
Kubernetes Course
Master Kubernetes from the ground up and gain the hands-on skills to deploy, secure, and operate production-grade clusters. This course covers everything from core architecture and networking to observability, GitOps, and multi-cluster strategies. Whether you're managing workloads today or preparing for your next engineering role, this is the complete Kubernetes training you need.
What your team will master:
You will build a solid understanding of Kubernetes architecture, including the control plane, worker nodes, and the declarative API model. You will learn to run and troubleshoot workloads using Pods, Deployments, StatefulSets, and Jobs. The course covers Kubernetes networking, storage, and configuration management using Services, Ingress, Persistent Volumes, ConfigMaps, and Secrets. You will apply security best practices through RBAC, security contexts, and admission controllers. Advanced topics include Helm, GitOps workflows, service meshes, custom operators, and multi-cluster strategies. By the end, you will have the practical skills to operate and maintain Kubernetes clusters in real production environments.
How your team learns practically Kubernetes Course
How your team practises Kubernetes Course
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Course content
8 Chapters • 39 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsKubernetes Foundations and Architecture
Kubernetes Foundations and Architecture
Lesson 1 • Cluster Architecture Overview
Maps the control plane and worker node components and their responsibilities. Provides the structural foundation for every subsequent operational topic.
Lesson 2 • Kubernetes Objects and the API
Introduces the declarative object model and how the API server exposes cluster state. Students gain fluency with resource definitions before writing any manifests.
Lesson 3 • Setting Up a Local Cluster
Guides students through installing a single-node cluster for hands-on practice. Validates the environment so all subsequent labs run without setup friction.
Lesson 4 • Why Kubernetes Exists
Traces the evolution from bare-metal to containers and the orchestration problem Kubernetes solves. Establishes the business and technical motivation for the platform.
Chapter 2HideHide detailsSee detailsRunning Workloads with Pods
Running Workloads with Pods
Lesson 1 • Init and Sidecar Containers
Covers auxiliary container patterns that extend Pod behaviour without modifying the main image. Students implement logging, proxying, and initialisation patterns.
Lesson 2 • Debugging and Inspecting Pods
Applies kubectl commands and ephemeral containers to diagnose Pod failures. Equips students with a repeatable troubleshooting workflow.
Lesson 3 • Pod Health Probes
Configures liveness, readiness, and startup probes to automate health management. Directly enables reliable rolling updates covered in the next chapter.
Lesson 4 • Pod Anatomy and Lifecycle
Defines Pod structure, container relationships, and phase transitions from Pending to Terminated. Grounds students in the unit all higher-level workloads wrap.
Lesson 5 • Writing and Applying Pod Manifests
Teaches YAML manifest authoring and kubectl apply workflows for Pod creation. Builds the manifest-writing habit used throughout the course.
Chapter 3HideHide detailsSee detailsWorkload Controllers and Scheduling
Workload Controllers and Scheduling
Lesson 1 • Scheduler Concepts and Pod Placement
Explains how the scheduler selects nodes using predicates and priorities, and how to influence placement. Enables intentional workload distribution across the cluster.
Lesson 2 • Jobs and CronJobs
Runs finite and scheduled batch tasks with completion guarantees. Extends workload coverage to non-long-running processes.
Lesson 3 • Deployments and ReplicaSets
Explains how Deployments manage ReplicaSets to maintain desired Pod count and enable updates. Establishes the primary controller for stateless workloads.
Lesson 4 • DaemonSets and Node-Level Workloads
Deploys one Pod per node for infrastructure tasks such as log collection and monitoring agents. Connects to node management topics introduced in Chapter 1.
Lesson 5 • StatefulSets for Stateful Applications
Covers ordered Pod identity, stable network names, and persistent volume claims in StatefulSets. Prepares students to run databases and clustered applications.
Chapter 4HideHide detailsSee detailsKubernetes Networking Fundamentals
Kubernetes Networking Fundamentals
Lesson 1 • The Kubernetes Network Model
Defines the flat network model, Pod-to-Pod communication rules, and CNI plugin responsibilities. Provides the conceptual base for all Service and Ingress configuration.
Lesson 2 • Ingress Controllers and Rules
Deploys an Ingress controller and writes rules for host- and path-based HTTP routing. Consolidates external access through a single entry point.
Lesson 3 • Services: ClusterIP, NodePort, LoadBalancer
Configures the three primary Service types to expose Pods at different network scopes. Students select the correct type for each exposure requirement.
Lesson 4 • DNS and Service Discovery
Explains CoreDNS operation and the DNS naming scheme for Services and Pods. Enables applications to resolve dependencies by name rather than IP.
Lesson 5 • Network Policies for Traffic Control
Restricts Pod-to-Pod and Pod-to-external traffic using NetworkPolicy resources. Introduces security segmentation as a networking concern.
Chapter 5HideHide detailsSee detailsStorage and Configuration Management
Storage and Configuration Management
Lesson 1 • Persistent Volumes and Claims
Covers the PersistentVolume and PersistentVolumeClaim API and the binding workflow. Students provision durable storage independent of Pod scheduling.
Lesson 2 • ConfigMaps for Application Configuration
Creates and consumes ConfigMaps as environment variables and mounted files. Decouples runtime configuration from image builds.
Lesson 3 • Secrets Management
Stores sensitive data in Secret objects and controls access through RBAC. Highlights encoding, encryption at rest, and safe consumption patterns.
Lesson 4 • Storage Classes and Dynamic Provisioning
Configures StorageClass objects to automate volume provisioning from a backend. Removes manual PV creation from the operator workflow.
Lesson 5 • Volumes and Volume Types
Introduces ephemeral and persistent volume types and their lifecycle relative to Pods. Establishes storage vocabulary used throughout the chapter.
Chapter 6HideHide detailsSee detailsSecurity and Access Control
Security and Access Control
Lesson 1 • Pod Security Standards
Applies the built-in Pod Security Standards profiles to namespaces to restrict dangerous Pod configurations. Replaces deprecated PodSecurityPolicy with a supported model.
Lesson 2 • Role-Based Access Control
Creates Roles, ClusterRoles, and bindings to grant least-privilege API access. Directly controls who can create, read, or modify cluster resources.
Lesson 3 • Authentication and Authorisation Basics
Explains how Kubernetes authenticates users and service accounts before authorising requests. Establishes the identity model underlying all RBAC configuration.
Lesson 4 • Security Contexts and Capabilities
Sets container-level and Pod-level security contexts to drop privileges and enforce read-only filesystems. Reduces the blast radius of a compromised container.
Lesson 5 • Admission Controllers and Webhooks
Explains how admission controllers intercept API requests to validate or mutate resources. Enables policy enforcement beyond what RBAC alone provides.
Chapter 7HideHide detailsSee detailsObservability: Monitoring and Logging
Observability: Monitoring and Logging
Lesson 1 • Distributed Tracing Concepts
Introduces trace context propagation and span collection to diagnose latency across microservices. Complements metrics and logs for full observability coverage.
Lesson 2 • Log Collection and Aggregation
Implements a cluster-wide log pipeline using a DaemonSet-based collector forwarding to a central store. Enables log search and correlation across all workloads.
Lesson 3 • Autoscaling Based on Metrics
Configures Horizontal Pod Autoscaler and Vertical Pod Autoscaler using collected metrics. Closes the loop between observability data and automated cluster response.
Lesson 4 • Cluster and Workload Monitoring
Deploys a Prometheus stack to scrape cluster and application metrics and visualise them in Grafana. Produces actionable dashboards for cluster operators.
Lesson 5 • Kubernetes Metrics Architecture
Explains the metrics pipeline from cAdvisor through the Metrics Server to consumers. Provides the foundation for autoscaling and alerting covered later.
Chapter 8HideHide detailsSee detailsProduction Operations and Cluster Management
Production Operations and Cluster Management
Lesson 1 • Cluster Upgrades and Maintenance
Executes node draining, cordon, and control plane upgrades with zero-downtime procedures. Ensures students can maintain cluster currency without service disruption.
Lesson 2 • Resource Optimisation and Cost Control
Analyses resource requests, limits, and idle capacity to reduce infrastructure spend. Applies rightsizing and cluster autoscaler configuration for efficiency.
Lesson 3 • Multi-Tenancy and Namespace Isolation
Partitions a cluster into isolated namespaces with quotas, limits, and RBAC boundaries. Enables safe sharing of a single cluster across multiple teams.
Lesson 4 • Backup and Disaster Recovery
Backs up etcd and application state and validates restore procedures. Prepares students to recover a cluster from data loss or corruption.
Lesson 5 • Troubleshooting Cluster-Level Issues
Diagnoses control plane failures, node NotReady states, and networking outages using systematic methods. Synthesises skills from all previous chapters into a unified troubleshooting framework.
Your valid completion certificate
This course is for you:
Backend developers ready to stop avoiding container orchestration entirely.
DevOps engineers who configure servers but have never touched Kubernetes.
Software engineers transitioning into platform or infrastructure-focused roles.
Cloud architects who need hands-on cluster experience beyond theoretical knowledge.
Site reliability engineers formalising scattered Kubernetes knowledge into structured expertise.
Bootcamp graduates seeking a competitive edge in cloud-native job markets.
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