your applications correctly, prevent 'Noisy Neighbor' syndrome, and ensure your AI workloads never crash the entire node.
Module 4 Exercises: Deployment Operations
Master the lifecycle of a production app. Perform rolling updates, debug resource limits, and practice the emergency rollback.
Module 5: Networking in Kubernetes
Master Pod communication, Ingress, and Network Policies.
Pod-to-Pod communication
Master the data plane. Learn how Kubernetes ensures every pod can talk to every other pod without NAT, and understand the magic of CNI plugins like Calico and AWS VPC CNI.
Services and endpoints
Look under the hood of Kubernetes load balancing. Learn how kube-proxy manipulates Linux kernel rules to route traffic and how EndpointSlices manage high-scale connectivity.
Ingress controllers and ingress rules
Master the front door of your cluster. Learn to consolidate traffic, manage domain-based routing, and automate SSL/TLS certificates for your Next.js and FastAPI services.
Network policies and security
Master the firewalls of Kubernetes. Learn to implement Zero Trust security, isolate your sensitive data, and control exactly who can talk to your AI services.
DNS resolution inside clusters
Master the phonebook of the cluster. Learn how CoreDNS handles service discovery, simplifies cross-namespace communication, and scales to millions of queries per second.
Module 5 Exercises: Cluster Networking
Master the data plane. Connect services with Ingress, secure them with Network Policies, and debug internal DNS.
Module 6: Storage and Volumes
Understand dynamic provisioning, PVCs, and stateful workloads.
Advanced volume patterns: ephemeral vs persistent
Go beyond the basic disk. Master temporary storage, host-level access, and the specialized volume types that power modern AI and high-frequency trading systems.
StatefulSets: Managing stateful applications
Stability in a world of chaos. Learn how to deploy databases, vector stores, and clustered systems that require permanent identities and predictable lifecycles.
StorageClasses and dynamic provisioning
Meet the disk orchestra. Learn to automate storage provisioning, fine-tune IOPS for high-performance AI, and master the cross-zone binding patterns of AWS.
Volume snapshots and backups
Protect your digital assets. Learn to take point-in-time snapshots of your persistent data, restore from disasters, and build a robust backup strategy for your AI cluster.
Module 6 Exercises: Stateful Storage
Master the persistence layer. Deploy a stateful cluster, explore ordinal naming, and practice disk expansion.
Module 7: Configuration and Secrets Management
Manage application config and secrets securely in K8s.
Immutable ConfigMaps and Secrets
Lock down your configuration. Learn to use immutability to prevent 'Configuration Drift,' improve cluster performance, and ensure your production AI services are 100% predictable.
Mounting secrets as volumes vs environment variables
Master the security of high-stakes data. Learn why environment variables are the standard but volumes are the fortress, and understand the magic of zero-downtime secret rotation.
External Secrets Operator (ESO) and sidecar injection
Eliminate secret management headaches. Learn to integrate your cluster with AWS Secrets Manager, HashiCorp Vault, and Google Secret Manager using the External Secrets Operator.
Module 7 Exercises: Secure Configuration
Lock it down. Practice building immutable configuration pipelines and delivering secrets via secure RAM-backed volumes.
Module 8: Scaling and Autoscaling
Implement HPA, VPA, and Cluster Autoscaling for high-availability.
Horizontal Pod Autoscaler (HPA)
Build an elastic application. Learn to automatically scale your pod counts based on CPU, memory, or custom business metrics to handle any traffic surge.
Vertical Pod Autoscaler (VPA)
Stop guessing your resource limits. Learn how the VPA automatically rightsizes your containers based on actual usage, preventing OOMKills and reducing cloud waste.
Cluster Autoscaler: Scaling the nodes
Master the infrastructure surge. Learn how the Cluster Autoscaler dynamically adds and removes physical servers from your cluster based on application demand, ensuring you never run out of room.
Module 8 Exercises: Advanced Autoscaling
Build an elastic cluster. Configure HPA for high demand, use VPA to rightsize your containers, and trigger a cluster-level growth.
Module 9: Logging, Monitoring, and Observability
Set up Prometheus, Grafana, and centralized logging.
Metrics Server and kubectl top
See your cluster in real-time. Learn to install the Metrics Server, interpret the 'top' command results, and identify resource-hungry pods before they crash your nodes.
Prometheus and Grafana: The Observability Standard
Master the data engine of DevOps. Learn to install Prometheus, write powerful PromQL queries, and build Grafana dashboards that make your AI infrastructure transparent.
Centralized logging with Loki and FluentBit
Stop chasing logs. Learn to build a high-performance logging pipeline that captures every line from every pod, even after they've been deleted.
Distributed tracing with Jaeger
Follow the thread. Learn how to use distributed tracing to visualize the entire journey of a request through your AI microservices, identifying exactly where latency is hiding.
Module 9 Exercises: Cluster Observability
See the unseen. Practice querying metrics, searching logs, and mapping traces to become a master of cluster performance.
Module 10: Security in Kubernetes
Master RBAC, network isolation, and container image security.
Role-Based Access Control (RBAC)
Master the gatekeeper of the cluster. Learn to implement the principle of Least Privilege using Roles, ClusterRoles, and Bindings to ensure every user and pod has exactly the access they need—and nothing more.
ServiceAccounts and tokens
Give your code an identity. Learn how ServiceAccounts provide the credentials your pods need to talk to the Kubernetes API and cloud providers securely.
Pod Security Standards (Privileged, Baseline, Restricted)
Lock the container door. Learn to use the built-in Pod Security Standards to prevent privilege escalation, block dangerous host access, and enforce a 'Restricted' security posture in your cluster.
Image Security and Scanning
Master the supply chain. Learn to identify vulnerabilities in your container images, enforce signed image policies, and ensure that only trusted code ever runs in your production environment.
Secrets encryption at rest
Master the final layer of defense. Learn how to configure Kubernetes to encrypt your sensitive data inside the etcd database using cloud-managed KMS keys.
Module 10 Exercises: Hardening the Cluster
Fortify your environment. Build precise RBAC policies, automate identity management, and enforce strict security standards.
Module 11: CI/CD with Kubernetes
Automate deployments with GitHub Actions and Helm.
Introduction to Helm
Stop repeating yourself. Learn how Helm, the Kubernetes package manager, allows you to bundle complex applications into reusable 'Charts,' making deployments predictable and manageable.
Helm Charts: Templates and Values
Build your own recipe. Master the Go templating engine, learn to use conditional logic and loops in your YAML, and create flexible charts that work in any environment.
Continuous Deployment with GitHub Actions
From code to cluster. Learn to build a professional CI/CD pipeline using GitHub Actions to automate image building, vulnerability scanning, and Helm deployments.
GitOps with ArgoCD
Master the pulse of the cluster. Learn how to use ArgoCD to implement GitOps, ensuring your cluster stays in sync with your Git repository and automatically heals itself if something drifts.
Canary and Blue-Green Deployments
Eliminate deployment anxiety. Learn to use Argo Rollouts to perform safe Canary releases and zero-downtime Blue-Green switches, ensuring your AI services stay stable for every user.
Module 11 Exercises: Automating Everything
Build the machine. Practice creating dynamic Helm charts, auditing your CI/CD pipelines, and implementing GitOps syncing.
Module 12: Advanced Kubernetes Concepts
Learn about CRDs, Operators, and Service Meshes.
Custom Resource Definitions (CRDs)
Rebuild Kubernetes in your image. Learn how to extend the Kubernetes API by defining your own custom object types, allowing you to manage anything from AI models to database clusters using standard kubectl commands.
The Operator Pattern: Bringing Intelligence to the Cluster
Build an automated SRE. Learn how to use the Operator Pattern to encode complex operational tasks—like database backups and AI model fine-tuning—directly into the Kubernetes Control Plane.
Service Meshes: Istio and Linkerd
Master the invisible network. Learn how Service Meshes provide Zero-Trust security, advanced traffic management, and instant observability across your entire microservice architecture.
Mutating and Validating Webhooks
Control the API. Learn how to use Admission Webhooks to enforce custom rules, automatically inject sidecars, and prevent misconfigurations from ever entering your cluster.
Module 12 Exercises: The Extensible Cluster
Become a cluster architect. Practice building custom resources, exploring the power of operators, and experimenting with service mesh security.
Module 13: Kubernetes on Cloud Platforms
Deploy and manage clusters on EKS, GKE, and AKS.
Amazon Elastic Kubernetes Service (EKS)
Build on the world's most popular cloud. Learn to deploy and manage production-grade clusters on AWS EKS, mastering networking, IAM integration, and managed node groups.
Google Kubernetes Engine (GKE): Autopilot and Standard
Experience the birthplace of Kubernetes. Master Google's managed platform, understand the revolutionary Autopilot mode, and learn to use Workload Identity for seamless cloud security.
Azure Kubernetes Service (AKS): Integration with Azure AD
Master the enterprise cloud. Learn how to deploy and secure Kubernetes on Azure AKS, leveraging Microsoft Entra ID for identity and Virtual Nodes for infinite scaling.
Multi-cloud and Hybrid strategies (Anthos / Arc)
Master the global cluster. Learn how to manage Kubernetes across multiple clouds and on-premises data centers using Google Anthos and Azure Arc for unified control.
Cloud-native backup and restore (Velero)
Master the insurance policy. Learn how to use Velero to back up your cluster's metadata and persistent volumes, enabling disaster recovery and painless migrations between cloud providers.
Module 13 Exercises: Mastering the Clouds
Take the flight. Practice designing cloud-native architectures, comparing managed services, and implementing disaster recovery.
Module 14: Real-World Projects
Apply your skills to full-stack and auto-scaling projects.
Project 1: Building a Production AI Inference Pipeline
Bring it all together. Design and deploy a complete AI inference system featuring a FastAPI backend, Redis caching, GPU-accelerated workers, and automated scaling based on real-time load.
Project 2: Multi-tenant SaaS Platform on Kubernetes
Master the 'Noisy Neighbor' problem. Learn to build a secure, multi-tenant platform where multiple customers share the same cluster without ever seeing each other's data.
Project 3: High-Availability Database Cluster
Master the heart of the stack. Learn to deploy a production-grade, self-healing, and highly-available PostgreSQL cluster using the Operator pattern and persistent storage.
Module 14 Exercises: Architecture and Design
Build the blueprint. Practice designing complex, real-world Kubernetes systems for AI, SaaS, and Databases.
Module 15: Capstone Project
Build and deploy a production-grade Kubernetes system.
The Capstone Project - Part 1: Architecture and Security
The Ultimate Challenge. Design the architecture and security blueprint for a global, multi-cloud AI Video Generation platform that is secure, scalable, and self-healing.
The Capstone Project - Part 2: Implementation and Automation
Build the machine. Implement the Helm charts, GitOps workflows, and CI/CD pipelines needed to deploy the OmniVision platform across a global, multi-cluster environment.
The Capstone Project - Part 3: Operational Excellence
Mission Control. Build the global monitoring dashboards, perform a full disaster recovery drill, and take your final steps toward becoming a certified Kubernetes professional.
Course Overview
Format
Self-paced reading
Duration
Approx 6-8 hours
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