Introduction
Your Journey to Container Mastery
A comprehensive, hands-on guide to mastering Docker and Kubernetes. From basic containers to advanced orchestration.

Why Learn Containerization and Orchestration?
From Docker to Kubernetes is an open-source learning resource designed to help you master containerization and orchestration technologies. This hands-on guide takes you through a progressive journey — starting with Docker fundamentals and advancing to real-world Kubernetes deployments.
Whether you're a developer, DevOps engineer, or technology enthusiast, this resource will help you build modern cloud-native workflows that power today's most innovative applications.
Learning Path Overview
Docker Fundamentals
Master the building blocks of containerization before moving to multi-container orchestration
Kubernetes Orchestration
Scale your container knowledge to manage distributed applications across clusters
Real-world Deployments
Apply container technology to solve actual production challenges
Security & Best Practices
Implement industry standards for secure, efficient containerized applications
Docker Fundamentals
Docker is the gateway to containerization. Our comprehensive coverage includes:
Core Container Concepts
Container Fundamentals
- Container architecture: How containers work at a technical level
- Linux primitives: Namespaces, cgroups, and union filesystems
- OCI specifications: Industry standards for container formats and runtimes
- Container isolation: Process, network, and filesystem boundaries
- Container lifecycle: Creation, running, pausing, stopping, and removal
Working with Containers
- Container commands: Mastering the Docker CLI
- Interactive shells: Connecting to running containers
- Container inspection: Viewing metadata and runtime information
- Resource constraints: Setting CPU, memory, and other limits
- Privileged containers: Use cases and security implications
- Container networking basics: Exposing ports and basic connectivity
Dockerfile Mastery
- Dockerfile syntax: Commands, arguments, and best practices
- Base images: Selecting and creating minimal base images
- Layer optimization: Minimizing image size and build time
- Build context: Understanding what gets sent to the Docker daemon
- Multi-stage builds: Separating build and runtime environments
- BuildKit features: Enhanced building capabilities
Image Management
- Image tagging: Versioning strategies and conventions
- Image inspection: Analyzing image contents and metadata
- Image storage: Local and remote registries
- Image signing: Ensuring supply chain integrity
- Caching strategies: Optimizing builds with layer caching
- Image cleanup: Managing disk space and removing unused images
Advanced Docker Features
Networking
- Network drivers: Bridge, host, overlay, macvlan, and none
- User-defined networks: Creating isolated network environments
- Container DNS: Service discovery within Docker networks
- Network topologies: Common patterns and their use cases
- Container-to-container communication: Direct links and networks
- Exposing services: Port publishing and routing mesh
- Network security: Isolation and access controls
Storage & Volumes
- Volume types: Named volumes, bind mounts, and tmpfs mounts
- Volume drivers: Local and remote storage options
- Data persistence: Strategies for stateful applications
- Backup and restore: Protecting volume data
- Shared storage: Accessing the same data across containers
- Storage performance: Optimizing I/O for containerized applications
Docker Compose
- Compose file structure: YAML configuration for multi-container apps
- Service definitions: Configuring container options declaratively
- Dependencies: Managing startup order and service relationships
- Environment variables: Configuration and secrets management
- Networks & volumes: Defining persistent resources
- Scaling services: Running multiple instances of containers
- Compose extensions: Reusing configuration with extensions
Advanced Topics
- Docker contexts: Managing multiple Docker environments
- Docker content trust: Signed image verification
- Resource monitoring: Tracking container performance
- Logging drivers: Configuring container log management
- Health checks: Implementing container health monitoring
- Docker security scanning: Finding vulnerabilities in images
- Docker Swarm: Built-in orchestration capabilities
Kubernetes Orchestration
Kubernetes takes container management to the next level, enabling scalable, resilient applications:
Core Kubernetes Concepts
Architecture & Components
- Control plane: API Server, etcd, Scheduler, Controller Manager
- Worker nodes: kubelet, container runtime, kube-proxy
- Cluster models: Single node, multi-node, high availability
- Communication patterns: How components interact
- API versioning: Understanding Kubernetes API evolution
- Kubernetes distributions: Differences between implementations
Pods & Workloads
- Pods: The fundamental unit of deployment
- Multi-container pods: Sidecar, adapter, and ambassador patterns
- Pod lifecycle: Creation, scheduling, termination
- Deployments: Managing replica sets and rollouts
- StatefulSets: Running stateful applications
- DaemonSets: Node-level services and agents
- Jobs & CronJobs: Batch processing and scheduled tasks
- ReplicaSets: Low-level pod replication controllers
Configuration
- ConfigMaps: Managing configuration data
- Secrets: Storing sensitive information
- Environment variables: Pod configuration injection
- Resource requests & limits: CPU and memory specifications
- Pod disruption budgets: Ensuring availability during updates
- Namespaces: Logical isolation of resources
- Labels & annotations: Metadata for organization and tooling
Networking Fundamentals
- Kubernetes networking model: Key principles and requirements
- Pod networking: How pods communicate
- Services: Stable endpoints for pod access
- Service types: ClusterIP, NodePort, LoadBalancer, ExternalName
- Network policies: Pod-level firewalls
- DNS resolution: Service discovery mechanisms
- CNI plugins: Configuring the cluster network
Advanced Kubernetes Features
Advanced Deployment
- Rolling updates: Progressive application rollouts
- Blue/green deployments: Zero-downtime environment switching
- Canary releases: Testing with partial traffic
- Feature flags: Decoupling deployment from release
- Helm charts: Packaging Kubernetes applications
- Kustomize: Configuration customization without templates
- GitOps workflows: Git-centered deployment patterns
Storage & Persistence
- Persistent Volumes (PV): Cluster-level storage resources
- Persistent Volume Claims (PVC): Storage requests
- Storage Classes: Dynamic provisioning
- Volume snapshot & restore: Data protection strategies
- StatefulSet storage: Stable storage for stateful apps
- CSI drivers: Pluggable storage integration
- Storage performance: Optimizing for different workloads
Advanced Networking
- Ingress controllers: HTTP/HTTPS routing to services
- Ingress resources: Route configuration
- Service mesh: Istio, Linkerd, and similar technologies
- Mutual TLS: Service-to-service encryption
- East-west traffic: Internal service communication
- North-south traffic: External client communication
- Load balancing algorithms: Traffic distribution strategies
Observability & Operations
- Logging architecture: Cluster and application logs
- Metrics collection: Prometheus integration
- Visualization: Grafana dashboards
- Distributed tracing: Understanding request flows
- Alerting: Proactive notification systems
- Debugging techniques: Troubleshooting pods and services
- Resource monitoring: Capacity and utilization tracking
Security & Compliance
Docker Security
- Container isolation: Security boundaries and limitations
- Rootless containers: Running without root privileges
- Security scanning: Finding vulnerabilities in images
- Runtime security: Monitoring for suspicious behavior
- Secrets management: Protecting sensitive data
- Docker Bench for Security: Applying best practices
- Content trust: Signing and verifying images
Kubernetes Security
- Authentication mechanisms: Certificates, tokens, OIDC
- Authorization: RBAC, ABAC, Node, Webhook
- Admission controllers: Validating and mutating requests
- Pod security standards: Baseline, restricted, privileged
- Pod security context: User IDs, group IDs, capabilities
- Network policies: Microsegmentation
- Secret encryption: Protecting sensitive data at rest
- Security scanning: Vulnerability management
Advanced Topics
Extending Kubernetes
- Custom Resource Definitions (CRDs): Extending the API
- Operators: Automating application operations
- Custom controllers: Implementing business logic
- Webhooks: Modifying and validating API requests
- API aggregation: Adding custom API servers
- Operator SDK: Building operators efficiently
- Kubernetes Gateway API: Next-gen networking
Production Readiness
- High availability configurations: Resilient control planes
- Multi-cluster management: Federation and fleet management
- Disaster recovery: Backup and restore strategies
- Upgrade strategies: Minimizing downtime during upgrades
- Resource optimization: Right-sizing workloads
- Cost management: Controlling cloud expenses
- Compliance: Meeting regulatory requirements
Advanced Autoscaling
- Horizontal Pod Autoscaler: Scaling based on metrics
- Vertical Pod Autoscaler: Automatic resource adjustment
- Cluster Autoscaler: Dynamic node provisioning
- Custom metrics: Scaling on business metrics
- Predictive scaling: Anticipating load changes
- Multi-dimensional autoscaling: Combining approaches
- Scale to zero: Serverless patterns in Kubernetes
DevOps & CI/CD Integration
Containerization and orchestration shine brightest when integrated into modern DevOps workflows:
Continuous Integration & Delivery
CI/CD Pipelines
- Container-based CI/CD: Building efficient pipelines
- Multi-stage testing: Unit, integration, and end-to-end tests
- Image building automation: Constructing and versioning images
- Artifact management: Storing and distributing images
- Deployment automation: GitOps and push-based approaches
- Rollback strategies: Recovering from failed deployments
- Pipeline optimization: Improving speed and reliability
GitOps & Infrastructure as Code
- GitOps principles: Git as single source of truth
- Pull-based deployments: Cluster reconciliation
- GitOps tools: Flux, ArgoCD, and alternatives
- Infrastructure as Code: Terraform, Pulumi with containers
- Policy as Code: OPA, Kyverno, and compliance automation
- Secret management: Vault, Sealed Secrets integration
- Progressive delivery: Feature flags and canary releases
Cloud & Platform Integration
Containers work across environments, with specialized features in different clouds:
AWS Container Services
- Amazon Elastic Container Service (ECS)
- Amazon Elastic Kubernetes Service (EKS)
- AWS Fargate (serverless containers)
- ECR (Elastic Container Registry)
- AWS App Mesh (service mesh)
- AWS Proton (deployment platform)
Google Cloud Platform
- Google Kubernetes Engine (GKE)
- Cloud Run (serverless containers)
- Artifact Registry
- GKE Autopilot
- Cloud Build
- Anthos (hybrid/multi-cloud)
Microsoft Azure
- Azure Kubernetes Service (AKS)
- Azure Container Instances
- Azure Container Registry
- Azure App Service
- Azure Container Apps
- Azure Service Fabric
Target Audience
This comprehensive guide is designed for various roles and experience levels:
Developers
Learn to containerize applications, create efficient images, and understand how containers work in production environments
DevOps Engineers
Master container orchestration, implement CI/CD pipelines, and manage infrastructure efficiently using containers
Platform Engineers
Design and implement container platforms that provide self-service capabilities for development teams
Students & Self-learners
Build practical skills in modern cloud-native technologies that are increasingly required in the job market
Learning Path
Our structured learning approach ensures you build knowledge progressively:
Start with core container concepts, Dockerfiles, and basic commands to run single containers.
Learn to connect containers using Docker Compose and container networking.
Understand Kubernetes architecture and deploy basic applications to a cluster.
Master stateful applications, advanced deployment strategies, and custom resources.
Learn security, scaling, monitoring, and other aspects of production deployments.
Implement automated pipelines for building, testing, and deploying containerized applications.
Prerequisites
Hands-on Approach
This guide emphasizes learning by doing. Each topic includes:
- Conceptual explanations: Understanding the "why" behind technologies
- Step-by-step tutorials: Clear instructions for practical implementation
- Real-world examples: Applications that demonstrate best practices
- Exercises and challenges: Opportunities to test and extend your knowledge
- Troubleshooting guides: Solutions to common problems you might encounter
Getting Started
Ready to begin your container journey? Follow these steps:
Your Next Steps
- Install Docker and Kubernetes tools using our installation guide
- Learn Docker fundamentals to understand container basics
- Build your first container with our hands-on tutorial
- Create multi-container applications using Docker Compose
- Deploy to Kubernetes to experience container orchestration
Community & Support
Join Our Community
- GitHub Discussions: Ask questions and share insights
- Discord Server: Real-time chat with other learners
- Monthly Webinars: Deep dives on advanced topics
- Contribution Guidelines: Help improve this resource
Getting Help
- Troubleshooting Guides: Solutions to common issues
- FAQ Section: Answers to frequently asked questions
- Issue Tracker: Report bugs or suggest improvements
- Email Support: For private inquiries
License
This project is open source and available under the MIT license.
We welcome contributions from the community! Whether it's fixing typos, improving explanations, adding new examples, or translating content—every contribution helps make this resource better for everyone.
Visit our GitHub repository to learn how you can contribute.