docker-compose-orchestration▌
manutej/luxor-claude-marketplace · updated Apr 8, 2026
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Orchestrate multi-container applications with declarative YAML configuration, networking, volumes, and production-ready deployments.
- ›Define entire application stacks in YAML with services, networks, volumes, and secrets; automatic service discovery enables inter-container communication by name
- ›Supports development, staging, and production workflows through compose file overrides and environment-specific configurations with health checks and restart policies
- ›Includes 16+ real-world pa
Docker Compose Orchestration
A comprehensive skill for orchestrating multi-container applications using Docker Compose. This skill enables rapid development, deployment, and management of containerized applications with service definitions, networking strategies, volume management, health checks, and production-ready configurations.
When to Use This Skill
Use this skill when:
- Building multi-container applications (microservices, full-stack apps)
- Setting up development environments with databases, caching, and services
- Orchestrating frontend, backend, and database services together
- Managing service dependencies and startup order
- Configuring networks and inter-service communication
- Implementing persistent storage with volumes
- Deploying applications to development, staging, or production
- Creating reproducible development environments
- Managing application lifecycle (start, stop, rebuild, scale)
- Monitoring application health and implementing health checks
- Migrating from single containers to multi-service architectures
- Testing distributed systems locally
Core Concepts
Docker Compose Philosophy
Docker Compose simplifies multi-container application management through:
- Declarative Configuration: Define entire application stacks in YAML
- Service Abstraction: Each component is a service with its own configuration
- Automatic Networking: Services can communicate by name automatically
- Volume Management: Persistent data and shared storage across containers
- Environment Isolation: Each project gets its own network namespace
- Reproducibility: Same configuration works across all environments
Key Docker Compose Entities
- Services: Individual containers and their configurations
- Networks: Communication channels between services
- Volumes: Persistent storage and data sharing
- Configs: Non-sensitive configuration files
- Secrets: Sensitive data (passwords, API keys)
- Projects: Collection of services under a single namespace
Compose File Structure
version: "3.8" # Compose file format version
services: # Define containers
service-name:
# Service configuration
networks: # Define custom networks
network-name:
# Network configuration
volumes: # Define named volumes
volume-name:
# Volume configuration
configs: # Application configs (optional)
config-name:
# Config source
secrets: # Sensitive data (optional)
secret-name:
# Secret source
Service Definition Patterns
Basic Service Definition
services:
web:
image: nginx:alpine # Use existing image
container_name: my-web # Custom container name
restart: unless-stopped # Restart policy
ports:
- "80:80" # Host:Container port mapping
environment:
- ENV_VAR=value # Environment variables
volumes:
- ./html:/usr/share/nginx/html # Volume mount
networks:
- frontend # Connect to network
Build-Based Service
services:
app:
build:
context: ./app # Build context directory
dockerfile: Dockerfile # Custom Dockerfile
args: # Build arguments
NODE_ENV: development
target: development # Multi-stage build target
image: myapp:latest # Tag resulting image
ports:
- "3000:3000"
Service with Dependencies
services:
web:
image: nginx
depends_on:
db:
condition: service_healthy # Wait for health check
redis:
condition: service_started # Wait for start only
db:
image: postgres:15
healthcheck:
test: ["CMD-SHELL", "pg_isready -U postgres"]
interval: 10s
timeout: 5s
retries: 5
start_period: 30s
redis:
image: redis:alpine
Service with Advanced Configuration
services:
backend:
build: ./backend
command: npm run dev # Override default command
working_dir: /app # Set working directory
user: "1000:1000" # Run as specific user
hostname: api-server # Custom hostname
domainname: example.com # Domain name
env_file:
- .env # Load env from file
- .env.local
environment:
DATABASE_URL: "postgresql://db:5432/myapp"
REDIS_URL: "redis://cache:6379"
volumes:
- ./backend:/app # Source code mount
- /app/node_modules # Preserve node_modules
- app-data:/data # Named volume
ports:
- "3000:3000" # Application port
- "9229:9229" # Debug port
expose:
- "8080" # Expose to other services only
networks:
- backend
- frontend
labels:
- "com.example.description=Backend API"
- "com.example.version=1.0"
logging:
driver: json-file
options:
max-size: "10m"
max-file: "3"
deploy:
resources:
limits:
cpus: '2'
memory: 1G
reservations:
cpus: '0.5'
memory: 512M
Multi-Container Application Patterns
Pattern 1: Full-Stack Web Application
Scenario: React frontend + Node.js backend + PostgreSQL database
version: "3.8"
services:
# Frontend React Application
frontend:
build:
context: ./frontend
dockerfile: Dockerfile
target: development
ports:
- "3000:3000"
volumes:
- ./frontend/src:/app/src
- /app/node_modules
environment:
- REACT_APP_API_URL=http://localhost:4000/api
- CHOKIDAR_USEPOLLING=true # For hot reload
networks:
- frontend
depends_on:
- backend
# Backend Node.js API
backend:
build:
context: ./backend
dockerfile: Dockerfile
ports:
- "4000:4000"
- "9229:9229" # Debugger
volumes:
- ./backend:/app
- /app/node_modules
environment:
- NODE_ENV=development
- DATABASE_URL=postgresql://postgres:password@db:5432/myapp
- REDIS_URL=redis://cache:6379
- JWT_SECRET=dev-secret
env_file:
- ./backend/.env.local
networks:
- fronteHow to use docker-compose-orchestration on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add docker-compose-orchestration
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches docker-compose-orchestration from GitHub repository manutej/luxor-claude-marketplace and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate docker-compose-orchestration. Access the skill through slash commands (e.g., /docker-compose-orchestration) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★29 reviews- ★★★★★Ganesh Mohane· Dec 28, 2024
docker-compose-orchestration has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Kofi Menon· Dec 16, 2024
We added docker-compose-orchestration from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★William Smith· Dec 4, 2024
Keeps context tight: docker-compose-orchestration is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Soo Johnson· Nov 23, 2024
Registry listing for docker-compose-orchestration matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Sakshi Patil· Nov 19, 2024
docker-compose-orchestration reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Omar Mehta· Nov 7, 2024
docker-compose-orchestration fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Maya Johnson· Oct 26, 2024
docker-compose-orchestration has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Ren Rao· Oct 14, 2024
Useful defaults in docker-compose-orchestration — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Chaitanya Patil· Oct 10, 2024
We added docker-compose-orchestration from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Kaira Kim· Sep 25, 2024
docker-compose-orchestration is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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