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devops

SKILL.md

DevOps Skill

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

Summary

Goal: Deploy and manage cloud infrastructure across Cloudflare (edge), Docker (containers), and Google Cloud Platform (managed services).

Step Action Key Notes
1 Platform selection Cloudflare (edge/low-latency), Docker (microservices), GCP (managed)
2 Configure infrastructure Workers, containers, or GCP services
3 Set up CI/CD Automated build, test, deploy pipelines
4 Deploy Multi-region, zero-downtime strategies
5 Monitor Health checks, logging, cost optimization

Key Principles:

  • Choose platform based on latency, cost, and architecture requirements
  • Cloudflare for edge-first with zero egress; Docker for portable microservices; GCP for managed scale
  • Always automate deployments — no manual production changes

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

⚠️ MUST READ: 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

⚠️ MUST READ: 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

⚠️ MUST READ: 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

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

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

IMPORTANT Task Planning Notes

  • Always plan and break many small todo tasks
  • Always add a final review todo task to review the works done at the end to find any fix or enhancement needed
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