CyberCode Academy

In this lesson, you’ll learn about: Docker Compose workflows, API versions, and real-world microservices orchestration1. Essential Docker Compose Commands & WorkflowUsing Docker Compose, you can manage your entire application lifecycle with a few commands:🔹 Core Commandsdocker-compose up → Start services
docker-compose build → Build images
docker-compose stop → Stop containers
docker-compose ps → List running containers
docker-compose logs → View logs
⚡ Efficient Development Shortcutdocker-compose up --build -dBuilds images
Pulls dependencies
Starts everything in detached mode
👉 This is the most commonly used real-world command🔹 Scaling Servicesdocker-compose up --scale web=3Runs multiple instances of a service
Useful for:Load balancing
Testing distributed systems

🔹 Overriding Dockerfile Behaviorcommand: python worker.pyOverrides CMD from Dockerfile
Lets you reuse the same image for:Web server
Background worker
Scheduler

2. API Versions & EvolutionDocker Compose started as:Fig (community project)

🔹 Version ComparisonVersionKey Featuresv1Legacy, no service/network namespacesv2Introduced networks, volumes improvementsv3Modern standard, supports scaling & orchestration✅ Recommended Versionversion: "3"Compatible with modern Docker
Required for newer features
3. Real-World Microservices Case StudyA complex voting app built with multiple technologies:Flask → frontend
Node.js → API layer
.NET → worker service
Redis → queue/cache
PostgreSQL → database
4. Multi-Tier NetworkingServices are split into:Front-tier → user-facing
Back-tier → internal services

networks: front-tier: back-tier: 👉 Improves:Security
Isolation
Traffic control
5. Volume Strategies🔹 For Interpreted Languages (Flask, Node.js)Use host-mounted volumes
Enables:Live code updates
No rebuild needed

🔹 For Compiled Languages (.NET)Requires:Rebuilding the image after changes

👉 Key difference in development workflow6. Coordinated DeploymentWithout Docker Compose:You’d manually configure:5+ containers
Networks
Dependencies

With Docker Compose:docker-compose up 👉 Everything starts automatically and correctly configured7. Environment & NamespacingUsing .env:COMPOSE_PROJECT_NAME=votingappPrevents naming conflicts
Keeps projects isolated
Key TakeawaysDocker Compose simplifies multi-container orchestration
up --build -d = real-world workflow shortcut
Version 3 is the modern standard
Supports:Scaling
Networking
Volume management

Essential for microservices architectures
Big PictureBy now, you understand ~95% of practical Docker Compose usage:Build images
Run multi-service apps
Manage dependencies
Scale and debug systems

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In this lesson, you’ll learn about: Docker Compose, multi-container apps, and service orchestration1. What is Docker Compose?Docker Compose is a tool used to:Define
Run
Manage
multi-container applications using a single command
👉 Instead of long docker run commands, you describe everything in one file2. The docker-compose.yml FileCore configuration file written in YAML
Uses version 3 syntax
Example structure:version: "3" services: web: build: . redis: image: redisDefines:Services (containers)
Networks
Volumes

3. Defining ServicesEach service represents a container
Example:Web app (custom build)
Redis (prebuilt image)
🔹 Build vs Imagebuild: → build from local Dockerfile
image: → pull from registry (e.g., Docker Hub)
web: build: . redis: image: redis 4. Port Mappingports: - "5000:5000"Format:host_port : container_port
👉 Allows access from your browser (localhost)5. Volumes (Data Management)🔹 Host-Mounted Volumevolumes: - .:/appSyncs local files with container
Ideal for development
🔹 Named Volumevolumes: - redis-data:/data volumes: redis-data:Persistent storage
Managed by Docker
6. Managing Service Dependenciesdepends_on: - redisEnsures:Redis starts before the web app

👉 Important for backend-dependent services7. Environment Variables with .envStore sensitive or dynamic values:
COMPOSE_PROJECT_NAME=myapp Benefits:Cleaner config
Avoid hardcoding
Easy to manage across environments
🔹 COMPOSE_PROJECT_NAMEDefines a custom project name
Prevents conflicts between projects
👉 Useful when running multiple apps on the same machine8. Running Everything with One Commanddocker-compose upBuilds images
Creates containers
Starts all services
9. Why Docker Compose MattersSimplifies complex setups
Reduces human error
Makes projects:Reproducible
Shareable
Scalable

Key TakeawaysDocker Compose = multi-container management made easy
docker-compose.yml = your infrastructure blueprint
Supports:Services
Volumes
Networks
Environment variables

One command replaces dozens of manual steps

You can listen and download our episodes for free on more than 10 different platforms:
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In this lesson, you’ll learn about: advanced Docker architecture, networking, persistence, and image optimization1. Container Networking & Service CommunicationYou move deeper into Docker networking by connecting multiple containers together.🔹 Default vs Custom NetworksDefault bridge network:Basic isolation
Requires manual IP handling

Custom bridge network (recommended):Automatic DNS resolution
Containers communicate by name (e.g., redis, db)

docker network create my-network 🔹 Why this mattersInstead of:http://172.18.0.3:6379 You can use:redis:6379 👉 Much more stable and production-ready2. Sharing Data Between Containers🔹 Volumes Between ContainersUse shared storage with:VOLUME instruction
--volumes-from

docker run --volumes-from container1 container2 🔹 Use CaseSharing:static files
logs
shared assets

3. Data Persistence with Named Volumes🔹 ProblemContainers are ephemeral
Data disappears when container is removed
🔹 Solution: Named Volumesdocker volume create app-dataManaged internally by Docker
Stored outside container lifecycle
🔹 BenefitsSurvives:container deletion
restarts

Ideal for:databases
user data
stateful apps

4. Image Optimization Techniques🔹 Reduce Build ContextUse .dockerignore:node_modules .env .gitPrevents unnecessary files from being copied
Improves build speed
Reduces image size
🔹 Remove Build DependenciesInstall build tools temporarily
Remove them after build
👉 Results in significantly smaller images5. Advanced Startup Logic (ENTRYPOINT)🔹 PurposeRun scripts before main container starts
ENTRYPOINT ["/start.sh"] 🔹 Use CasesEnvironment setup
Database migrations
Dynamic configuration
6. System Maintenance & Cleanup🔹 Check Disk Usagedocker system df 🔹 Clean Unused Resourcesdocker system prune Removes:stopped containers
unused networks
dangling images
Key TakeawaysCustom networks enable stable service discovery
Named volumes provide persistent storage
.dockerignore improves performance and security
ENTRYPOINT enables startup automation
Docker cleanup tools prevent disk bloat
Big PictureYou are now building production-grade systems with Docker:Multi-container communication
Persistent storage layers
Optimized, lightweight images
Automated startup workflows
Maintainable infrastructure

You can listen and download our episodes for free on more than 10 different platforms:
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In this lesson, you’ll learn about: Docker CLI workflows, container management, live development, and debugging techniques1. Image Management & Docker CLI WorkflowYou start by working with Docker image lifecycle operations:🔹 Build Imagesdocker build -t myapp:1.0 .Uses Dockerfile instructions
Leverages layer caching → faster rebuilds
🔹 Tagging Imagesdocker tag myapp:1.0 username/myapp:1.0Used for version control
Prepares image for sharing
🔹 DockerHub WorkflowLogin → docker login
Push → docker push
Pull → docker pull
👉 Enables sharing across machines and teams2. Running & Managing Containers🔹 Core Run Flagsdocker run -it -p 5000:5000 -e FLASK_APP=app.py myapp FlagPurpose-itInteractive terminal-pPort mapping-eEnvironment variables🔹 Detached Modedocker run -d myappRuns container in background
Frees terminal
🔹 Monitoring Containersdocker logs → view logs
docker stats → live performance metrics
🔹 Restart Policiesdocker run --restart on-failure myappAutomatically restarts crashed containers
Improves reliability in production
3. Live Development with Volumes🔹 Volume Mountingdocker run -v $(pwd):/app myappSyncs local code into container
Enables real-time updates
🔹 Flask Live ReloadSet:FLASK_DEBUG=1Automatically reloads server on file changes
4. Debugging & Container Access🔹 Enter Running Containerdocker exec -it container_id bashInspect filesystem
Run debugging commands
🔹 Run One-Off CommandsRun tests
Check logs
Inspect environment
5. Platform Compatibility Issues⚠️ File Watch Issues (Windows/Mac)Inotify may not work properly in some environments
✅ Solution:Use slim Python images instead of Alpine
👉 Improves:File syncing
Stability of live reload
6. File Permissions HandlingFiles created inside containers may become root-owned
Fix by aligning:container user
host user

Key TakeawaysDocker builds are faster using layer caching
Images are portable via DockerHub
Containers can be:interactive (-it)
background (-d)

Volumes enable real-time development
docker exec is essential for debugging
OS differences can affect file syncing
Big PictureYou’re now operating at a professional Docker workflow level:Building and publishing images
Running production-like containers
Debugging live systems
Developing without rebuild delays

You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cybercode_academy

In this lesson, you’ll learn about: dockerizing a web app, writing Dockerfiles, and optimizing builds1. The Application Architecture (Real-World Example)This lab uses a simple microservices setup:Flask web application (frontend/API)
Redis (backend datastore)

Key idea:Each service runs in its own container
They communicate over a Docker network

👉 This mirrors real production systems (microservices architecture)2. Writing a Dockerfile from ScratchA Dockerfile is the blueprint for building an image in Docker.🧱 FROM — Base ImageFROM python:2.7-alpineUses an official image
Alpine = very small size → faster builds & less storage
⚙️ RUN — Execute CommandsRUN mkdir /appRuns shell commands inside the image
Typically used for:Installing dependencies
Preparing the environment

📁 WORKDIR — Set Working DirectoryWORKDIR /appDefines where commands will run
Avoids hardcoding full paths everywhere
📦 COPY — Add Files to ImageCOPY . .Copies your application code into the container
Includes:Source code
Requirements file

3. Build Optimization (Layer Caching)Docker builds images in layers
Order of instructions matters a lot
✅ Optimized Approach:COPY requirements.txt . RUN pip install -r requirements.txt COPY . .Why?Dependencies don’t change often
Docker caches this layer
Rebuilds become much faster

4. Metadata with LABELLABEL maintainer="[email protected]"Adds useful metadata:Author
Version
Description

👉 Helpful for team environments and production tracking5. Running the Application with CMDCMD ["python", "app.py"]Defines the default command when the container starts
In this case:Launches the Flask app on port 5000

6. How Everything Works TogetherBuild the image:docker build -t myapp .
Run the container:docker run -p 5000:5000 myapp
Access app:Open browser → localhost:5000

7. Key Concepts You Just LearnedHow to dockerize a real application
Core Dockerfile instructions:FROM, RUN, WORKDIR, COPY, LABEL, CMD

How layer caching speeds up builds
How services like Flask + Redis work together in containers
Key TakeawaysDockerfile = reproducible build recipe
Instruction order = performance optimization
Containers isolate services cleanly
This workflow is used in:DevOps
CI/CD
Cloud deployments

You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cybercode_academy