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name: devops description: Deploy and manage cloud infrastructure on Cloudflare (Workers, R2, D1, KV, Pages, Durable Objects, Browser Rendering), Docker containers, and Google Cloud Platform (Compute Engine, GKE, Cloud Run, App Engine, Cloud Storage). Use when deploying serverless functions to the edge, configuring edge computing solutions, managing Docker containers and images, setting up CI/CD pipelines, optimizing cloud infrastructure costs, implementing global caching strategies, working with cloud databases, or building cloud-native applications. license: MIT version: 1.0.0

DevOps Skill

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

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

Create and deploy Worker

wrangler init my-worker cd my-worker wrangler deploy

See: references/cloudflare-workers-basics.md

Docker Container

Build and run

docker build -t myapp . docker run -p 3000:3000 myapp

See: references/docker-basics.md

Google Cloud Deployment

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

Benefits:

- Edge caching and routing

- Containerized business logic

- Global distribution

Multi-Stage Docker 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

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