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DevOps · Container orchestration and cloud-native deployment

Kubernetes

Learn Kubernetes architecture, pods, deployments, services, ingress, ConfigMaps, Secrets, scaling, storage, monitoring, troubleshooting, and production-ready deployment workflows.

Move from Kubernetes fundamentals to a complete Production Cluster Deployment project with manifests, configuration, scaling, health checks, monitoring, and documentation.

Intermediate to Advanced 8 Weeks 10 Modules Online / Classroom Production Cluster Deployment Project
Explore curriculum → View capstone project

Course overview

Kubernetes is a container-orchestration platform used to deploy, scale, manage, and monitor containerized applications across clusters of machines.

This course introduces Kubernetes architecture, clusters, nodes, pods, ReplicaSets, Deployments, Services, Ingress, ConfigMaps, Secrets, namespaces, resource limits, scaling, storage, probes, logging, and troubleshooting.

The proposed capstone is a Production Cluster Deployment project. It covers application containerization, Kubernetes manifests, configuration management, service exposure, scaling, health checks, monitoring, and deployment documentation.

Kubernetes is powerful, but reliable deployments require clear resource limits, health checks, secure configuration, versioned manifests, monitoring, and a tested rollback plan.

Prerequisites

This course is designed for learners with basic Docker, Linux, and command-line familiarity.

  • Basic computer knowledge.
  • Basic Linux command-line knowledge.
  • Basic Docker and container concepts.
  • Basic Git and GitHub knowledge.
  • Basic YAML syntax awareness is helpful.
  • Basic networking concepts are helpful.

Readiness activity

Explain the difference between a container image and a running container. Identify two reasons an application may need multiple running instances.

Who can explore this course?

Docker learners

Orchestrate containers

Move from running containers to managing them at scale.

Developers

Deploy applications

Learn how modern applications are deployed and managed in clusters.

DevOps learners

Build cloud-native skills

Understand Kubernetes objects, configuration, scaling, and operations.

IT professionals

Manage workloads

Learn deployment, monitoring, troubleshooting, and infrastructure concepts.

What you will learn

  • Explain Kubernetes architecture and core components.
  • Use kubectl to inspect and manage cluster resources.
  • Create and manage pods, ReplicaSets, and Deployments.
  • Expose applications using Services and Ingress.
  • Manage configuration using ConfigMaps and Secrets.
  • Apply resource requests, limits, and namespaces.
  • Scale applications manually and automatically.
  • Use persistent storage and volume concepts.
  • Configure readiness, liveness, and startup probes.
  • Inspect logs, events, and resource usage.
  • Troubleshoot common pod, service, and deployment issues.
  • Prepare a production-ready Kubernetes deployment project.

Curriculum outline

The ten-module outline moves from Kubernetes fundamentals to a complete Production Cluster Deployment. Exact cluster type, cloud provider, container registry, and monitoring tools should be confirmed before delivery.

01

Kubernetes fundamentals

Understand why Kubernetes is used and learn its core architecture.

  • Containers and orchestration.
  • Kubernetes cluster concepts.
  • Control plane and worker nodes.
  • API server, scheduler, and controller concepts.
  • kubelet and container runtime.
  • Declarative configuration and desired state.

Practice: Draw a Kubernetes cluster and identify the control plane, worker nodes, pods, and user access path.

02

Environment and kubectl

Set up a Kubernetes learning environment and use kubectl to interact with a cluster.

  • Local cluster options.
  • Managed Kubernetes options.
  • kubectl installation and configuration.
  • Contexts and namespaces.
  • Basic kubectl commands.
  • YAML manifest structure.

Practice: Connect to a cluster, view nodes and namespaces, and inspect an existing resource using kubectl.

03

Pods and containers

Understand pods, containers, images, and basic workload execution.

  • Pod concepts and lifecycle.
  • Containers and container images.
  • Single-container and multi-container pods.
  • Pod YAML structure.
  • Labels and annotations.
  • Pod logs and exec access.

Practice: Create a pod from an approved container image and inspect its status, logs, and events.

04

Deployments and ReplicaSets

Manage application replicas, updates, and rollback workflows.

  • ReplicaSet concepts.
  • Deployment concepts.
  • Desired and current replica counts.
  • Rolling updates.
  • Revision history and rollback.
  • Deployment strategies.

Practice: Deploy an application with multiple replicas, update its image, and perform a controlled rollback.

05

Services and networking

Expose and connect applications using Kubernetes networking objects.

  • Cluster networking concepts.
  • Service types and use cases.
  • ClusterIP, NodePort, and LoadBalancer.
  • Service discovery and DNS.
  • Ingress concepts.
  • Ingress controllers and routing.

Practice: Expose a deployment using a Service and configure an Ingress route for a sample application.

06

Configuration and secrets

Separate application configuration and sensitive data from container images.

  • ConfigMap concepts.
  • Environment variables and mounted files.
  • Secret concepts and base64 encoding.
  • Secret usage in pods.
  • Namespace isolation.
  • Configuration management practices.

Practice: Configure an application using a ConfigMap and securely inject a non-production secret.

07

Scaling, resources, and storage

Manage application capacity, resource usage, and persistent data.

  • Manual scaling.
  • Horizontal Pod Autoscaler concepts.
  • Resource requests and limits.
  • CPU and memory management.
  • PersistentVolume concepts.
  • PersistentVolumeClaims and StorageClasses.

Practice: Set resource requests and limits, scale a deployment, and attach persistent storage to a sample workload.

08

Health checks and observability

Improve application reliability through probes, logging, and monitoring.

  • Readiness probes.
  • Liveness probes.
  • Startup probes.
  • Pod logs and events.
  • Resource metrics.
  • Monitoring and alerting concepts.

Practice: Add readiness and liveness probes to a deployment and observe restart and traffic-routing behavior.

09

Security and troubleshooting

Apply security practices and diagnose common Kubernetes problems.

  • Role-based access control concepts.
  • Service accounts and permissions.
  • Network policies.
  • Pod security practices.
  • Debugging pods and services.
  • Common deployment errors.

Practice: Diagnose a controlled pod failure using kubectl describe, logs, events, and service checks.

10

Capstone delivery

Complete the Production Cluster Deployment project and prepare a professional Kubernetes demonstration.

  • Define application, users, and deployment requirements.
  • Containerize the application.
  • Create versioned Kubernetes manifests.
  • Deploy the application to an approved cluster.
  • Configure services, ingress, and configuration.
  • Add scaling, probes, and resource limits.
  • Document deployment, monitoring, and rollback procedures.

Practice: Submit a complete Production Cluster Deployment with manifests, documentation, monitoring notes, and rollback plan.

Practical exercise ideas

Complete these smaller activities before assembling the final Production Cluster Deployment project.

Pods

First pod

Create, inspect, and delete a pod using kubectl and YAML.

Deployments

Rolling update

Deploy an application, update its image, and roll back a change.

Networking

Service exposure

Expose a deployment using ClusterIP, NodePort, or Ingress.

Configuration

ConfigMap app

Configure an application using ConfigMaps and environment variables.

Scaling

Replica scaling

Scale a deployment and observe pod creation and resource usage.

Troubleshooting

Pod diagnosis

Investigate a failing pod using logs, events, and resource details.

Suggested eight-week learning plan

This is an illustrative learning sequence. Confirm the academy's official timetable, cluster environment, cloud provider, container registry, and assessment requirements before publishing.

Weekly focus and practical milestones
Week Focus Suggested milestone
01 Kubernetes fundamentals Explain cluster architecture and use basic kubectl commands.
02 Pods and containers Create and inspect a pod from an approved image.
03 Deployments and ReplicaSets Deploy, update, and roll back an application.
04 Services and networking Expose an application using a Service and Ingress.
05 Configuration and secrets Use ConfigMaps and Secrets in a sample deployment.
06 Scaling, resources, and storage Scale workloads and configure resource limits.
07 Health checks and troubleshooting Add probes and diagnose a controlled failure.
08 Capstone presentation Submit and present the Production Cluster Deployment.
Deploy and operate a cloud-native application

Capstone project

Production Cluster Deployment

Build a complete Production Cluster Deployment for a chosen approved application. Possible examples include a web application, REST API, task manager, blog platform, or another suitable educational workload.

Core project requirements

  • Define the application purpose, users, and deployment requirements.
  • Containerize the application using an approved base image.
  • Create versioned Kubernetes YAML manifests.
  • Create a namespace for the project.
  • Deploy the application using a Deployment and ReplicaSet.
  • Expose the application using a Service and, where appropriate, Ingress.
  • Use ConfigMaps for non-sensitive configuration.
  • Use Secrets for approved non-production sensitive values.
  • Set CPU and memory requests and limits.
  • Configure readiness, liveness, and startup probes.
  • Scale the application manually or with an autoscaler.
  • Add persistent storage only where the application requires it.
  • Document deployment, monitoring, troubleshooting, and rollback steps.

Quality requirements

  • Use meaningful resource, namespace, label, and annotation names.
  • Use versioned container images instead of latest tags.
  • Keep manifests organized and reusable across environments.
  • Use least-privilege service accounts and permissions.
  • Do not commit cluster credentials, tokens, or production secrets.
  • Use approved container registries and cluster environments only.
  • Set resource requests and limits for predictable workloads.
  • Use health probes and meaningful application endpoints.
  • Test deployment, scaling, service access, and rollback.
  • Document known limitations and operational considerations.

A production-ready Kubernetes deployment should be reproducible, observable, resource-aware, securely configured, and recoverable through a tested rollback process.

Suggested project structure

Keep application code, Docker files, Kubernetes manifests, and documentation organized for maintainability.

kubernetes-deployment/
├── app/
│   ├── src/
│   └── tests/
├── docker/
│   └── Dockerfile
├── k8s/
│   ├── namespace.yaml
│   ├── configmap.yaml
│   ├── secret.example.yaml
│   ├── deployment.yaml
│   ├── service.yaml
│   ├── ingress.yaml
│   └── hpa.yaml
├── docs/
│   ├── deployment-guide.md
│   └── rollback-plan.md
├── README.md
└── .gitignore

Do not commit Kubernetes credentials, kubeconfig files, cloud keys, registry tokens, or production secrets to a public repository.

Kubernetes deployment workflow

Kubernetes deployments are iterative. Application changes, resource constraints, configuration changes, and monitoring results may require updates to manifests, images, or cluster configuration.

Plan

Define workloads

Identify application components, dependencies, configuration, and scaling needs.

Containerize

Build images

Create reproducible container images and store them in an approved registry.

Configure

Create manifests

Define Deployments, Services, ConfigMaps, Secrets, and Ingress resources.

Deploy

Apply to cluster

Deploy resources to an approved namespace and verify rollout status.

Observe

Monitor workloads

Review pods, logs, events, resource use, and application health.

Operate

Update safely

Use versioned images, controlled rollouts, and tested rollback procedures.

Kubernetes uses a declarative model: you describe the desired state of workloads, and the platform works to maintain that state.

Tools and technologies

The exact cluster type, cloud provider, and monitoring stack may vary by delivery. The proposed toolkit focuses on practical Kubernetes operations and deployment.

  • Kubernetes
  • kubectl
  • YAML
  • Docker
  • Container registries
  • Deployments
  • Services
  • Ingress
  • ConfigMaps
  • Secrets
  • PersistentVolumes
  • Git
  • GitHub

Supporting concepts

  • Clusters, nodes, pods, and namespaces.
  • Deployments, ReplicaSets, and rolling updates.
  • Services, DNS, and Ingress routing.
  • ConfigMaps, Secrets, and environment configuration.
  • Resource requests, limits, scaling, and storage.
  • Probes, logging, monitoring, and troubleshooting.

Learning outcomes

By completing the proposed lessons and exercises, aim to demonstrate the following abilities:

  • Explain Kubernetes architecture and core objects.
  • Use kubectl to inspect and manage cluster resources.
  • Create and manage pods, Deployments, and ReplicaSets.
  • Expose applications using Services and Ingress.
  • Use ConfigMaps and Secrets appropriately.
  • Configure scaling, resource limits, and storage.
  • Add health probes and monitor workloads.
  • Troubleshoot pods, services, and deployments.
  • Apply Kubernetes security and operational practices.
  • Build and document a Production Cluster Deployment.

These are learning objectives, not guarantees of employment, certification, placement, or a specific DevOps role. Progress depends on practice, Linux and Docker knowledge, security awareness, and continued learning.

Related career interests

Illustrative directions for continued learning, not job or placement guarantees.

  • Kubernetes Trainee
  • DevOps Engineer Trainee
  • Cloud Operations Trainee
  • Platform Engineer Trainee
  • Site Reliability Engineer Trainee
  • Technology Trainee
  • Associate Engineer

Portfolio presentation ideas

  • Explain the application, components, and deployment flow.
  • Show Kubernetes manifests and namespace organization.
  • Demonstrate Deployment rollout and rollback.
  • Present Service and Ingress access paths.
  • Explain ConfigMaps, Secrets, and resource limits.
  • Discuss probes, monitoring, troubleshooting, and rollback.

Frequently asked questions

Who is this course for?

It is suitable for developers, Docker learners, DevOps learners, and IT professionals who want to deploy and manage containerized applications.

Do I need Docker knowledge?

Basic Docker knowledge is recommended because Kubernetes runs and manages containerized workloads.

Do I need Linux knowledge?

Basic Linux and command-line knowledge is helpful. The course introduces the required commands and workflows for practical Kubernetes use.

Will the course cover kubectl?

Yes. It covers kubectl installation, contexts, namespaces, resource inspection, logs, events, and common management commands.

Will the course cover Deployments?

Yes. It covers Pods, ReplicaSets, Deployments, rolling updates, revision history, and rollback workflows.

Will the course cover Services and Ingress?

Yes. It covers ClusterIP, NodePort, LoadBalancer, service discovery, Ingress, and Ingress-controller concepts.

Will the course cover ConfigMaps and Secrets?

Yes. It covers configuration separation, environment variables, mounted files, and secure handling of sensitive values.

What is the capstone project?

The proposed capstone is a Production Cluster Deployment covering containerization, Kubernetes manifests, deployment, services, configuration, scaling, probes, monitoring, and rollback.

Do I need a cloud account?

A cloud account may be required for managed-cluster exercises. Confirm the academy's approved cloud provider, account setup, permissions, and security rules before enrollment.

How long is the course?

The supplied course information proposes a duration of eight weeks. Confirm the academy's official schedule, cluster environment, cloud access, and assessment requirements.

Does this course guarantee a job?

No. The course can support practical learning and portfolio development, but it does not guarantee employment, placement, certification, or salary.

How do I enroll?

This page is a frontend course-information demonstration. Enrollment, payment, scheduling, and admission workflows are not implemented here.

Operate cloud-native applications

Build your Kubernetes deployment

Study Kubernetes architecture, pods, Deployments, Services, Ingress, ConfigMaps, Secrets, scaling, storage, monitoring, and troubleshooting through a practical portfolio project.

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