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Docker Best Practices

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rohitg00
docker-best-practices

Docker best practices including multi-stage builds, compose patterns, image optimization, and security

Overview

Publisherrohitg00
Repositoryawesome-claude-code-toolkit
Skill namedocker-best-practices
Stars
2.6K
Forks
963
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by rohitg00 on GitHub. Read the source before you install it.

Installation

Install the Docker Best Practices AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/rohitg00/awesome-claude-code-toolkit.git /tmp/awesome-claude-code-toolkit
mkdir -p .claude/skills
cp -r /tmp/awesome-claude-code-toolkit/skills/docker-best-practices .claude/skills/docker-best-practices
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Docker Best Practices in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Docker Best Practices on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Docker Best Practices is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Docker Best Practices

Multi-Stage Build

dockerfile
FROM node:22-alpine AS deps
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm ci --only=production

FROM node:22-alpine AS build
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm ci
COPY . .
RUN npm run build

FROM node:22-alpine AS runtime
WORKDIR /app
RUN addgroup -g 1001 -S appgroup && adduser -S appuser -u 1001 -G appgroup
COPY --from=deps /app/node_modules ./node_modules
COPY --from=build /app/dist ./dist
COPY --from=build /app/package.json ./
USER appuser
EXPOSE 3000
HEALTHCHECK --interval=30s --timeout=3s CMD wget -qO- http://localhost:3000/healthz || exit 1
CMD ["node", "dist/server.js"]

Separate dependency installation from build steps. Final stage contains only runtime artifacts.

Python Multi-Stage

dockerfile
FROM python:3.12-slim AS builder
WORKDIR /app
RUN python -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

FROM python:3.12-slim
WORKDIR /app
RUN useradd --create-home appuser
COPY --from=builder /opt/venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"
COPY . .
USER appuser
CMD ["gunicorn", "app:create_app()", "-b", "0.0.0.0:8000", "-w", "4"]

Docker Compose

yaml
services:
  api:
    build:
      context: .
      dockerfile: Dockerfile
      target: runtime
    ports:
      - "3000:3000"
    environment:
      - DATABASE_URL=postgres://user:pass@db:5432/app
      - REDIS_URL=redis://cache:6379
    depends_on:
      db:
        condition: service_healthy
      cache:
        condition: service_started
    restart: unless-stopped
    deploy:
      resources:
        limits:
          memory: 512M

  db:
    image: postgres:16-alpine
    volumes:
      - pgdata:/var/lib/postgresql/data
    environment:
      POSTGRES_DB: app
      POSTGRES_USER: user
      POSTGRES_PASSWORD: pass
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U user -d app"]
      interval: 5s
      timeout: 3s
      retries: 5

  cache:
    image: redis:7-alpine
    command: redis-server --maxmemory 128mb --maxmemory-policy allkeys-lru

volumes:
  pgdata:

.dockerignore

node_modules
.git
.env*
*.md
docker-compose*.yml
.github
coverage
dist

Always include a .dockerignore to reduce build context size and prevent leaking secrets.

Image Optimization Tips

bash
# Check image size breakdown
docker history --human --no-trunc <image>

# Use dive for layer analysis
dive <image>

# Multi-arch build
docker buildx build --platform linux/amd64,linux/arm64 -t registry/app:1.0 --push .

Combine RUN commands to reduce layers. Order instructions from least to most frequently changing for cache efficiency.

Anti-Patterns

  • Running as root inside containers
  • Using ADD when COPY suffices (ADD auto-extracts tarballs, pulls URLs)
  • Storing secrets in environment variables in Dockerfiles
  • Not pinning base image versions (FROM node:latest)
  • Missing .dockerignore causing large build contexts
  • Installing dev dependencies in production images

Checklist

  • Multi-stage build separates build and runtime stages
  • Non-root user created and used with USER directive
  • Base images pinned to specific versions (e.g., node:22-alpine)
  • .dockerignore excludes .git, node_modules, .env
  • HEALTHCHECK instruction defined
  • Production image contains no build tools or dev dependencies
  • docker-compose uses depends_on with health conditions
  • Secrets passed via build secrets or runtime mounts, not ENV in Dockerfile

Frequently asked questions

What does the Docker Best Practices AI skill do?

Docker best practices including multi-stage builds, compose patterns, image optimization, and security

Why use Docker Best Practices on TypingMind?

Because you install it once and use it with any model. Docker Best Practices is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Docker Best Practices in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rohitg00/awesome-claude-code-toolkit/tree/main/skills/docker-best-practices. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Docker Best Practices?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Docker Best Practices?

As many as you like. As long as a model supports skills, you can use Docker Best Practices with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Docker Best Practices AI skill free?

Yes. It is published on GitHub by rohitg00 under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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