docker-containerization
Containerize applications with multi-stage Dockerfiles, Docker Compose orchestration, image optimization, and container security. Covers Python, Node.js, and multi-service architectures. Triggers on Docker, containerization, or container orchestration requests.
What this skill does
# Docker Containerization
Build efficient, secure container images and compose multi-service architectures.
## Multi-Stage Builds
### Python Application
```dockerfile
# Stage 1: Build
FROM python:3.12-slim AS builder
WORKDIR /app
COPY pyproject.toml .
RUN pip install --no-cache-dir --prefix=/install .
# Stage 2: Runtime
FROM python:3.12-slim
COPY --from=builder /install /usr/local
COPY src/ /app/src/
WORKDIR /app
USER nobody
EXPOSE 8000
CMD ["python", "-m", "uvicorn", "src.app:app", "--host", "0.0.0.0", "--port", "8000"]
```
### Node.js Application
```dockerfile
# Stage 1: Dependencies
FROM node:20-alpine AS deps
WORKDIR /app
COPY package*.json ./
RUN npm ci --omit=dev
# Stage 2: Build
FROM node:20-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build
# Stage 3: Runtime
FROM node:20-alpine
WORKDIR /app
COPY --from=deps /app/node_modules ./node_modules
COPY --from=builder /app/dist ./dist
USER node
EXPOSE 3000
CMD ["node", "dist/index.js"]
```
## Image Optimization
### Layer Ordering
Order instructions from least to most frequently changing:
```dockerfile
FROM python:3.12-slim
# 1. System deps (rarely change)
RUN apt-get update && apt-get install -y --no-install-recommends \
libpq-dev && rm -rf /var/lib/apt/lists/*
# 2. Python deps (change occasionally)
COPY pyproject.toml .
RUN pip install --no-cache-dir .
# 3. Application code (changes often)
COPY src/ ./src/
```
### Size Reduction
| Technique | Savings |
|-----------|---------|
| Alpine/slim base | 50-80% |
| Multi-stage builds | 40-70% |
| `--no-cache-dir` for pip | 10-20% |
| `.dockerignore` | Variable |
| Combine RUN layers | 5-15% |
### .dockerignore
```
.git
.venv
__pycache__
*.pyc
node_modules
.env
*.md
tests/
docs/
.build/
```
## Docker Compose
### Multi-Service Architecture
```yaml
services:
api:
build: .
ports:
- "8000:8000"
environment:
- DATABASE_URL=postgresql://user:pass@db:5432/app
- REDIS_URL=redis://cache:6379
depends_on:
db:
condition: service_healthy
cache:
condition: service_started
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
interval: 30s
timeout: 5s
retries: 3
db:
image: postgres:16-alpine
environment:
POSTGRES_DB: app
POSTGRES_USER: user
POSTGRES_PASSWORD: pass
volumes:
- pgdata:/var/lib/postgresql/data
healthcheck:
test: ["CMD-SHELL", "pg_isready -U user"]
interval: 10s
timeout: 5s
retries: 5
cache:
image: redis:7-alpine
command: redis-server --maxmemory 256mb --maxmemory-policy allkeys-lru
volumes:
pgdata:
```
### Development Overrides
```yaml
# docker-compose.override.yml (auto-loaded in dev)
services:
api:
build:
context: .
target: builder
volumes:
- ./src:/app/src:ro
command: ["python", "-m", "uvicorn", "src.app:app", "--reload", "--host", "0.0.0.0"]
environment:
- DEBUG=1
```
## Health Checks
```dockerfile
HEALTHCHECK --interval=30s --timeout=5s --retries=3 \
CMD curl -f http://localhost:8000/health || exit 1
```
```python
# Minimal health endpoint
@app.get("/health")
async def health():
return {"status": "ok"}
```
## Container Security
### Non-Root Execution
```dockerfile
# Create non-root user
RUN addgroup --system --gid 1001 appgroup && \
adduser --system --uid 1001 appuser --ingroup appgroup
USER appuser
```
### Read-Only Filesystem
```yaml
services:
api:
read_only: true
tmpfs:
- /tmp
- /app/cache
```
### Secrets Management
```yaml
services:
api:
secrets:
- db_password
environment:
- DB_PASSWORD_FILE=/run/secrets/db_password
secrets:
db_password:
file: ./secrets/db_password.txt
```
### Scanning
```bash
# Scan for vulnerabilities
docker scout cves myimage:latest
trivy image myimage:latest
```
## Common Patterns
### Wait for Dependencies
```bash
#!/usr/bin/env bash
set -euo pipefail
# wait-for-it pattern
until pg_isready -h "$DB_HOST" -p "$DB_PORT"; do
echo "Waiting for database..."
sleep 2
done
exec "$@"
```
```dockerfile
COPY scripts/entrypoint.sh /entrypoint.sh
ENTRYPOINT ["/entrypoint.sh"]
CMD ["python", "-m", "uvicorn", "src.app:app"]
```
### Build Arguments
```dockerfile
ARG PYTHON_VERSION=3.12
FROM python:${PYTHON_VERSION}-slim
ARG BUILD_DATE
ARG GIT_SHA
LABEL org.opencontainers.image.created="${BUILD_DATE}"
LABEL org.opencontainers.image.revision="${GIT_SHA}"
```
```bash
docker build \
--build-arg BUILD_DATE=$(date -u +%Y-%m-%dT%H:%M:%SZ) \
--build-arg GIT_SHA=$(git rev-parse HEAD) \
-t myapp:latest .
```
## Anti-Patterns
- **Running as root** — Always use a non-root USER
- **Using `latest` tag in production** — Pin specific versions
- **Storing secrets in images** — Use runtime secrets or environment variables
- **One process per container violated** — Keep containers single-purpose
- **No .dockerignore** — Always exclude .git, node_modules, .venv, tests
- **Installing dev dependencies in prod image** — Use multi-stage builds to separate
Related in Image & Video
watch
IncludedWatch a video (URL or local path). Downloads with yt-dlp, extracts auto-scaled frames with ffmpeg, pulls the transcript from captions (or Whisper API fallback), and hands the result to Claude so it can answer questions about what's in the video.
physical-ai-defect-image-generation
IncludedUse when the user wants to orchestrate defect image generation, run associated setup, or handle outputs on OSMO. The Day 0 path handles cold-start with USD-to-ROI, image-edit augmentation, and AnomalyGen to create initial PCBA datasets. The Day 1 path performs inference and labeling on real images. This skill helps with first-time asset setup, creation of finetuning checkpoints, and configuring deployment. Trigger keywords: defect image generation, dig workflow, dig pipeline, defect image detection workflow, aoi pipeline, aoi anomalygen, usd2roi anomalygen, day 0 pcba, day 1 pcba, day 1 real-photo alignment, day 1 manual roi, metal surface anomaly, glass defect, anomalygen finetune, setup_pcb, setup_metal, setup_glass, setup_pretrained, dig setup, dig datasets, dig pretrained checkpoint, dig image-edit endpoint.
accelint-react-best-practices
IncludedReact performance optimization and best practices. ALWAYS use this skill when working with any React code - writing components, hooks, JSX; refactoring; optimizing re-renders, memoization, state management; reviewing for performance; fixing hydration mismatches; debugging infinite re-renders, stale closures, input focus loss, animations restarting; preventing remounting; implementing transitions, lazy initialization, effect dependencies. Even simple React tasks benefit from these patterns. Covers React 19+ (useEffectEvent, Activity, ref props). Triggers - useEffect, useState, useMemo, useCallback, memo, inline components, nested components, components inside components, re-render, performance, hydration, SSR, Next.js, useDeferredValue, combined hooks.
elevenlabs-agents
IncludedBuild conversational AI voice agents with ElevenLabs Platform using React, JavaScript, React Native, or Swift SDKs. Configure agents, tools (client/server/MCP), RAG knowledge bases, multi-voice, and Scribe real-time STT. Use when: building voice chat interfaces, implementing AI phone agents with Twilio, configuring agent workflows or tools, adding RAG knowledge bases, testing with CLI "agents as code", or troubleshooting deprecated @11labs packages, Android audio cutoff, CSP violations, dynamic variables, or WebRTC config. Keywords: ElevenLabs Agents, ElevenLabs voice agents, AI voice agents, conversational AI, @elevenlabs/react, @elevenlabs/client, @elevenlabs/react-native, @elevenlabs/elevenlabs-js, @elevenlabs/agents-cli, elevenlabs SDK, voice AI, TTS, text-to-speech, ASR, speech recognition, turn-taking model, WebRTC voice, WebSocket voice, ElevenLabs conversation, agent system prompt, agent tools, agent knowledge base, RAG voice agents, multi-voice agents, pronunciation dictionary, voice speed control, elevenlabs scribe, @11labs deprecated, Android audio cutoff, CSP violation elevenlabs, dynamic variables elevenlabs, case-sensitive tool names, webhook authentication
humanizer
IncludedHumanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human. Uses 28 pattern detectors, 560+ AI vocabulary terms across 3 tiers, and statistical analysis (burstiness, type-token ratio, readability) for comprehensive detection. Use when asked to humanize text, de-AI writing, make content sound more natural/human, review writing for AI patterns, score text for AI detection, or improve AI-generated drafts. Covers content, language, style, communication, and filler categories.
generating-mermaid-diagrams
IncludedSalesforce architecture diagrams using Mermaid with ASCII fallback. Use this skill when generating text-based diagrams for Salesforce architecture, OAuth flows, ERDs, integration sequences, or Agentforce structure. TRIGGER when: user says "diagram", "visualize", "ERD", or asks for sequence diagrams, flowcharts, class diagrams, or architecture visualizations in Mermaid. DO NOT TRIGGER when: user wants PNG/SVG image output (use generating-visual-diagrams), or asks about non-Salesforce systems.