docker-best-practices▌
josiahsiegel/claude-plugin-marketplace · updated Apr 8, 2026
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Comprehensive Docker best practices for images, containers, and production deployments.
- ›Covers base image selection (Wolfi/Chainguard, Alpine, Distroless), Dockerfile structure with optimal layer ordering, multi-stage builds, and layer optimization techniques to minimize image size and build time
- ›Includes container runtime security patterns: running as non-root, dropping capabilities, read-only filesystems, resource limits, health checks, and logging configuration
- ›Provides Docker Com
🚨 CRITICAL GUIDELINES
Windows File Path Requirements
MANDATORY: Always Use Backslashes on Windows for File Paths
When using Edit or Write tools on Windows, you MUST use backslashes (\) in file paths, NOT forward slashes (/).
Examples:
- ❌ WRONG:
D:/repos/project/file.tsx - ✅ CORRECT:
D:\repos\project\file.tsx
This applies to:
- Edit tool file_path parameter
- Write tool file_path parameter
- All file operations on Windows systems
Documentation Guidelines
NEVER create new documentation files unless explicitly requested by the user.
- Priority: Update existing README.md files rather than creating new documentation
- Repository cleanliness: Keep repository root clean - only README.md unless user requests otherwise
- Style: Documentation should be concise, direct, and professional - avoid AI-generated tone
- User preference: Only create additional .md files when user specifically asks for documentation
Docker Best Practices
This skill provides current Docker best practices across all aspects of container development, deployment, and operation.
Image Best Practices
Base Image Selection
2025 Recommended Hierarchy:
- Wolfi/Chainguard (
cgr.dev/chainguard/*) - Zero-CVE goal, SBOM included - Alpine (
alpine:3.19) - ~7MB, minimal attack surface - Distroless (
gcr.io/distroless/*) - ~2MB, no shell - Slim variants (
node:20-slim) - ~70MB, balanced
Key rules:
- Always specify exact version tags:
node:20.11.0-alpine3.19 - Never use
latest(unpredictable, breaks reproducibility) - Use official images from trusted registries
- Match base image to actual needs
Dockerfile Structure
Optimal layer ordering (least to most frequently changing):
1. Base image and system dependencies
2. Application dependencies (package.json, requirements.txt, etc.)
3. Application code
4. Configuration and metadata
Rationale: Docker caches layers. If code changes but dependencies don't, cached dependency layers are reused, speeding up builds.
Example:
FROM python:3.12-slim
# 1. System packages (rarely change)
RUN apt-get update && apt-get install -y --no-install-recommends \
gcc \
&& rm -rf /var/lib/apt/lists/*
# 2. Dependencies (change occasionally)
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
# 3. Application code (changes frequently)
COPY . /app
WORKDIR /app
CMD ["python", "app.py"]
Multi-Stage Builds
Use multi-stage builds to separate build dependencies from runtime:
# Build stage
FROM node:20-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build
# Production stage
FROM node:20-alpine AS runtime
WORKDIR /app
# Only copy what's needed for runtime
COPY /app/dist ./dist
COPY /app/node_modules ./node_modules
USER node
CMD ["node", "dist/server.js"]
Benefits:
- Smaller final images (no build tools)
- Better security (fewer attack vectors)
- Faster deployment (smaller upload/download)
Layer Optimization
Combine commands to reduce layers and image size:
# Bad - 3 layers, cleanup doesn't reduce size
RUN apt-get update
RUN apt-get install -y curl
RUN rm -rf /var/lib/apt/lists/*
# Good - 1 layer, cleanup effective
RUN apt-get update && \
apt-get install -y --no-install-recommends curl && \
rm -rf /var/lib/apt/lists/*
.dockerignore
Always create .dockerignore to exclude unnecessary files:
# Version control
.git
.gitignore
# Dependencies
node_modules
__pycache__
*.pyc
# IDE
.vscode
.idea
# OS
.DS_Store
Thumbs.db
# Logs
*.log
logs/
# Testing
coverage/
.nyc_output
*.test.js
# Documentation
README.md
docs/
# Environment
.env
.env.local
*.local
Container Runtime Best Practices
Security
docker run \
# Run as non-root
--user 1000:1000 \
# Drop all capabilities, add only needed ones
--cap-drop=ALL \
--cap-add=NET_BIND_SERVICE \
# Read-only filesystem
--read-only \
# Temporary writable filesystems
--tmpfs /tmp:noexec,nosuid \
# No new privileges
--security-opt="no-new-privileges:true" \
# Resource limits
--memory="512m" \
--cpus="1.0" \
my-image
Resource Management
Always set resource limits in production:
# docker-compose.yml
services:
app:
deploy:
resources:
limits:
cpus: '2.0'
memory: 1G
reservations:
cpus: '1.0'
memory: 512M
Health Checks
Implement health checks for all long-running containers:
HEALTHCHECK \
CMD curl -f http://localhost:3000/health || exit 1
Or in compose:
services:
app:
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost/health"]
interval: 30s
timeout: 3s
retries: 3
start_period: 40s
Logging
Configure proper logging to prevent disk fill-up:
services:
app:
logging:
driver: "json-file"
options:
max-size: "10m"
max-file: "3"
Or system-wide in /etc/docker/daemon.json:
{
"log-driver": "json-file",
"log-opts": {
"max-size": "10m",
"max-file": "3"
}
}
Restart Policies
services:
app:
# For development
restart: "no"
# For production
restart: unless-stopped
# Or with fine-grained control (Swarm mode)
deploy:
restart_policy:
condition: on-failure
delay: 5s
max_attempts: 3
window: 120s
Docker Compose Best Practices
File Structure
# No version field needed (Compose v2.40.3+)
services:
# Service definitions
web:
# ...
api:
# ...
database:
# ...
networks:
# Custom networks (preferred)
frontend:
backend:
internal: true
volumes:
# Named volumes (preferred for persistence)
db-data:
app-data:
configs:
# Configuration files (Swarm mode)
app-config:
file: ./config/app.conf
secrets:
# Secrets (Swarm mode)
db-password:
file: ./secrets/db_pass.txt
Network Isolation
networks:
how to use docker-best-practicesHow to use docker-best-practices on Cursor
AI-first code editor with Composer
1Prerequisites
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-best-practices
2Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
$npx skills add https://github.com/josiahsiegel/claude-plugin-marketplace --skill docker-best-practicesThe skills CLI fetches docker-best-practices from GitHub repository josiahsiegel/claude-plugin-marketplace and configures it for Cursor.
3Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
◆ Which agents do you want to install to?││ ── Universal (.agents/skills) ── always included ────│ • Amp│ • Antigravity│ • Cline│ • Codex│ ●Cursor(selected)│ • Cursor│ • Windsurf4Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/docker-best-practicesReload or restart Cursor to activate docker-best-practices. Access the skill through slash commands (e.g., /docker-best-practices) 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.
Additional Resources
List & Monetize Your Skill
Submit your Claude Code skill and start earning
GET_STARTED →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.
general reviewsRatings
4.7★★★★★73 reviews- ★★★★★Charlotte Thompson· Dec 28, 2024
Useful defaults in docker-best-practices — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Mei Srinivasan· Dec 20, 2024
docker-best-practices is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Sofia Kim· Dec 12, 2024
docker-best-practices reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Li Jain· Dec 8, 2024
Registry listing for docker-best-practices matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Harper Iyer· Dec 8, 2024
Solid pick for teams standardizing on skills: docker-best-practices is focused, and the summary matches what you get after install.
- ★★★★★Shikha Mishra· Dec 4, 2024
docker-best-practices reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Li Khanna· Dec 4, 2024
Registry listing for docker-best-practices matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Liam Kapoor· Dec 4, 2024
Keeps context tight: docker-best-practices is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Mei Okafor· Nov 27, 2024
Keeps context tight: docker-best-practices is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Arjun Chen· Nov 27, 2024
Useful defaults in docker-best-practices — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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