DevOps

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

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

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

<example type="usage"> <code language="bash"> # Install Wrangler CLI npm install -g wrangler

Create and deploy Worker

wrangler init my-worker cd my-worker wrangler deploy </code> </example>

See: references/cloudflare-workers-basics.md

Docker Container

<example type="usage"> <code language="bash"> # 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 </code> </example>

See: references/docker-basics.md

Google Cloud Deployment

<example type="usage"> <code language="bash"> # 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 </code> </example>

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

<example type="usage"> <code language="yaml"> # Cloudflare Workers (API Gateway) # -> Docker containers on Cloud Run (Backend Services) # -> R2 (Object Storage)

Benefits:

- Edge caching and routing

- Containerized business logic

- Global distribution

</code> </example>

Multi-Stage Docker Build

<example type="usage"> <code language="dockerfile"> # 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"] </code> </example>

CI/CD Pipeline Pattern

<example type="usage"> <code language="yaml"> # 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 </code> </example>

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

<constraints> <constraint severity="critical">Never commit secrets, API keys, or credentials to version control</constraint> <constraint severity="critical">Always run containers as non-root user in production</constraint> <constraint severity="high">Scan container images for vulnerabilities before deployment</constraint> <constraint severity="high">Implement health checks for all containerized services</constraint> <constraint severity="medium">Use multi-stage Docker builds to minimize image size</constraint> <constraint severity="medium">Set resource limits (CPU, memory) for all containers</constraint> </constraints>

Decision Matrix

| Need | Choose | |------|--------| | Sub-50ms latency globally | Cloudflare Workers | | Large file storage (zero egress) | Cloudflare R2 | | SQL database (global reads) | Cloudflare D1 | | Containerized workloads | Docker + Cloud Run/GKE | | Enterprise Kubernetes | GKE | | Managed relational DB | Cloud SQL | | Static site + API | Cloudflare Pages | | WebSocket/real-time | Cloudflare Durable Objects | | ML/AI pipelines | GCP Vertex AI | | Browser automation | Cloudflare Browser Rendering |

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