home / skills / jackspace / claudeskillz / devops_mrgoonie

devops_mrgoonie skill

/skills/devops_mrgoonie

This skill helps you deploy and manage cloud infrastructure across Cloudflare, Docker, and Google Cloud with CI/CD, cost optimization, and edge first patterns.

This is most likely a fork of the devops skill from mamba-mental
npx playbooks add skill jackspace/claudeskillz --skill devops_mrgoonie

Review the files below or copy the command above to add this skill to your agents.

Files (4)
SKILL.md
8.1 KB
---
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.

## 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

```bash
# 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

```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
```

See: `references/docker-basics.md`

### Google Cloud Deployment

```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
```

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

```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
```

### Multi-Stage Docker Build

```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"]
```

### CI/CD Pipeline Pattern

```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
```

## 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

- **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

Overview

This skill helps deploy and manage cloud infrastructure across 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). It consolidates practical commands, patterns, and decision guidance so you can choose the right platform and deploy reliably. The content focuses on edge-first architectures, container workflows, CI/CD pipelines, cost optimization, and operational best practices.

How this skill works

The skill inspects platform trade-offs and provides concrete steps for common tasks: initializing and deploying Cloudflare Workers, building and running Docker images, and deploying containerized services to GCP. It includes quick-start CLI snippets, multi-stage Docker patterns, CI/CD pipeline outlines, and a decision matrix mapping needs to platform choices. You get checklists and recommended workflows for hybrid edge+container architectures, cost controls, and security hardening.

When to use it

  • Deploy serverless functions to the edge with ultra-low latency
  • Containerize apps for consistent local and CI environments
  • Run production containers on Cloud Run, GKE, or Compute Engine
  • Implement global caching and edge-first routing with Cloudflare
  • Set up CI/CD pipelines that build, test, push, and deploy across platforms
  • Optimize cloud costs and right-size infrastructure for sustained workloads

Best practices

  • Run containers as non-root and scan images for vulnerabilities
  • Use multi-stage builds to minimize image size and attack surface
  • Store secrets securely; prefer provider secret stores or env injection in CI
  • Implement edge caching and use R2 for zero-egress object storage when applicable
  • Right-size resources and enable health checks, timeouts, and autoscaling
  • Use least-privilege service accounts and audit IAM regularly

Example use cases

  • Edge API gateway: Cloudflare Workers fronting Cloud Run backend services with R2 for assets
  • Local development: Docker Compose for multi-service stacks and Wrangler dev for Workers
  • Hybrid workflow: static site on Cloudflare Pages + serverless API on Workers + state in D1/KV
  • CI/CD pattern: build (multi-stage), test in containers, push to registry, deploy to Cloud Run or Workers
  • Global real-time app: Durable Objects for stateful WebSocket coordination and Cloudflare Browser Rendering for headless tasks

FAQ

Which platform should I pick for sub-50ms global latency?

Choose Cloudflare Workers for sub-50ms global latency and edge-first routing; pair with KV or D1 for lightweight state and R2 for object storage.

When is GCP a better choice than Cloudflare or Docker alone?

Use GCP for enterprise-scale needs, complex IAM/compliance, managed databases, large-scale Kubernetes (GKE), and heavy data/ML pipelines like BigQuery and Vertex AI.