DevOps Skill

Comprehensive guide for deploying and managing cloud infrastructure across Cloudflare edge platform, Docker containerization, and Google Cloud Platform.

When to Use This Skill

Use this skill when:

• •Deploying serverless applications to Cloudflare Workers
• •Containerizing applications with Docker
• •Managing Google Cloud infrastructure with gcloud CLI
• •Setting up CI/CD pipelines across platforms
• •Optimizing cloud infrastructure costs
• •Implementing multi-region deployments
• •Building edge-first architectures
• •Managing container orchestration with Kubernetes
• •Configuring cloud storage solutions (R2, Cloud Storage)
• •Automating infrastructure with scripts and IaC

Platform Selection Guide

When to Use Cloudflare

Best For:

• •Edge-first applications with global distribution
• •Ultra-low latency requirements (<50ms)
• •Static sites with serverless functions
• •Zero egress cost scenarios (R2 storage)
• •WebSocket/real-time applications (Durable Objects)
• •AI/ML at the edge (Workers AI)

Key Products:

• •Workers (serverless functions)
• •R2 (object storage, S3-compatible)
• •D1 (SQLite database with global replication)
• •KV (key-value store)
• •Pages (static hosting + functions)
• •Durable Objects (stateful compute)
• •Browser Rendering (headless browser automation)

Cost Profile: Pay-per-request, generous free tier, zero egress fees

When to Use Docker

Best For:

• •Local development consistency
• •Microservices architectures
• •Multi-language stack applications
• •Traditional VPS/VM deployments
• •Kubernetes orchestration
• •CI/CD build environments
• •Database containerization (dev/test)

Key Capabilities:

• •Application isolation and portability
• •Multi-stage builds for optimization
• •Docker Compose for multi-container apps
• •Volume management for data persistence
• •Network configuration and service discovery
• •Cross-platform compatibility (amd64, arm64)

Cost Profile: Infrastructure cost only (compute + storage)

When to Use Google Cloud

Best For:

• •Enterprise-scale applications
• •Data analytics and ML pipelines (BigQuery, Vertex AI)
• •Hybrid/multi-cloud deployments
• •Kubernetes at scale (GKE)
• •Managed databases (Cloud SQL, Firestore, Spanner)
• •Complex IAM and compliance requirements

Key Services:

• •Compute Engine (VMs)
• •GKE (managed Kubernetes)
• •Cloud Run (containerized serverless)
• •App Engine (PaaS)
• •Cloud Storage (object storage)
• •Cloud SQL (managed databases)

Cost Profile: Varied pricing, sustained use discounts, committed use contracts

Quick Start

Cloudflare Workers

# Install Wrangler CLI
npm install -g wrangler

# Create and deploy Worker
wrangler init my-worker
cd my-worker
wrangler deploy

See: references/cloudflare-workers-basics.md

Docker Container

# Create Dockerfile
cat > Dockerfile <<EOF
FROM node:20-alpine
WORKDIR /app
COPY package*.json ./
RUN npm ci --production
COPY . .
EXPOSE 3000
CMD ["node", "server.js"]
EOF

# Build and run
docker build -t myapp .
docker run -p 3000:3000 myapp

See: references/docker-basics.md

Google Cloud Deployment

# Install and authenticate
curl https://sdk.cloud.google.com | bash
gcloud init
gcloud auth login

# Deploy to Cloud Run
gcloud run deploy my-service \
  --image gcr.io/project/image \
  --region us-central1

See: references/gcloud-platform.md

Reference Navigation

Cloudflare Platform

• •cloudflare-platform.md - Edge computing overview, key components
• •cloudflare-workers-basics.md - Getting started, handler types, basic patterns
• •cloudflare-workers-advanced.md - Advanced patterns, performance, optimization
• •cloudflare-workers-apis.md - Runtime APIs, bindings, integrations
• •cloudflare-r2-storage.md - R2 object storage, S3 compatibility, best practices
• •cloudflare-d1-kv.md - D1 SQLite database, KV store, use cases
• •browser-rendering.md - Puppeteer/Playwright automation on Cloudflare

Docker Containerization

• •docker-basics.md - Core concepts, Dockerfile, images, containers
• •docker-compose.md - Multi-container apps, networking, volumes

Google Cloud Platform

• •gcloud-platform.md - GCP overview, gcloud CLI, authentication
• •gcloud-services.md - Compute Engine, GKE, Cloud Run, App Engine

Python Utilities

• •scripts/cloudflare-deploy.py - Automate Cloudflare Worker deployments
• •scripts/docker-optimize.py - Analyze and optimize Dockerfiles

Common Workflows

Edge + Container Hybrid

# Cloudflare Workers (API Gateway)
# -> Docker containers on Cloud Run (Backend Services)
# -> R2 (Object Storage)

# Benefits:
# - Edge caching and routing
# - Containerized business logic
# - Global distribution

Multi-Stage Docker Build

# Build stage
FROM node:20-alpine AS build
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build

# Production stage
FROM node:20-alpine
WORKDIR /app
COPY --from=build /app/dist ./dist
COPY --from=build /app/node_modules ./node_modules
USER node
CMD ["node", "dist/server.js"]

CI/CD Pipeline Pattern

# 1. Build: Docker multi-stage build
# 2. Test: Run tests in container
# 3. Push: Push to registry (GCR, Docker Hub)
# 4. Deploy: Deploy to Cloudflare Workers / Cloud Run
# 5. Verify: Health checks and smoke tests

Best Practices

Security

• •Run containers as non-root user
• •Use service account impersonation (GCP)
• •Store secrets in environment variables, not code
• •Scan images for vulnerabilities (Docker Scout)
• •Use API tokens with minimal permissions

Performance

• •Multi-stage Docker builds to reduce image size
• •Edge caching with Cloudflare KV
• •Use R2 for zero egress cost storage
• •Implement health checks for containers
• •Set appropriate timeouts and resource limits

Cost Optimization

• •Use Cloudflare R2 instead of S3 for large egress
• •Implement caching strategies (edge + KV)
• •Right-size container resources
• •Use sustained use discounts (GCP)
• •Monitor usage with cloud provider dashboards

Development

• •Use Docker Compose for local development
• •Wrangler dev for local Worker testing
• •Named gcloud configurations for multi-environment
• •Version control infrastructure code
• •Implement automated testing in CI/CD

Decision Matrix

Resources

• •Cloudflare Docs: https://developers.cloudflare.com
• •Docker Docs: https://docs.docker.com
• •GCP Docs: https://cloud.google.com/docs
• •Wrangler CLI: https://developers.cloudflare.com/workers/wrangler/
• •gcloud CLI: https://cloud.google.com/sdk/gcloud

Implementation Checklist

Cloudflare Workers

• • Install Wrangler CLI
• • Create Worker project
• • Configure wrangler.toml (bindings, routes)
• • Test locally with wrangler dev
• • Deploy with wrangler deploy

Docker

• • Write Dockerfile with multi-stage builds
• • Create .dockerignore file
• • Test build locally
• • Push to registry
• • Deploy to target platform

Google Cloud

• • Install gcloud CLI
• • Authenticate with service account
• • Create project and enable APIs
• • Configure IAM permissions
• • Deploy and monitor resources