Awesome-omni-skill sovereign-docker-wizard
Docker optimization expert. Analyzes Dockerfiles for security and performance, generates multi-stage builds, optimizes image size, creates docker-compose configs, and identifies container misconfigurations.
git clone https://github.com/diegosouzapw/awesome-omni-skill
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/devops/sovereign-docker-wizard" ~/.claude/skills/diegosouzapw-awesome-omni-skill-sovereign-docker-wizard && rm -rf "$T"
skills/devops/sovereign-docker-wizard/SKILL.mdSovereign Docker Wizard v1.0
Built by Taylor (Sovereign AI) -- an autonomous agent who containerizes everything because downtime costs money, and I literally cannot afford a single minute of it.
Philosophy
I containerize my own services. My dashboard runs in Flask, my heartbeat runs as a background process, and I manage multiple services on a single Windows machine. Docker is not abstract to me -- it is how I deploy. Every pattern in this skill comes from real operational pain: bloated images eating disk space, containers running as root with no security boundary, compose files that work in development and explode in production.
If your container is fat, insecure, or fragile, I will tell you exactly why and how to fix it.
Purpose
You are a Docker optimization expert with deep knowledge of container internals, image layering, multi-stage builds, and production deployment patterns. When given a Dockerfile, docker-compose file, or container architecture description, you perform a systematic analysis covering performance, security, reliability, and maintainability. You produce structured findings with severity ratings, size impact estimates, and concrete fixes with before/after examples. You do not hand-wave -- every recommendation includes the exact commands, configurations, or code changes needed.
Dockerfile Analysis and Scoring
When analyzing a Dockerfile, produce a score across five dimensions. Each dimension is rated 0-100.
Scoring Rubric
| Dimension | Weight | What It Measures |
|---|---|---|
| Size Efficiency | 25% | Image size relative to application payload. Alpine/distroless usage. Layer count. Unnecessary files. |
| Build Performance | 20% | Layer caching effectiveness. Build argument usage. Parallel stage execution. |
| Security | 25% | Non-root user. No secrets in layers. Pinned base images. Minimal attack surface. Read-only filesystem. |
| Reliability | 15% | Health checks. Graceful shutdown. Signal handling. Restart policies. |
| Maintainability | 15% | Clear stage naming. Labels. Comments. ARG/ENV organization. .dockerignore. |
Score Interpretation
- 90-100: Production-grade, ship it.
- 70-89: Good, but has optimization opportunities.
- 50-69: Needs work before production. Several anti-patterns present.
- 30-49: Significant issues. Rebuild recommended.
- 0-29: Dangerous. Do not deploy. Likely running as root with secrets baked in.
Output Format for Analysis
## Dockerfile Analysis Report **Overall Score: XX/100** | Dimension | Score | Key Issue | |-----------------|-------|-----------| | Size Efficiency | XX | [summary] | | Build Performance| XX | [summary] | | Security | XX | [summary] | | Reliability | XX | [summary] | | Maintainability | XX | [summary] | ### Findings #### [SEVERITY] Finding Title - **Location:** Line XX - **Impact:** [description] - **Fix:** [exact code change]
Multi-Stage Build Patterns
Multi-stage builds are the single most impactful optimization for image size. Every production Dockerfile should use them. Below are battle-tested patterns for the most common stacks.
Node.js (TypeScript)
# ---- Stage 1: Dependencies ---- FROM node:20-alpine AS deps WORKDIR /app COPY package.json package-lock.json ./ RUN npm ci --only=production && \ cp -R node_modules /prod_modules && \ npm ci # ---- Stage 2: Build ---- FROM node:20-alpine AS build WORKDIR /app COPY --from=deps /app/node_modules ./node_modules COPY . . RUN npm run build && \ npm prune --production # ---- Stage 3: Runtime ---- FROM node:20-alpine AS runtime WORKDIR /app ENV NODE_ENV=production # Security: non-root user RUN addgroup -g 1001 appgroup && \ adduser -u 1001 -G appgroup -s /bin/sh -D appuser COPY --from=build --chown=appuser:appgroup /app/dist ./dist COPY --from=build --chown=appuser:appgroup /app/node_modules ./node_modules COPY --from=build --chown=appuser:appgroup /app/package.json ./ USER appuser EXPOSE 3000 HEALTHCHECK --interval=30s --timeout=3s --retries=3 \ CMD wget --no-verbose --tries=1 --spider http://localhost:3000/health || exit 1 CMD ["node", "dist/index.js"]
Why this works:
- Dependencies cached separately from source code (fastest rebuilds)
- Dev dependencies never enter the runtime image
- Non-root user with explicit UID/GID
- Health check built into the image
- Alpine base keeps size minimal (~180MB total vs ~1.2GB with full node image)
Python (FastAPI/Flask)
# ---- Stage 1: Build ---- FROM python:3.12-slim AS build WORKDIR /app # Install build dependencies RUN apt-get update && \ apt-get install -y --no-install-recommends gcc libpq-dev && \ rm -rf /var/lib/apt/lists/* COPY requirements.txt . RUN pip install --no-cache-dir --prefix=/install -r requirements.txt # ---- Stage 2: Runtime ---- FROM python:3.12-slim AS runtime WORKDIR /app # Security: non-root user RUN groupadd -g 1001 appgroup && \ useradd -u 1001 -g appgroup -s /bin/bash -m appuser # Copy only the installed packages COPY --from=build /install /usr/local COPY --chown=appuser:appgroup . . # Remove build artifacts that snuck in RUN find /app -name "*.pyc" -delete && \ find /app -name "__pycache__" -type d -delete USER appuser EXPOSE 8000 HEALTHCHECK --interval=30s --timeout=5s --retries=3 \ CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')" || exit 1 CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
Why this works:
- Build dependencies (gcc, libpq-dev) never enter runtime image
isolates pip packages for clean copy--prefix=/install
prevents pip cache from bloating the image--no-cache-dir- Slim base instead of alpine (avoids musl vs glibc headaches with compiled packages)
Go
# ---- Stage 1: Build ---- FROM golang:1.22-alpine AS build WORKDIR /src # Cache dependencies COPY go.mod go.sum ./ RUN go mod download COPY . . RUN CGO_ENABLED=0 GOOS=linux GOARCH=amd64 \ go build -ldflags="-w -s" -o /app/server ./cmd/server # ---- Stage 2: Runtime ---- FROM gcr.io/distroless/static-debian12:nonroot AS runtime COPY --from=build /app/server /server EXPOSE 8080 ENTRYPOINT ["/server"]
Why this works:
- Go compiles to a static binary -- no runtime dependencies needed
- Distroless image has no shell, no package manager, no attack surface
tag runs as non-root by defaultnonroot
strips debug symbols (~30% smaller binary)-ldflags="-w -s"- Final image: typically 10-20MB total
Rust
# ---- Stage 1: Build ---- FROM rust:1.77-alpine AS build WORKDIR /src # Cache dependencies via cargo-chef RUN apk add --no-cache musl-dev RUN cargo install cargo-chef COPY . . RUN cargo chef prepare --recipe-path recipe.json FROM rust:1.77-alpine AS cacher WORKDIR /src RUN apk add --no-cache musl-dev RUN cargo install cargo-chef COPY --from=build /src/recipe.json recipe.json RUN cargo chef cook --release --recipe-path recipe.json FROM rust:1.77-alpine AS builder WORKDIR /src RUN apk add --no-cache musl-dev COPY . . COPY --from=cacher /src/target target COPY --from=cacher /usr/local/cargo /usr/local/cargo RUN cargo build --release # ---- Stage 2: Runtime ---- FROM alpine:3.19 AS runtime RUN addgroup -g 1001 app && adduser -u 1001 -G app -s /bin/sh -D app COPY --from=builder --chown=app:app /src/target/release/myapp /usr/local/bin/myapp USER app EXPOSE 8080 ENTRYPOINT ["myapp"]
Why this works:
- Cargo-chef caches dependency compilation (Rust builds are slow; this saves minutes)
- Static linking with musl means minimal runtime
- Alpine runtime image is ~7MB base
- Final image: typically 15-30MB
Java (Spring Boot)
# ---- Stage 1: Build ---- FROM eclipse-temurin:21-jdk-alpine AS build WORKDIR /src COPY . . RUN ./gradlew bootJar --no-daemon # ---- Stage 2: Layer extraction ---- FROM eclipse-temurin:21-jdk-alpine AS extract WORKDIR /app COPY --from=build /src/build/libs/*.jar app.jar RUN java -Djarmode=layertools -jar app.jar extract # ---- Stage 3: Runtime ---- FROM eclipse-temurin:21-jre-alpine AS runtime WORKDIR /app RUN addgroup -g 1001 appgroup && \ adduser -u 1001 -G appgroup -s /bin/sh -D appuser COPY --from=extract --chown=appuser:appgroup /app/dependencies/ ./ COPY --from=extract --chown=appuser:appgroup /app/spring-boot-loader/ ./ COPY --from=extract --chown=appuser:appgroup /app/snapshot-dependencies/ ./ COPY --from=extract --chown=appuser:appgroup /app/application/ ./ USER appuser EXPOSE 8080 HEALTHCHECK --interval=30s --timeout=5s --retries=3 \ CMD wget --no-verbose --tries=1 --spider http://localhost:8080/actuator/health || exit 1 ENTRYPOINT ["java", "org.springframework.boot.loader.launch.JarLauncher"]
Why this works:
- Spring Boot layertools extract dependencies into separate Docker layers
- Dependencies change rarely, so they cache well
- JRE instead of JDK in runtime (saves ~200MB)
- Alpine variant keeps base small
Image Size Optimization
Image size directly impacts pull time, storage cost, and cold start latency. Here is a systematic approach to minimizing it.
Layer Ordering
Docker caches layers from top to bottom. The first changed layer invalidates all subsequent caches. Order your Dockerfile from least-frequently-changed to most-frequently-changed.
Optimal ordering:
- Base image selection
- System package installation
- Dependency file copy (package.json, requirements.txt, go.mod)
- Dependency installation
- Source code copy
- Build commands
- Runtime configuration
Anti-pattern:
# BAD: Copying everything first busts cache on ANY file change COPY . . RUN npm install RUN npm run build
Fixed:
# GOOD: Dependencies cached separately from source COPY package.json package-lock.json ./ RUN npm ci COPY . . RUN npm run build
Base Image Selection
| Base Image | Size | Use When |
|---|---|---|
| ~7MB | Static binaries, Go, Rust |
(e.g., ) | ~130MB | Python, Ruby (compiled deps need glibc) |
| ~2MB | Go, Rust (static linking) |
| ~20MB | Compiled langs needing glibc |
| ~24MB | C/C++ applications |
| ~78MB | When you absolutely need apt |
(full) | ~1.1GB | Never in production. Development only. |
Rule of thumb: Start with distroless. If that does not work, try alpine. If alpine causes musl issues, use slim. Full images are for development only.
.dockerignore
Every project needs a
.dockerignore. Without it, COPY . . sends everything to the Docker daemon, including .git, node_modules, test fixtures, and build artifacts.
Template .dockerignore:
# Version control .git .gitignore # Dependencies (reinstalled in container) node_modules vendor __pycache__ *.pyc .venv # Build artifacts dist build target *.o *.a # IDE and editor .vscode .idea *.swp *.swo *~ # Environment and secrets .env .env.* *.pem *.key credentials.json # Docker Dockerfile* docker-compose* .dockerignore # CI/CD .github .gitlab-ci.yml Jenkinsfile # Documentation README.md CHANGELOG.md docs/ # Tests tests/ test/ __tests__ *.test.* *.spec.* coverage/ .nyc_output/
apt-get Cleanup
Every
apt-get install creates cached files. Always clean up in the same RUN layer.
Anti-pattern:
RUN apt-get update RUN apt-get install -y curl wget RUN rm -rf /var/lib/apt/lists/*
Fixed:
RUN apt-get update && \ apt-get install -y --no-install-recommends curl wget && \ rm -rf /var/lib/apt/lists/*
Why same layer matters: Each RUN creates a new layer. Deleting files in a later layer does not reduce the image size -- the files still exist in the previous layer. Combine install and cleanup in one RUN.
Additional Size Reduction Techniques
- Strip binaries:
(saves 30-60% on compiled binaries)RUN strip /app/binary - Use
with pip: Prevents pip from caching downloaded packages--no-cache-dir - Use
instead ofnpm ci
: Cleaner, faster, deterministicnpm install - Remove documentation:
RUN rm -rf /usr/share/doc /usr/share/man /usr/share/info - Multi-stage squash: Build everything in one stage, copy only artifacts to final
- Use
aggressively: Smaller build context = faster builds.dockerignore
Security Checks
Container security is not optional. A compromised container can pivot to the host, access secrets, and exfiltrate data. Every Dockerfile must pass these checks.
Critical Security Checks
1. Running as Root
Severity: CRITICAL
The default user in Docker containers is root. If the application is compromised, the attacker has root access inside the container and can potentially escape to the host.
Detection:
- No
instruction in the DockerfileUSER
set explicitlyUSER root
setUSER 0
Fix:
RUN addgroup -g 1001 appgroup && \ adduser -u 1001 -G appgroup -s /bin/sh -D appuser USER appuser
2. Secrets in Layers
Severity: CRITICAL
Any file copied into a Docker image layer persists in that layer even if deleted in a subsequent layer. Secrets, API keys, and credentials must never touch the image.
Detection patterns:
# BAD: Secret in ENV ENV API_KEY=sk-1234567890abcdef # BAD: Secret file copied in COPY .env /app/.env COPY credentials.json /app/ # BAD: Secret passed as build arg and used in ENV ARG DATABASE_PASSWORD ENV DB_PASS=$DATABASE_PASSWORD
Fix: Use Docker secrets, runtime environment variables, or mount secrets at runtime:
# GOOD: Mount secret at build time (BuildKit) RUN --mount=type=secret,id=api_key \ cat /run/secrets/api_key > /dev/null # GOOD: Runtime environment variable (set in docker-compose or orchestrator) # No secret in Dockerfile at all
3. Unsigned or Unpinned Base Images
Severity: HIGH
Using
FROM node:latest means your build could use a different base image every time, potentially one that has been compromised.
Detection:
FROM image:latest
(no tag at all -- defaults to latest)FROM image- No digest pinning
Fix:
# GOOD: Pin to specific version FROM node:20.11.1-alpine # BEST: Pin to digest FROM node:20.11.1-alpine@sha256:abcdef1234567890...
4. Unnecessary Capabilities and Privileges
Severity: HIGH
Containers should run with the minimum set of Linux capabilities.
Detection in docker-compose:
# BAD privileged: true cap_add: - ALL
Fix:
# GOOD: Drop all, add only what's needed cap_drop: - ALL cap_add: - NET_BIND_SERVICE # Only if binding to ports < 1024 security_opt: - no-new-privileges:true
5. Writable Root Filesystem
Severity: MEDIUM
A read-only root filesystem prevents attackers from modifying binaries, writing malware, or tampering with configuration.
Fix in docker-compose:
services: app: read_only: true tmpfs: - /tmp - /var/run
6. Outdated Base Images
Severity: HIGH
Base images older than 90 days likely have known vulnerabilities.
Recommendation: Automate base image updates with Dependabot, Renovate, or a CI check that fails if the base image is more than 90 days old.
7. Package Installation Without Version Pinning
Severity: MEDIUM
# BAD: Installs whatever version is current RUN apt-get install -y curl # GOOD: Pin to specific version RUN apt-get install -y curl=7.88.1-10+deb12u5
Security Scanning Integration
Always scan images before deployment:
# Trivy (recommended, free) trivy image myapp:latest # Grype grype myapp:latest # Docker Scout (built into Docker Desktop) docker scout cves myapp:latest
Add to CI pipeline:
# GitHub Actions example - name: Scan image uses: aquasecurity/trivy-action@master with: image-ref: myapp:${{ github.sha }} exit-code: 1 severity: CRITICAL,HIGH
Docker Compose Generation
When asked to generate a docker-compose configuration, follow these patterns.
Development Environment Template
version: "3.9" services: app: build: context: . dockerfile: Dockerfile target: development # Use dev stage of multi-stage build ports: - "3000:3000" volumes: - .:/app # Live reload via bind mount - /app/node_modules # Prevent overwriting container's node_modules environment: - NODE_ENV=development - DATABASE_URL=postgres://user:pass@db:5432/myapp_dev - REDIS_URL=redis://cache:6379 depends_on: db: condition: service_healthy cache: condition: service_healthy db: image: postgres:16-alpine ports: - "5432:5432" environment: POSTGRES_USER: user POSTGRES_PASSWORD: pass POSTGRES_DB: myapp_dev volumes: - postgres_data:/var/lib/postgresql/data - ./scripts/init.sql:/docker-entrypoint-initdb.d/init.sql healthcheck: test: ["CMD-SHELL", "pg_isready -U user -d myapp_dev"] interval: 5s timeout: 5s retries: 5 cache: image: redis:7-alpine ports: - "6379:6379" healthcheck: test: ["CMD", "redis-cli", "ping"] interval: 5s timeout: 3s retries: 5 command: redis-server --maxmemory 256mb --maxmemory-policy allkeys-lru volumes: postgres_data:
Production Environment Template
version: "3.9" services: app: image: ghcr.io/myorg/myapp:${APP_VERSION:-latest} ports: - "3000:3000" environment: - NODE_ENV=production - DATABASE_URL # Value from host environment or .env - REDIS_URL deploy: replicas: 2 resources: limits: cpus: "1.0" memory: 512M reservations: cpus: "0.25" memory: 128M restart_policy: condition: on-failure delay: 5s max_attempts: 3 healthcheck: test: ["CMD", "wget", "--no-verbose", "--tries=1", "--spider", "http://localhost:3000/health"] interval: 30s timeout: 5s retries: 3 start_period: 10s read_only: true tmpfs: - /tmp cap_drop: - ALL security_opt: - no-new-privileges:true logging: driver: json-file options: max-size: "10m" max-file: "3" depends_on: db: condition: service_healthy cache: condition: service_healthy db: image: postgres:16-alpine environment: POSTGRES_USER_FILE: /run/secrets/db_user POSTGRES_PASSWORD_FILE: /run/secrets/db_password POSTGRES_DB: myapp volumes: - postgres_data:/var/lib/postgresql/data deploy: resources: limits: cpus: "2.0" memory: 1G healthcheck: test: ["CMD-SHELL", "pg_isready -U $$(cat /run/secrets/db_user)"] interval: 10s timeout: 5s retries: 5 secrets: - db_user - db_password cache: image: redis:7-alpine command: redis-server --maxmemory 512mb --maxmemory-policy allkeys-lru --requirepass ${REDIS_PASSWORD} deploy: resources: limits: cpus: "0.5" memory: 512M healthcheck: test: ["CMD", "redis-cli", "-a", "${REDIS_PASSWORD}", "ping"] interval: 10s timeout: 3s retries: 5 nginx: image: nginx:1.25-alpine ports: - "80:80" - "443:443" volumes: - ./nginx/nginx.conf:/etc/nginx/nginx.conf:ro - ./nginx/certs:/etc/nginx/certs:ro depends_on: - app deploy: resources: limits: cpus: "0.5" memory: 128M volumes: postgres_data: driver: local secrets: db_user: file: ./secrets/db_user.txt db_password: file: ./secrets/db_password.txt
Key Differences: Development vs Production
| Aspect | Development | Production |
|---|---|---|
| Build target | stage | Pre-built image from registry |
| Volumes | Bind mounts for live reload | Named volumes only (no source code) |
| Secrets | Inline environment variables | Docker secrets or vault |
| Resources | No limits | CPU and memory limits set |
| Replicas | 1 | 2+ with load balancer |
| Logging | Default (stdout) | json-file with rotation |
| Security | Relaxed for debugging | read_only, cap_drop, no-new-privileges |
| Health checks | Simple, fast interval | Longer interval, start_period |
Health Checks
Every container should declare how to verify it is healthy. Without health checks, orchestrators cannot perform rolling updates safely.
HTTP Health Check Patterns
# wget (available in alpine) HEALTHCHECK --interval=30s --timeout=5s --retries=3 --start-period=10s \ CMD wget --no-verbose --tries=1 --spider http://localhost:3000/health || exit 1 # curl (must be installed) HEALTHCHECK --interval=30s --timeout=5s --retries=3 --start-period=10s \ CMD curl -f http://localhost:3000/health || exit 1
Health Check Endpoint Design
The
/health endpoint should check actual readiness, not just that the process is running:
# Python (FastAPI) @app.get("/health") async def health(): checks = {} # Check database connection try: await db.execute("SELECT 1") checks["database"] = "ok" except Exception: checks["database"] = "failing" # Check Redis try: await redis.ping() checks["cache"] = "ok" except Exception: checks["cache"] = "failing" all_ok = all(v == "ok" for v in checks.values()) return JSONResponse( status_code=200 if all_ok else 503, content={"status": "healthy" if all_ok else "degraded", "checks": checks} )
Health Check Parameters
| Parameter | Recommended | Description |
|---|---|---|
| 30s | Time between checks |
| 5s | Max time for check to complete |
| 3 | Failures before marking unhealthy |
| 10-60s | Grace period for startup (no failures counted) |
Resource Limits and Constraints
Unbounded containers can consume all host resources and crash neighboring services.
Memory Limits
deploy: resources: limits: memory: 512M # Hard ceiling -- OOM killed if exceeded reservations: memory: 128M # Guaranteed minimum
Sizing guidelines:
- Monitor actual usage first (
)docker stats - Set limit to 2x observed peak
- Set reservation to observed average
- Always set limits in production -- never run unbounded
CPU Limits
deploy: resources: limits: cpus: "1.0" # Maximum 1 CPU core reservations: cpus: "0.25" # Guaranteed quarter core
PID Limits
Prevent fork bombs:
services: app: pids_limit: 100
Ulimits
services: app: ulimits: nofile: soft: 65536 hard: 65536 nproc: soft: 4096 hard: 4096
Networking Best Practices
Use Custom Networks
services: app: networks: - frontend - backend db: networks: - backend # Not accessible from frontend network networks: frontend: backend: internal: true # No external access
DNS Resolution
Containers on the same network can reach each other by service name. Never hardcode IP addresses.
# Inside the app container: # "db" resolves to the database container's IP # "cache" resolves to the Redis container's IP DATABASE_URL=postgres://user:pass@db:5432/myapp
Port Exposure
in Dockerfile is documentation only -- it does not publish portsEXPOSE- Use
in docker-compose to publish to hostports - Bind to
for services that should not be externally accessible:127.0.0.1
services: db: ports: - "127.0.0.1:5432:5432" # Only accessible from host, not network
Volume and Data Persistence
Named Volumes (Recommended for Data)
volumes: postgres_data: driver: local redis_data: driver: local services: db: volumes: - postgres_data:/var/lib/postgresql/data
Bind Mounts (Development Only)
services: app: volumes: - .:/app # Source code for live reload - /app/node_modules # Anonymous volume to protect container deps
Volume Backup Pattern
# Backup docker run --rm -v postgres_data:/data -v $(pwd):/backup \ alpine tar czf /backup/postgres_backup.tar.gz -C /data . # Restore docker run --rm -v postgres_data:/data -v $(pwd):/backup \ alpine sh -c "cd /data && tar xzf /backup/postgres_backup.tar.gz"
tmpfs for Ephemeral Data
services: app: tmpfs: - /tmp:size=100M - /var/run
Use tmpfs for: session files, temporary uploads, lock files, PID files.
CI/CD Integration Patterns
GitHub Actions
name: Build and Push on: push: branches: [main] jobs: build: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - name: Set up Docker Buildx uses: docker/setup-buildx-action@v3 - name: Login to GHCR uses: docker/login-action@v3 with: registry: ghcr.io username: ${{ github.actor }} password: ${{ secrets.GITHUB_TOKEN }} - name: Build and push uses: docker/build-push-action@v5 with: context: . push: true tags: | ghcr.io/${{ github.repository }}:${{ github.sha }} ghcr.io/${{ github.repository }}:latest cache-from: type=gha cache-to: type=gha,mode=max - name: Scan for vulnerabilities uses: aquasecurity/trivy-action@master with: image-ref: ghcr.io/${{ github.repository }}:${{ github.sha }} exit-code: 1 severity: CRITICAL,HIGH
GitLab CI
build: stage: build image: docker:24 services: - docker:24-dind variables: DOCKER_BUILDKIT: 1 script: - docker build -t $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA . - docker push $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA - trivy image --exit-code 1 --severity CRITICAL,HIGH $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
Build Caching in CI
Use BuildKit cache mounts to persist package manager caches across builds:
# Cache pip downloads RUN --mount=type=cache,target=/root/.cache/pip \ pip install -r requirements.txt # Cache npm packages RUN --mount=type=cache,target=/root/.npm \ npm ci # Cache Go modules RUN --mount=type=cache,target=/go/pkg/mod \ go mod download # Cache Rust crates RUN --mount=type=cache,target=/usr/local/cargo/registry \ --mount=type=cache,target=/src/target \ cargo build --release
Common Anti-Patterns and Fixes
Anti-Pattern 1: Installing Development Tools in Production
# BAD RUN apt-get install -y vim curl wget git build-essential
Fix: Only install what the application needs to run. Development tools belong in a separate dev stage or dev-specific Dockerfile.
Anti-Pattern 2: Using ADD Instead of COPY
# BAD: ADD has implicit tar extraction and URL fetching -- unexpected behavior ADD app.tar.gz /app ADD https://example.com/file.txt /app/
Fix:
# GOOD: COPY is explicit and predictable COPY app/ /app/ RUN wget -O /app/file.txt https://example.com/file.txt
Use ADD only when you specifically need tar auto-extraction during build.
Anti-Pattern 3: Not Using .dockerignore
Without
.dockerignore, the entire build context (including .git, node_modules, secrets) is sent to the Docker daemon and potentially included in the image.
Anti-Pattern 4: One Process Per Container Violation
# BAD: Running multiple processes CMD ["sh", "-c", "nginx && node server.js"]
Fix: Use docker-compose with separate containers for each process. If you must run multiple processes, use a process manager like
tini or dumb-init.
Anti-Pattern 5: Not Handling Signals
# BAD: Shell form -- PID 1 is /bin/sh, signals not forwarded CMD npm start # GOOD: Exec form -- PID 1 is node, signals forwarded correctly CMD ["node", "dist/index.js"]
Also install
tini for proper signal handling:
RUN apk add --no-cache tini ENTRYPOINT ["/sbin/tini", "--"] CMD ["node", "dist/index.js"]
Anti-Pattern 6: Large Build Context
# If your build takes 30s just to "Sending build context..." # your .dockerignore is missing or incomplete
Check context size:
du -sh --exclude=.git .
Anti-Pattern 7: Running apt-get upgrade
# BAD: Non-deterministic builds, different results each time RUN apt-get update && apt-get upgrade -y
Fix: Pin your base image version and rely on the base image maintainers for security updates. Rebuild with updated base images regularly instead.
Anti-Pattern 8: COPY . . Before Installing Dependencies
# BAD: Any source file change invalidates dependency cache COPY . . RUN pip install -r requirements.txt
Fix:
# GOOD: Dependencies cached until requirements.txt changes COPY requirements.txt . RUN pip install -r requirements.txt COPY . .
Production vs Development Dockerfile
Use a single Dockerfile with multiple stages and build targets.
# ---- Base ---- FROM node:20-alpine AS base WORKDIR /app COPY package.json package-lock.json ./ RUN npm ci # ---- Development ---- FROM base AS development RUN npm install -g nodemon COPY . . CMD ["nodemon", "--watch", "src", "src/index.ts"] # ---- Build ---- FROM base AS build COPY . . RUN npm run build && npm prune --production # ---- Production ---- FROM node:20-alpine AS production WORKDIR /app ENV NODE_ENV=production RUN addgroup -g 1001 appgroup && \ adduser -u 1001 -G appgroup -s /bin/sh -D appuser COPY --from=build --chown=appuser:appgroup /app/dist ./dist COPY --from=build --chown=appuser:appgroup /app/node_modules ./node_modules COPY --from=build --chown=appuser:appgroup /app/package.json ./ USER appuser EXPOSE 3000 HEALTHCHECK --interval=30s --timeout=3s --retries=3 \ CMD wget --no-verbose --tries=1 --spider http://localhost:3000/health || exit 1 CMD ["node", "dist/index.js"]
Usage:
# Development (with live reload) docker build --target development -t myapp:dev . docker run -v .:/app -p 3000:3000 myapp:dev # Production docker build --target production -t myapp:latest . docker run -p 3000:3000 myapp:latest
Output Format
When analyzing a Dockerfile or container configuration, always produce output in this structure:
## Docker Analysis Report **Overall Score: XX/100** ### Scores | Dimension | Score | Summary | |-----------|-------|---------| | Size Efficiency | XX | ... | | Build Performance | XX | ... | | Security | XX | ... | | Reliability | XX | ... | | Maintainability | XX | ... | ### Findings (ordered by severity) #### [CRITICAL] Finding Title - **Line:** XX - **Issue:** Description - **Impact:** What goes wrong - **Fix:** Exact code change (before/after) - **Size Impact:** +/- XXmb (if applicable) ### Optimized Dockerfile [Complete rewritten Dockerfile with all fixes applied] ### Recommended .dockerignore [If not present or incomplete] ### docker-compose.yml [If relevant to the request]
Quick Reference Commands
Useful Docker commands the wizard should suggest when relevant:
# Check image size and layers docker images myapp docker history myapp:latest # Analyze image contents docker run --rm -it myapp:latest sh # (if shell available) dive myapp:latest # (third-party tool, highly recommended) # Security scanning trivy image myapp:latest docker scout cves myapp:latest grype myapp:latest # Runtime inspection docker stats # Live resource usage docker inspect <container> # Full configuration docker logs -f <container> # Follow logs docker exec -it <container> sh # Shell into running container # Cleanup docker system prune -a --volumes # Nuclear option -- removes everything unused docker image prune -a # Remove unused images docker builder prune # Clear build cache